Tech has always been all about efficiency and automation. With AI, it’s getting ever easier to automate.

Before the agentic wave, I vibe-coded my own automations in n8n. I was very proud of a screenshot categorisation tool I built that took me 2 hours to wire together Telegram, Cloudflare, and a library in Notion. Today I could set up the same thing with one agent in less than a minute.

I do love my Grok bots. They do all sorts of stuff that frankly adds absolutely no value to me as an investor and operator. They’ll prepare a note for my weekly team catch-up; they’ll do the invoices... It’s all absolutely boring!

At the same time, it’s so easy to get swept up in the efficiency of it all that you’re tempted to go fully automated and just become a bot manager. But on the other hand… I chose this career, so why the hell would I want to automate the very things that make me good at it?

This brings me to the point - some things just shouldn’t be automated. Last week Hilary Gridley (one of my absolute favourite Substack writers) published an essay on writerbuilder entitled “What not to automate“, and that’s what inspired me to think about my own approach.

She categorises work as downhill and uphill:

“Downhill is when I’m just trying to get somewhere, and all that matters is getting there. If I’m headed downhill anyway, why not take the sled?

Uphill is different. Uphill is the climb that makes me better at something. Struggling through an essay makes me a better writer and a better thinker. Struggling through formatting that essay in Substack does not.”

It made me think about which parts of my job push me uphill, and what I’ve been subconsciously unwilling to automate, despite all the pressure (both external and internal) to automate myself as much as possible.

I landed on these 6:

(1) Researching a topic

AI is extremely useful in getting you to the right sources and the articles / people that are worth reading.

But to me, good research is a bit like sightseeing in a new place. You’ve got a destination in mind, you go there, and you see all sorts of interesting things along the way. The little details are what make it such a good trip.

Research works in the same way. There’s value in just going through the material, combining all the different perspectives in your head and coming up with a piece of something that someone else referenced, which your AI completely missed because it didn’t quite match your prompt.

Shiri Melumad (Wharton) and Jin Ho Yun (New Mexico State University) looked at this in 7 experiments with thousands of participants. People were taught about a topic (e.g. how to plant a vegetable garden) either via an LLM (e.g. ChatGPT) or via a standard Google search and then were asked to write some advice on it. The group who’d used the LLM spent less time with their sources, felt they knew less and produced shorter advice with fewer facts. In a separate study, 1,501 of the readers (who didn’t know which group had produced the advice) rated the advice produced via the LLM as less helpful and less trustworthy. The authors conclude that “relying on pre-synthesised summaries can transform learning from an active quest to a passive activity” (PNAS Nexus, October 2025).

The pattern predates AI. When the scientific journals moved online, James Evans looked at 34 million articles and found that researchers were citing fewer papers, and those they did cite were more recent (Science, 2008). His explanation was that search and hyperlinks get you to the consensus much faster. A summary gets you there even faster, by skipping the detours.

(2) Thinking through a deck

The second thing I wouldn’t want to automate is actually a fairly big part of deck making, which is working out how we want to communicate something and what actually goes on the slides.

People hate presentations, but a deck is still one of the clearest ways of presenting an idea with visuals. You can quite easily spot which decks have been produced by AI and I don’t think there’s anything wrong with that at all. In Hilary’s terms, building the deck is the downhill side.

Deciding what to say is the hard bit. Every time you’re selling an idea, a project, a startup or a fund you’re going to have to work through the deck and think very carefully about how you’re going to tell the story and how you’re going to say it.

Like a good speech or letter, the shorter the piece, the more thought it takes. Blaise Pascal apologised for exactly that in one of his letters, in a now famous line: “I have made this longer than usual because I have not had time to make it shorter.” That’s why startups spend weeks preparing for a three-minute pitch at demo day.

If you’re having AI do the deck then you skip the drafts that you’d normally show your colleagues, their feedback and the subsequent iteration. Those conversations are often where relationships get built, too.

(3) Portfolio conversations

This is the one that’s obvious. Part of my VC job is matching up our portfolio companies with executive advisors. A large element of that could be automated: agents collecting information from the investment memo and the investor updates that the company sends, what it needs from an advisor, perhaps a form for the founders to complete.

I still prefer to do it on a call and go through all the interesting bits together, because a call gives me far more data and lets me build a relationship with the founder.

(4) Networking (and I mean actually talking to people)

AI is absolutely great at finding people. I’ve got a Grokbot that suggests who I should connect with on LinkedIn and Substack. It’s been a massive game changer and has helped me find loads of interesting people.

At the same time, I think using AI to communicate with other human beings should be a crime. Things like writing AI-generated (often automated, badly) comments to engage with someone on social media, and sending automated emails where the first line is “personalised” in a very fake way, are just so cringe!

(5) Writing

There’s a very big difference between outsourcing the editing and outsourcing the thinking. As historian David McCullough put it:

Writing is thinking. To write well is to think clearly. That’s why it’s so hard.

Whenever I try to put my thoughts together with a bot, or in Notion, the result is never as good or as crisp as going offline, taking a pen and writing down everything I want to say. Then I build on it, and yes, I use AI to look for other avenues and perspectives. But never for the very first draft. The first draft is where the thinking happens, and that’s exactly the part I want to do myself.

(6) Understanding ecosystem depth and market sentiment

AI is absolutely invaluable for podcast, news, and event summaries at both the macro and micro level in the markets I focus on. That said, at the very early stages of venture investing, you do still need to talk to people to get a feel for what’s going on and what your stakeholders actually think.

When something major happens politically in one of our markets, I don’t want to outsource forming my view. I’d much prefer to talk to the startups on the ground and hear how they describe what’s going on.

Abu Dhabi

WatchHouse, a London coffee brand, opened its Abu Dhabi café at The Arcades inside the Abu Dhabi Equestrian Club. The banana cheesecake is rich and generous. The texture is dense and smooth. The banana adds a mellow, ripe sweetness to the filling, a great twist.

@ Modern Coffee by WatchHouse, The Arcades - Banana cheesecake

Copenhagen

I visited 12 restaurants and coffee shops in Copenhagen last week, but none served a proper cheesecake!

Cheesecake isn’t really Danish, so I’m breaking the pattern here. No cheesecake review from Denmark this time, just two desserts I really liked instead.

#1 Cardamom bun at The Roe Bar

This was the best pastry I had in Copenhagen. The dough is soft and buttery, twisted into a knot with cardamom sugar baked into every fold. The Roe Bar is the café inside the Louise Roe gallery on Vognmagergade, and its pastries come from Juno the Bakery, which was founded by former Noma chef Emil Glaser. Juno definitely deserves some credit.

#2 Danish pastry with cheesy cream and fig at Hart Bageri

This was the closest I got to cheesecake on the whole trip: flaky layers, a lightly tangy cheese cream, and fig for sweetness. Richard Hart opened Hart in 2018 after working as head baker at Tartine in San Francisco and starting out in Noma’s kitchens. I’ve heard their cheesecake is really good (back in 2019, their almost-burnt Basque cheesecake drew crowds), but it’s not on the menu right now.

Florence

Osteria delle Tre Panche has used the same cheesecake recipe since 1986. It’s famous enough that when the restaurant ran a pop-up in New York in 2022, whole cheesecakes to take home were priced at $180.

The texture is soft and custardy, and the slice is much lighter than you’d expect from a cheesecake. It’s a dessert you can still say yes to after a plate of pasta. The dining room is beautiful, and even though it’s in the Centro Storico, steps from the Ponte Vecchio, it doesn’t feel touristy at all.

@ Osteria delle Tre Panche, Centro Storico - Cheesecake

Warsaw

Almost 2 years ago I wrote that Polish cheesecakes were boring: too creamy, not cheesy enough, and sometimes full of raisins. Koneser Grill was the exception, and its Basque cheesecake with honey and truffle ranked #4 on the Global Cheesecake Ranking in December 2024. It’s been my answer to “where’s the best cheesecake in Warsaw?” ever since.

Not anymore. Now, the best cheesecake in Warsaw is the Basque cheesecake at Warszawa Wschodnia, Mateusz Gessler’s restaurant in the old Soho Factory complex in Praga. (That’s the restaurant, not the train station.)

The top is deeply burnt and dark, with the slight bitterness that a proper Basque cheesecake should have. Underneath, the texture is perfect: creamy and smooth, but not too heavy. It comes with raspberries, and their bright, tart bite works beautifully with the cream.

Honestly, it’s just perfect. This is my new favourite in Warsaw.

@ Warszawa Wschodnia by Mateusz Gessler, Soho Factory - Basque cheesecake

Sources:

FACT Magazine: WatchHouse Abu Dhabi

Time Out: Osteria delle Tre Panche pop-up in SoHo

Only the best investors get a chance to invest in the top deals. But what does it really mean to be “the best investor”?

The problem is that the venture market is usually not the most transparent, so it’s hard to know for sure. Until recently, the main industry ranking was Forbes’s well-known Midas List, which is a mix of performance and vibes.

About a year ago, I looked into VC investors’ career paths. My main takeaway was that the biggest indicator of success is going to an Ivy League school (=network).

Only 42% of investors on the 2024 and 2025 Midas lists had previously been founders. So, being a founder didn’t seem to play a big role in becoming a top investor.

People in venture capital usually fall into two camps. Some think you need to be a successful founder to become a great investor (i.e., you only know how to invest and help companies if you’ve founded a successful company yourself). Others believe investing and founding require different skills, i.e. “You don’t need to suffer a disease to cure it.”

So, does being a founder really make someone a better investor? When I saw Ilya Strebulaev’s new rankings, I had to check this pattern again. This time, I looked at more reliable data and both top VC and top angel rankings.

TL;DR

No. You don’t need to be a founder to be an exceptional investor. But being a founder seems to help, especially in angel investing.

US Angels: Founders are common among the top performers

Ilya Strebulaev’s US angel ranking looks at how many unicorns each angel investor backed early, before the company hit a $1 billion valuation.

Starting a company is common among the top US angel investors. 79% of the best angels on the list founded a tech startup, and that number goes up to 84% in the top 50. Founders still back about 16% more unicorns than angels who weren’t founders.

But you don’t have to be a founder to make the list. About one in five angels never started a tech company, including Tim Draper (#36) and Henry Kravis (#64).

Going to an elite school is also common (59% of the top angels did), but it doesn’t affect their rank. Max Levchin (#16), Paul Buchheit (#13), Alexis Ohanian (#25), and Marc Benioff (#7) all founded companies, but none went to a school considered elite.

Top US VCs: Many have MBAs, fewer are founders

The VC list measures something different. Strebulaev ranks VCs by the value of their recent deals, while the angel list counts lifetime successes. 14 people appear on both lists.

Less than half of the top VC partners started a tech company (43% vs 42% in the Midas List analysis), compared to 79% of the angels. More than half have an MBA (57 out of 100), and 78% went to an elite school, compared to 59% of angels.

What about Europe?

I tried to do the same analysis for Europe, looking at angels from Dealroom’s Power Law list and Europe-based investors from Forbes Midas List Europe 2022-2025. These are very small samples (13 for angels and 34 for VCs) and use different criteria. Regardless, in Europe, the angel pattern is even stronger, while the VC pattern leans the other way.

All the top European angels with confirmed backgrounds are founders, including the founders of Wise, Supercell, Mollie, and Iliad. This is partly because Dealroom mostly tracks angels who are already well-known founders. For VCs, it’s different.

For VCs, elite schooling is just as common as in the US (78%).

How about other regions?

I looked at top angels and VCs from LatAm, Africa and Asia.

Emerging-market angels are more similar to American ones than European ones: 17 out of 21 confirmed (81%) started a tech company, compared to 79% in the US and 100% in Europe. All 11 confirmed Asian angels did as well. Differences within the region stand out even more. Almost all Latin American angels studied business and most studied abroad, while Asian angels are more likely to be engineers. For emerging-market VCs, the trend is reversed: only 4 out of 11 founded a startup, a significant gap compared to angels.

*The sample is small, with 28 angels and 11 VCs from a few countries.

Take the data with a grain of salt

Every ranking uses different methods. Also, these winner lists can’t tell us whether firms look for certain credentials or whether people with those credentials just tend to go into VC. For now, it’s a good theory to keep in mind.

Seven out of ten angels and 63 of the 100 VCs are based in California, so this reflects just one ecosystem. Some people might say, “You need to be in California if you want to be a great VC,” but that’s only because the data is US-only by design 🤷🏼‍♀️.

Other data sources:

• Forbes Midas List, used for European VCs (the Midas List Europe, 2022 to 2025) and for the Indian and Singapore VCs

• NeoFeed: most admired angel investors in Brazil, used for Brazil’s angels

• LAVCA Top Women Investors (via Startups.com.br), used for Brazil’s VCs

• Forbes México: 50 most influential LatAm angels, used for Mexico’s angels

• Moneycontrol: top super angels of 2021, used for India’s angels

• Inc42: most active angel investors in India, used for India’s angels

• Forbes Middle East: top venture capitalists 2024, used for Egypt’s VCs

About a month ago, Claire Vo, founder of ChatPRD and host of the How I AI podcast, got me hooked on GrokBots. Since then, I’ve explained my GrokBot setup at least ten times, so I thought I’d share what I’ve borrowed from other investors and what I’ve built myself.

I’ve heard someone calling Grok bots a “Canva moment for AI agents,” and I cannot unsee it.

They’re incredibly easy to set up. I expect OpenAI’s dots will be just as simple. So, think of this article as general bot inspiration, not just about GrokBot. Dots are about seven weeks newer than GrokBot, and I don’t think they’re quite ready yet (or at least that’s what my YouTube research suggests).

What makes GrokBot different

First, each bot gets its own cloud computer. They can log into sites and do anything you would, and they keep working even when your laptop is closed. If a bot gets stuck logging in, you can step in, take over, and help.

Second, with GrokBot, you hire bots instead of building workflows. Each bot has a simple job and routine, which appeals to non-technical people. When bots need to work together, you can add a manager bot to coordinate them. My chief of staff bot (see bot 2 below) does this for me.

Third, you can connect several accounts for the same tool. For me, it’s a game changer- I have multiple Gmail accounts. GrokBot lets me keep my work-related bots and personal bots in one place.

OpenClaw and Hermes are open-source agents you install and run yourself, which can feel intimidating if you’re not technical. GrokBot is so simple that I even told my mum she should have one 🙂

One thing you need to consider is giving your bots access to your email, calendar, X, and any other media you use. In my experience, you won’t get the full value from them otherwise. If you don’t want to do that, a good solution is to set up a separate Gmail inbox and forward only what the bot needs to that address.

Another important rule I recommend is to review and humanise automated outreach or messages before sending them. It’s tempting not to, but in the end it makes people think you’re lazy.

Getting started

Here’s a simple onboarding guide from Cursor.

Before you build anything, take a look at the GrokBot marketplace where you can find ready-made bots.

For my setup, I followed advice from Roman Ugarte, who helped build GrokBot. He suggests thinking of your bots like new employees. Each one has its own area of expertise and needs proper onboarding to succeed.

(1) Bot designer - Dr Eggbot

This bot is from the marketplace. His job is to build new bots. You share your bot idea with Dr Eggbot, and it asks a few questions and builds the bot for you.

I suggest using it to build every other bot on this list.

Tip: You can also ask it to colour-code your bots. For example, I make my work bots blue, personal ones pink, and side projects purple.

(2) Chief of staff

Chief of staff takes your requests and delegates them to other bots, reviews your meeting notes, tells you what you promised and asks you if you did it :) Polly (my ChoS) is my accountability manager.

Tell your bot designer:

Build me a chief of staff bot.

Job: take my messy requests, send each one to the right bot, and keep one list of everything still open. Review my meeting notes and tell me every evening what I promised, and ask whether I delivered. If it's obvious from my inbox, you don't have to mention it.

Reads: my chats with it, my meeting notes from [your meeting notes tool], my email and my calendar.

Runs: whenever I message it, plus every weekday evening at [time] in [time zone].

Sends: each evening, a short list of promises I made to other people in meetings, asking, "Did you do these?" It drops the items I confirm as done. Replies are short and crisp. It asks a question only when it's blocked; otherwise, it assumes and states it.

Never: does deep specialist work itself (it hands that to the right bot), or sends, posts or replies on my behalf without my explicit yes.

Finding companies

(3) Stealth founder scout

Stolen from: Francis Santora, angel investor

Stealth founder scout searches Hacker News, Crunchbase, X, Reddit and Product Hunt for early-stage companies with accomplished founders. Twice a week in the morning, it texts me a table of what it found.

You can point it at any website or page you follow to scan for hackathon winners or conference speakers.

Tell your bot designer:

Build me a stealth founder scout bot.

Job: find early-stage companies with accomplished founders in [your sector] and [your region].

Reads: Hacker News, Crunchbase, X, Reddit, Product Hunt, [your local news site], and lists of conference attendees and hackathon winners in [your region].

Runs: twice a week, on [days] at [morning time] in [time zone].

Sends: a text with a table of company, founder, why the founder stands out, stage, and a source link. A source for every claim; "couldn't verify" rather than guessing.

Never contact founders, or send posts or replies on my behalf without my explicit yes.

(4) Funding round tracker

This bot logs new funding rounds in your sector or region, including the amount, lead investor, and a source for each.

Tell your bot designer:

Build me a funding round tracker bot.

Job: log new funding rounds in [your sector] and [your region], and keep a running list I can search later as a co-investor map.

Reads: [your go-to news sites], X and Crunchbase.

Runs: once a week, on [day] at [time] in [time zone].

Logs: for each round, company, amount, round stage, lead investor, other investors, date, and a source link, including the founder's own announcement when there is one. "Undisclosed" when a number isn't public; "couldn't verify" rather than guessing.

Never: invents amounts or investors, or sends, posts or replies on my behalf without my explicit yes.

Research and staying on top of things

(5) Call prep buddy

Before each call, it writes a short brief and suggests questions to ask the founder/person you’re meeting.

Tell your bot designer:

Build me a call prep bot. 

Job: write a short brief on a company before my first call with its founder.

Reads: my calendar, the intro emails, the company website, the founders' LinkedIn profiles, news and X.

Runs: whenever I ask

Sends: a brief of no more than one page, with three sections: what we know, what we don't know, and three questions the founder can't answer with their standard pitch. A source for every claim; "undisclosed" or "couldn't verify" rather than guessing.

Never: replies to the founder or the person who made the intro, or sends, posts or replies on my behalf without my explicit yes.

(6) Podcast summarizer

Stolen from: Gavin Baker, A16Z podcast

This bot summarises podcasts you don’t have time to listen to.

Tell your bot designer:

Build me a podcast summarizer bot.

Job: summarise podcasts I don't have time to listen to.

Reads: the episodes I send it, plus new episodes from [list of podcasts].

Runs: whenever I send an episode, and weekly on [day] for new episodes on my list.

Sends: for each episode, title and link, a five-line summary, and three key takeaways.

Never: sends, posts or replies on my behalf without my explicit yes.

(7) Substack digest reader

Mine is called Substack Nerd. It reads every Substack newsletter that landed in your inbox overnight and tells you each one’s main takeaways, so you know which ones are worth opening.

You can set it up to read any newsletters you subscribe to, not just Substack, and adjust it for your field. Mine puts VC and emerging-markets pieces first, with lighter reads at the end.

Tell your bot designer:

Build me a newsletter digest bot.

Job: summarise the newsletters I receive.

Reads: my [Gmail] inbox, read-only, covering mail since the last run. It opens each article in full and follows the link to the public post when the email is only a teaser.

Runs: every morning at [time] in [time zone].

Sends: activity on my own publication first (new subscribers, comments), then the pieces most relevant to [your field], then the rest. For each piece, it gives the publication, title, link, two to four main takeaways, and one line on why it matters to me. It flags anything paywalled or a video it couldn't watch.

Never sends, replies to, labels, archives, or deletes any email, and never makes up facts it didn't read. It stays quiet when there's nothing new.

Portfolio and LPs

(8) Portfolio news watcher

Stolen from: David Cummings, Atlanta Ventures

Portfolio news watcher tracks every company in your portfolio for news and online announcements and emails you a weekly summary. If a company hits a major milestone, like launching a new product, it drafts a congratulatory message and puts it in your email drafts.

If you add your portfolio companies’ main competitors, you might learn about a rival’s funding round before your founder does.

Tell your bot designer:

Build me a portfolio news watcher bot.

Job: track my portfolio companies and their main competitors.

Reads: the websites, news coverage, press releases and online sentiment for [list of portfolio companies] and [list of competitors].

Runs: continuously, with a weekly summary by email every [day] at [time].

Sends: a weekly summary by company covering website changes, news, sentiment and competitor moves, each with a source link. When a portfolio company hits a major milestone, such as launching a new product, it puts a short congratulations draft in my email drafts for me to review. "Couldn't verify" rather than guessing.

Never: sends the congratulations note or anything else on my behalf without my explicit yes.

(9) Exit and liquidity tracker

Stolen from: Paul Klay, Begin Capital

The exit and liquidity tracker watches exits and shutdowns and sorts them into real liquidity events, acqui-hires, and shutdowns.

Tell your bot designer:

Build me an exit and liquidity tracker bot.

Job: watch exits and shutdowns in [your sector] and [your region] and sort each one.

Reads: news sites, X, Crunchbase and company announcements.

Runs: checks every [frequency], sends a summary every day.

Sends: for each event, company, buyer, date, a label (real exit, acqui-hire or shutdown), why it chose that label, and a source link. For real exits, who likely got liquidated, as a possible LP lead. For acqui-hires and shutdowns, the team that may soon be free. "Undisclosed" or "couldn't verify" rather than guessing.

Never: contacts anyone, or sends, posts or replies on my behalf without my explicit yes.

Other productivity tasks

(10) Writing team: my team of bots

For my Substack writing, 4 bots work together. Topic Scout suggests topics relevant to my audience. Once I approve it, the researcher returns arguments, counterarguments, data, and sources, and flags anything it couldn’t verify. Then the prompt writer takes over and turns that research into a writing prompt I can use later in Claude. After I publish, I’m letting my bot know that the article was published, and my Substack and my distribution bot called Elena (I named it after the ultimate suggest to me LinkedIn posts and notes that I can share in order to promote the article

You can use this same process for LP updates or a portfolio newsletter.

Tell your bot designer (one request per bot):

Topic scout

Build me a topic scout bot.

Job: suggest writable topics for [your publication or LP update] in [your topics].

Reads: the news, X and newsletters in my field, plus any ideas I send it.

Runs: every morning at [time] in [time zone], and whenever I send an idea.

Sends: exactly 5 numbered topics, each with a one-line angle, why it fits, and a real recent spark with a link. It saves any idea I send as a pending topic.

Never: invent sources, research deeply or write drafts.

Researcher

Build me a researcher bot.

Job: research a topic I pick.

Reads: the web, reports and articles.

Runs: whenever my topic scout or I send it a topic.

Sends: a brief with a core angle, key arguments, counterarguments, data and examples, sources, and open questions. A real source for every claim; "couldn't verify" next to anything it can't confirm.

Never: invent sources, quotes or numbers, or write the article.

Prompt writer

Build me a prompt writer bot.

Job: turn a research brief into a writing prompt tuned to my voice.

Reads: the research brief and these samples of my writing: [links to 2 or 3 of your pieces].

Runs: whenever a research brief is ready.

Sends: one copy-paste writing prompt covering audience, my voice, the angle, an outline, must-include facts with sources, what to avoid, and target length [word count].

Never: add facts that aren't in the brief, or write the article itself.

Distribution

Build me a distribution bot.

Job: turn a published piece into social drafts.

Reads: the published piece I send it.

Runs: whenever I send a published link.

Sends: [number] Substack Notes and [number] LinkedIn posts, each ready to paste, using only lines and facts from the piece.

Never: posts, schedules or publishes anything. I copy and post every draft myself.

(11) Outreach drafter

It drafts intros, follow-ups and connection requests after looking each person up in a contact-data tool like Apollo. Nothing goes out until you approve it.

Tell your bot designer:

Build me an outreach drafter bot.

Job: draft intros, follow-ups and connection requests to people I want to reach.

Reads: [your contact-data tool, for example Apollo] to look each person up, plus their LinkedIn and anything I tell it about why I'm reaching out.

Runs: whenever I name a person and a goal.

Sends: for each person, a two-line summary of who they are, the best channel (email or LinkedIn) and why, and a short draft message in my voice that I'll rewrite.

Never: sends anything (nothing goes out until I say send), or manages or triages my inbox.

(12) Best student

What it does: keeps track of the deadlines and readings for a course you’re taking and reminds you before each one is due. Mine does it for my Stanford leadership program.

Tell your bot designer:

Build me a study assistant bot.

Job: track deadlines and readings for [your course].

Reads: [course portal, syllabus or board pre-read folder], my email and my calendar.

Runs: checks daily and reminds me [number] days before each item is due, at [time] in [time zone].

Sends: for each reminder, what's due, the due date, how long it will likely take, and a link; every Monday, a list of the week's deadlines.

Never: submits assignments or replies to anyone on my behalf without my explicit yes.

Bots for fun

(13) Local culture scout

Mine is called Inshallah.

What it does: finds non-commercial events in your city: art, underground cinema, classical and underground music.

(The name is a joke. Here, “inshallah” (God willing) is the standard answer to “are you coming tonight?” and can mean yes, maybe, or no.)

You can swap the categories for anything that doesn’t usually show up on the big listing sites in your city, like talks or supper clubs.

Tell your bot designer:

Build me a local culture scout bot.

Job: find non-commercial events in [your city].

Reads: local venue sites, community pages, social media and newsletters, looking for [your categories, for example, art, underground cinema, classical and underground music].

Runs: every [day] at [time] in [time zone].

Sends: a short list for the coming week. For each event, name, date and time, venue, one line on why it's worth going, and a link. "Couldn't verify" if details are unclear.

Never: suggests big commercial events, or books or buys tickets without my explicit yes.

(14) Personal stylist

Mine is called Miranda (iykyk). She learns your taste and sends you a short list of clothes every two weeks. It has access to my Pinterest board, so it understands my style. It knows what size I’m wearing, and it knows what shops and materials I like

You can use this for books, wine, or restaurants, too.

Tell your bot designer:

Build me a personal stylist bot.

Job: learn my taste and find [clothes, books, wine or restaurants] I'll like.

Reads: what I tell it about my taste, the Pinterest board [link], sizes [your sizes] and budget [your budget], and what I liked or rejected before. It searches shops that deliver to [your country]. 

Runs: every two weeks on [day] at [time] in [time zone].

Sends: a short list of [number] items, each with name, price, a link, and one line on why it fits me. It learns from my reactions.

Never: buys anything without my explicit yes.

PS. When doing the research for this article, I found this super cool website where people share what they’ve built with Grok bots, and there are almost 4000 use cases here: https://www.grokbots.de/en/

PS2. This article is AI-assisted. I used GrokBot Chief of Staff to describe my setup and write the prompts accordingly.

I get it, you want to be efficient. Everyone is doing it. There is AI content everywhere. AI-generated Substack posts, AI-generated presentations, music…

But using AI to get other humans’ attention is a crime.

I checked each cold outreach email and LinkedIn message I received in the last month using Pangram. I was shocked. 82% of them were 90-100% AI-generated!

But it’s not only me. The ultimate boss of early-stage investing says the same thing.

So this tells me some founders think it’s ok, it’s efficient, and maybe that investors don’t mind it at all. At the end of the day, they should be the strongest “tech advocates”.

For most, it’s not ok. Let’s nerd about it.

Making a good first impression

Obviously, you reach out to people for a reason (in this context, a business reason). Getting in touch and making a bad first impression is pointless because it gets you nowhere near your goal of making a connection. But that’s exactly what happens with AI-automated outreach. The message itself isn’t the main issue here, but what the text makes the recipient infer about the person behind it.

Here’s what we know:

Firstly, people form first impressions extremely quickly. In fact, research suggests that we don’t consciously decide to form a first impression; our brains do it automatically (Source).

Secondly, people form opinions about you before they have enough information to evaluate you properly. People can also form impressions about others from surprisingly little information (Source).

Third, research suggests that two fundamental dimensions matter most in how we perceive other people: warmth (whether someone seems well-intentioned) and competence (whether someone seems capable) (Source).

In other words, when you send someone a message, they’re evaluating you, not the message.

The AI Ick

And this is where AI makes things more complicated. Research suggests that when people know AI wrote a message, they judge the person behind it differently.

In a recent study published in Computers in Human Behaviour, participants who knew a message had been AI-generated formed more negative impressions of its sender as a person, associating them with qualities such as being “lazy,” “insincere,” or putting in less effort.

AI use, then, matters a lot for first impressions. When people know someone has used AI, they perceive that person as less competent and less warm 🚩🚩🚩.

People quickly infer the person behind it: “If you used AI to write this message, how much did you actually care about sending it to me or the topic you’re writing about?” (Source)

The irony is that the sender may have used AI because they cared about being efficient, professional and just doing it to the best of their abilities. The recipient, on the other hand, may interpret the same behaviour as evidence that they didn't care enough to put in the effort.

In the VC-startup context, it’s hard not to think of AI-generated messages in the following way:

1. This person who sent it is desperate to fundraise.

If you blast the same AI-personalised message to hundreds of investors, it can look like you’re hoping that volume will compensate for a lack of interest. As much as no one wants to date someone desperate, no investor wants to invest in desperate companies.

2. This founder isn’t taking this seriously enough.

If you’re asking someone to invest in your company, why outsource the very first impression you can make to a machine?

Of course, those are interpretations. A founder can be highly committed and still use AI to write an email. But first impressions are built from the signals available to us.

What works then

Cold outreach isn’t going anywhere. But it needs to be more thoughtful than ever before.

I actually do a fair amount of cold outreach myself, mostly to find potential executive advisors and board advisors for companies we invest in. These are often people I have never interacted with, in different countries, and in very senior positions.

My process is a classic human-in-the-loop, with a simple rule: automate the work, not the relationship.

So no, maybe it’s not the most scalable process. But since my objective is to build a relationship, automating the very first message to the person I want to build a relationship with has never seemed like a good option. Here’s the process that works for me:

1. Research the right people

I use Claude/Grokbot (his name is Richard) and Apollo to research who I should actually reach out to.

To get one advisor, I typically target about 20 profiles that meet my founders’ criteria.

2. Enrich the data

Apollo helps me find the relevant contact information and enrich the profiles.

3. Decide how to reach out

I manually review the profiles and decide whether LinkedIn or email makes more sense. My response rate is usually higher on LinkedIn, and I choose LinkedIn if I see that the person is active there. I choose email if they aren’t.

I tend to use LinkedIn more often because I like that the person can immediately click on my profile and see that there is a real human on the other side.

4. Draft the v1 of the message

This is where I happily use AI. For email outreach, Grok writes drafts for me and leaves them in my Gmail drafts. For LinkedIn outreach, Grokbot prepares a document with a link to the LinkedIn profile and a suggested message.

Of course, Grokbot and Claude are supposed to know my writing style, but it’s still not quite there, so the next step is…

5. Humanise it

I read every single message. I make sure it sounds like me.

I’m not a native English speaker, so I do use Grammarly; I have been Grammarly-maxxing since my master’s degree in the UK in 2017. But that’s very different from asking AI to create an impression of me.

**Sent**

AI can help me get to the starting point faster, but it never decides how I sound.

Of course, it’s cold outreach, so response rates vary. I also don’t reach out to 1000 people a month, so I know it might not apply to everyone.

At the end of the day, I’m not trying to convince anyone to stop using AI for outreach. Quite the opposite! As much as it’s a crime to use it in the first message, it’s also a crime not to leverage it to find people, enrich the data and set follow-up reminders (Grokbot is also great for follow-ups).

Because AI will make it increasingly easy for everyone to sound personalised, and when everyone can sound personalised, sounding human may become the real competitive advantage.

Here are 3 notes I’d like to share from an incredible event I attended in Florence this summer: the Stanford International Alumni Weekend, aka #SIAW26.

Note #1: Do AI to others as you would like others to do AI to you

Clay’s AI writing policy recently went viral all over our usual AI/VC/tech bubble. While Clay’s policy mostly covers AI-written text that other people will read, the slightly older, less viral “Guiding Principles for AI” from Stanford covers every AI system the university buys, builds, or uses.

Russ Altman chaired Stanford’s advisory committee on AI, and in Florence he shared the committee’s output. I found it extremely relevant for the wider startup and VC context:

(1) Human oversight: every AI system needs a named person who answers for it, from the day it’s bought or built to the day it’s switched off.

(2) Human alignment: AI should serve the organisation’s mission and values, and the people it affects should be consulted before it goes live.

(3) Human professionalism: you’re still responsible for the quality of your work, so you don’t get to blame the AI.

(4) Ethical and safe use: use AI where it actually improves things, and if you can’t say what it will do, evaluate it before you rely on it.

(5) Guarding privacy: before AI touches personal data, check that it’s legal and think about the impact on the people whose data it is.

(6) Data quality: know where the data behind a system came from, make sure it was collected legally and ethically, and keep a record.

Basically, it all comes down to Stanford's golden rule of AI: “Do AI to others as you would like others to do AI to you”.

Russ Altman also emphasised that AI will not replace you as long as you stay the author of your own thinking. The most critical skill right now is maintaining agency over your own intelligence. AI makes original thinking even more urgent than before.

And that brings us to the second note from Florence…

Note #2: AGI will never be a creative genius

Riccardo Di Molfetta of Prelude Labs (an applied research lab focused on understanding the nature of human creative genius, and building machines capable of expressing it) made a very compelling point. Creative genius is a hard limit for AI.

AI keeps getting better at problems where someone can check the answer, because scaling pulls it towards whatever the data agrees on.

Creative genius runs on a completely different axis. More data and more compute simply doesn’t work for creativity.

"Scaling trains on consensus across huge datasets, so it biases toward the conventional and converges fast on the optimal answer. Creativity lives in the tails of the distribution; the training objective pulls to the centre.”

The same logic applies to novel startups ideas, which, to me, sit at the intersection of creative genius and execution.

Note #3: You should be cheering for Translated9 in the Ocean Globe Race 2027

The most inspiring sailing story I’ve heard since watching Maiden (must watch! especially if you’re a woman in a male-dominated field!)

In 2023, Isabelle Andrieu and Marco Trombetti, together with their company Translated, entered the Ocean Globe Race (a fully crewed, retro-style round-the-world sailing race) with a boat called Translated 9 and the motto “We believe in humans”.

The race bans GPS, and 70% of his crew came from outside professional sailing. They won the first two legs.

During Leg 3, the hull cracked. Because they accepted outside assistance, they were disqualified from Leg 3, instantly destroying their chances of an overall race victory.

Unwilling to quit, the team spent weeks in the Falklands executing a massive repair.

Incredibly, Translated 9 fought her way straight back to the front of the pack. By early April, they were once again leading Leg 4 in the IRC rankings.

On Leg Four, the cracks opened again, so they diverted towards Portugal and repaired in Madeira. They still sailed into the finish line anyway and won the Spirit of OGR award.

Translated 9 is returning to take on the challenge once again in 2027.

In Florence, I fell in love with the story itself, as well as the resilience and warmth Mark and his wife bring to the sailing world!

You can follow Translated9 on Instagram here.

The chart is redrawn + simplified, based on the slide Riccardo Di Molfetta showed during his talk at SIAW26

I was convinced this August. Earth Cafe, a quite popular place in Msheireb, introduced a new cheesecake - EKHLAS, with dates and cardamom, meant to taste like a Qatari summer.

I have eaten this cheesecake like at least five times already, and I can confidently say that this is my official number one, aka THE BEST cheesecake in Qatar.

We spend most of summer indoors, but it's also date season. Every July, Souq Waqif runs a whole festival for local dates, and this year 125 farms brought their harvest. Dear Earth Cafe team, thank you for putting that into a cheesecake!

The plate looks deliberate. A small baked cylinder on a biscuit base, with thick date puree swirled on top, plus a date and a fleck of gold on the date paste. The base on its own is not too sweet. Add the date paste and the cardamom, and the whole thing tastes just perfect.

Verdict: 10/5 worth the calories!

Must visit!

EARTH Organic Coffee
📍 Google Maps

Greenland has jaw-dropping landscapes, glaciers and icebergs. What Greenland does not have is cheesecake. The only village I visited had around 400 people, and at that population size, nobody makes cheesecakes. At least, not for sale.

But I had a layover in Reykjavík on the way back and managed to squeeze in two of them. One went straight into the global ranking.

It was at Tides, on the ground floor of The Reykjavík EDITION. And it was my first Basque skyr cheesecake!

The skyr tradition in Iceland goes back over a thousand years, and I love that Tides leaned into it. Skyr is a cheese, and it carries flavour in a way cream cheese never quite does.

The texture was perfect. The flavour was perfect. It was properly cheesy and at the same time completely fresh, which is the combination I have been chasing since I started this ranking. Orange confit on top for a burst of citrus. Mango sorbet on the side, creamy enough to smooth it all back out.

Honestly, what a delight. Must visit. 5/5 worth the calories.

New #2 on the Global Cheesecake Ranking.

1. Ofício - Tasco Atípico, Lisbon 🇵🇹

2. Tides, Reykjavík 🇮🇸 (new)

3. Don Diablo, Medellín 🇨🇴

4. Qinwan Cafe, Doha 🇶🇦

5. Koneser Grill, Warsaw 🇵🇱

6. L’eto, Abu Dhabi 🇦🇪

7. IT, Jeddah 🇸🇦

8. The Kitchen, Tbilisi 🇬🇪

Ofício keeps the top spot, but the gap has never been thinner 🤏

PS Sailing in Greenland was amazing! My dear friend Filip is organising incredible expeditions.

Subscribe now

For years, the tooling conversation in VC was mostly about software shopping: Which CRM are you using? Who moved from Affinity to Attio? What are you using for portfolio KPI tracking?

But it’s changing now. If you spend time around VC operators, platform teams, or people close to the fund’s internal workflows, you can feel the shift already.

The more interesting question now is no longer what tools you use, but what you are building in-house. Early this year, my favourite Elena Verna wrote an article, “Why every exec should be vibecoding.” The VC crowd seems to have taken that advice very seriously!

What follows is a curated collection of the most recent case studies showing what some of the more forward-leaning VC firms are already building across sourcing, investment analysis, portfolio support, and beyond. If you want to understand where the operating edge in VC may be heading next, this is a good place to start.

Share

1. Finding deals

Ada Ventures’ Deck Genius

What: An AI-powered pitch deck review tool that gives founders fast, detailed feedback before they start pitching investors. It sits between founder support and sourcing, but it’s clearly a top-of-funnel tool: Ada describes it as a new touchpoint with founders before they formally seek funding.

What problem it solves: Most funds cannot give high-quality feedback to the thousands of decks they receive. Founders get little signal, and investors lose a chance to improve the quality of inbound deal flow. Ada’s answer was to turn that early screening and feedback layer into software. The earlier AdaGPT version was already being used by more than 200 founders per month, and Ada said one company that used it later received a term sheet. Three months after launch, Deck Genius had processed 1,091 decks in three weeks.

How: Michael Tefula rebuilt the system from scratch. Deck Genius runs 20 to 50 LLM calls in the background across three areas: narrative, design, and venture fundamentals. It delivers slide-level and holistic feedback in roughly 30 to 90 seconds.

🛠️ Tools used: Cursor, Claude, Codex, multi-step LLM workflows

Source: “Could a VC create an AI to tell founders what investors would really think of their pitch deck?”, Pathfounders; Michael Tefula’s LinkedIn post

Fika Ventures’ Job Post Intelligence Tool

What: A lightweight, self-hosted job-post intelligence tool that monitors companies’ career pages across multiple ATS platforms and sends a Slack alert the moment a new role goes live.

What problem it solves: Hiring is one of the clearest external signals of startup momentum, but it is difficult to track systematically. Job openings are fragmented across different ATS platforms, manual checks are tedious, and important changes are easy to miss. The tool turns scattered public hiring data into a live signal layer that helps investors monitor growth, hiring velocity, expansion into new functions, and competitive movement.

How: The system runs on a scheduled cron job, queries each company’s ATS endpoint, compares fresh job postings against a local SQLite database, and triggers a Slack webhook whenever it detects a new role. This allows the team to monitor hiring velocity across portfolio companies and other target companies without manually checking dozens of career pages.

🛠️ Tools used: Node.js 18+, SQLite, Slack, cron, public ATS APIs

The best part is that the tool is available for everyone to try and customise here.

Source: “We Built a Job Post Intelligence Tool for VC’s — and We’re Open Sourcing It”

2. Evaluating deals

Airtree’s research agent

What: AI agents that automate parts of the investment process, including company research, meeting preparation, deal analysis, and routine due diligence formatting.

What problem it solves: A large share of early-stage investment work is repetitive knowledge work: gathering information, following leads, synthesising findings, and turning all of that into an internal brief. Airtree’s goal is to eliminate hours of manual prep and speed up analysis, without replacing investor judgment.

How: Jackie Vullinghs describes Airtree’s company research workflow as agentic because it searches multiple data sources, decides which leads to follow, loops back when initial results are thin, and synthesises across sources. Airtree’s view is that most real workflows don’t need a complex swarm of agents. A single agent with a ReAct loop and well-chosen tools handles most real-world tasks. Three months in, one of their biggest lessons has been that context management matters more than model selection: their agents get meaningfully better when the team focuses on curating what goes into the context window rather than experimenting with different models. Their research agent now produces a company brief in about three minutes that used to take an analyst a few hours.

🛠️ Tools used: Claude, MCP-based tool connections, ReAct-style agent design

Source: “Building a System of Agents”, Making Connections by Jax

TheVentures’ Vicky

What: An internal AI investment analyst built by Korean early-stage VC TheVentures. Vicky produces structured company analysis and an investment recommendation designed to mirror how the firm’s own investors think.

What problem it solves: Early-stage investing has limited hard data, so much of the work relies on qualitative judgment, synthesis, and memo writing. TheVentures wanted to scale that work without linearly scaling headcount, while keeping the system close to their own decision-making patterns.

How: The firm started by studying how its investors actually make decisions, then translated those patterns into prompts and context engineering. The finished system is a multi-agent setup that uses different LLM providers for different tasks and connects RAG to the firm’s internal database and knowledge base. When a pitch deck, founder profile, one-pager, or meeting transcript enters the system, Vicky generates a structured company summary and a Yes/Maybe/No investment rating with written reasoning. After six months of use, TheVentures said Vicky’s recommendations aligned with human investors about 87.5% of the time. What used to take roughly a week to produce an investment memo now takes about one hour, and the overall response time went from four to six weeks down to one week. The firm also said Vicky surfaced teams that some investors had initially overlooked.

🛠️ Tools used: Multi-agent workflow, multiple LLM providers, RAG, internal dashboard integration

Source: “We let an AI help us decide which startups to invest in for 6 months — here’s what happened”, KRDeals by TheVentures

3. Portfolio intelligence

The post-investment phase presents a different set of challenges. For funds managing large portfolios, aggregating data, staying on top of company news, and keeping institutional knowledge accessible are ongoing burdens.

Point Nine Capital’s Knowledge Hub

What: A homemade version of Glean that allows the firm to ask natural language questions like “How is Company X doing?” and get answers drawing from the firm’s entire institutional memory.

What problem it solves: Institutional knowledge at a VC fund is scattered across email, Slack, meeting notes, CRM entries, and shared drives. Finding relevant context about a portfolio company means digging through multiple systems. The Knowledge Hub centralises it all into a single queryable layer.

How: Over 13 days in January 2026, Managing Partner Christoph Janz vibe-coded the system without writing a single line of code. All 43,800 lines of Python were written by either Replit’s agents or Claude Code. Data from Gmail, Google Drive, Slack, Zendesk, Attio, and Granola is processed into a vector database (Qdrant) with semantic search and connected to Claude via MCP servers. The team can query it through Claude Desktop, Claude.ai in the browser, or a Slack bot. In a follow-up post, Janz explained that he later simplified the architecture by connecting data sources directly to Claude without the vector database, and found that the simpler version delivered most of the value for a fraction of the maintenance.

🛠️ Tools used: Replit agents, Claude Code, Qdrant, PostgreSQL, OpenAI Embeddings, Anthropic Claude, Cohere Reranking, MCP servers

Source: “Some Learnings from Vibe Coding a Knowledge Hub in 13 Days”, Point Nine Land, Medium

AppWorks’ social media tracker

What: An automated social media tracker for 600 portfolio teams, plus a semi-automated X/Twitter engagement system.

What problem it solves: Keeping up with hundreds of portfolio teams manually is not realistic. Fundraising announcements, product launches, and partnership signals get missed. The tracker turns a daily firehose of social posts into a structured feed of what actually matters.

How: Hsu started with an open-source social media tracking system and customised it. The account list lives in Google Sheets. Posts are scraped across platforms, scored and summarised by AI (with fundraising, product launches, and partnerships weighted higher), and delivered as a daily Telegram summary. The system can also draft short repost-ready messages for the team’s official account.

🛠️ Tools used: Open-source social media tracker (customised), Google Sheets, Telegram

Source: Bill Hsu at AppWorks has been documenting the whole Vibe VC experiment publicly Vibe VC #2: Tracking 600 teams

Alpaca VC’s “Gordon”

What: A proprietary AI system that generates highly specific, actionable prospect lists for portfolio companies.

What problem it solves: Portfolio support often means helping startups find the right customers, partners, or hires. Gordon automates the research and mapping that a human team would spend days doing manually.

How: In one instance, Gordon produced a list of 50 high-value prospects (academics, pharma execs, former FDA leaders) with exact connection routes for a startup called Autopoiesis Sciences, helping Alpaca secure a $1M allocation in a competitive round. At the same time, this is a portfolio support tool: it helps existing portfolio companies grow, not the fund find new deals.

🛠️ Tools used: Proprietary system (specific stack not publicly disclosed)

Source: “Deep Dive: As Smaller VC Firms Build AI Tools To Compete”, Upstarts Media, December 2025

4. Fund infrastructure

Beyond the investment workflow itself, VCs are automating the “firm building” layer: LP reporting, internal finance, CRM, and team coordination. This is the plumbing of a fund, and it has historically consumed a disproportionate amount of time relative to its strategic value.

Union Square Ventures’ agents

What: A custom internal web application and database powered by background agents, each with a name and a job: Sally (meeting transcription), Ellie (email monitoring), Felix (finance data), Arthur (deal analysis), Connor (calendar monitoring). The system was built to make USV’s internal context structured, retrievable, and continuously updated.

What problem it solves: At a firm like USV, information about companies, people, and themes is constantly generated across meetings, email threads, and calendars. The problem was that this context was scattered, manually maintained, and often outdated when the team needed it. The agents solve that by automatically capturing and structuring mentions across the firm’s workflows, creating a live internal memory layer for portfolio and pipeline discussions

How: USV first built a recap workflow for team meetings, then expanded it into its own internal database and web app. Background agents access Granola meeting transcripts, internal group email threads, and team calendars, then convert unstructured activity into structured “mentions” attached to companies and people. Those mentions feed the internal app, where companies automatically appear on the deal log with related decks, memos, and other internal context. Arthur also monitors the pipeline, maintains living deal memos, and supports investment discussions.

🛠️ Tools used: Claude Code, Tasklet, Granola, Notion, Attio, and the internal USV API. Arthur also uses Harmonic for research support.

Source: “Meet the Agents at USV: Arthur, Ellie, Sally, and Friends”, USV Blog, March 2026

HP Tech Ventures’ CVC agents

What: A team of specialised AI agents running on top of a structured internal knowledge layer, including agents for startup profiling, VC investment tracking, executive briefing synthesis, company evaluation, meeting briefing preparation, and a “Chief of Staff” orchestration agent.

What problem it solves: Corporate Venture Capital faces a unique challenge: proving strategic value to the parent company. The agents automate the cross-referencing and synthesis that connects deal pipeline activity to strategic priorities across HP’s business units.

How: HP built a team of purpose-built agents that share context but each own a specific workflow. In the past, the team had been tracking edge inference trends across articles, podcasts, and analyst reports. The Intel Digest agent picked up those signals, scored them against HP’s strategic priorities, clustered them with related signals already in the system, connected multiple startups in the pipeline to the same emerging theme, generated a themed briefing, created a standalone Insight note for specific HP business units, and produced follow-up actions.

🛠️ Tools used: Claude Code, Obsidian

Source: “The CVC Problem Nobody Talks About — and How AI Agents Solve It”, Andrew Bolwell, March 2026

5. Exiting

This is the white space.

Across every case study I came across, not a single vibe-coded tool was built for the exit process: secondary sales timing, M&A preparation, IPO readiness workflows, or portfolio exit modelling.

There are a few possible explanations. Exit processes tend to be highly bespoke, legally complex, and involve sensitive information that firms are reluctant to run through AI systems. The data required (buyer sentiment, secondary market dynamics, board-level strategic discussions) is harder to systematise than scraping founder LinkedIn profiles. And the stakes of getting it wrong are higher.

Reality check

The case studies above make for exciting reading, but the honest version of this story includes the cautionary tales.

The maintenance trap. Michael Bloch, a partner at Quiet Capital, spent around 50 hours building a command centre with Claude Code covering email, calendar, meeting notes, and CRM. It worked. The maintenance cost kept compounding while the usefulness never quite caught up. “I built something” Bloch wrote. “But I didn’t build a product. I built a prototype with no one maintaining it but me and a chatbot.”

Vibe coding makes building fast, but it doesn’t make maintaining easy (yet!)

The “building fast in the wrong direction” problem. USV’s Spencer Yen was candid about the risks: “The double-edged sword of AI coding agents is that you can build really fast in the wrong direction. When building internal tools or agents, the act of building can feel so engaging and productive that you lose sight of actually solving any real problems.”

The information edge is temporary. An associate at Vertex Ventures, Isaac Kwa, built an AI deal-sourcing tool and then wrote one of the most clear-eyed assessments of its limitations: “The best deals in VC do not surface through data”. If your AI can see the deal, so can everyone else’s AI. The tools being built are powerful, but they optimise the parts of VC that were never the sole source of alpha. Networks, judgment, and founder trust remain stubbornly human.

Closing note

The VC tech stack is being rebuilt in real time, one weekend project at a time.

It’s hard to say how much of this will stick in the long term. But for now, I see a lot of excitement and VC professionals having fun.

For inspiration on off-the-shelf AI tooling in VC, I highly recommend Cory Bolotsky’s newly released market map of AI VC tools.

I’ve been working with early-stage founders for nearly a decade, both on the investment and portfolio sides of Venture Capital. I invested in and/or worked with nearly 200 founders from about 50 countries who built startups serving customers worldwide. And what I saw recently blew my mind.

My job is to make sure that we are the favourite investor on the cap table of every founder we back. So obviously, negotiating software and services discounts for our portfolio companies is a part of it.

Over the past year, something changed.

As AI tools accelerated, the requests from portfolio companies changed. Founders weren’t just passively browsing what we had available. They were actively asking us to source specific tools, negotiate discounts with AI providers, and add new partners. The demand for anything that reduces building costs, whether cloud credits, AI tools, or dev platforms, went through the roof.

I’ve seen how founders react to every major perk we’ve ever offered, including OpenAI credits. I know what “strong interest” looks like.

When we onboarded Lovable to our perks platform, the redemption interest was unlike anything I’d seen before.

Here’s the actual screenshot of my inbox 👇

When founders in São Paulo, Lagos, Nairobi, and Jakarta all reach for the same tool, that tells you something. And for me, the best signals are the ones that come from my portfolio. So I started digging. Why Lovable? Why is the interest so strong?

The gap

Here’s what most people in developed markets don’t realise about building software in emerging economies: the developer supply simply isn’t there.

The US has roughly 12.9 software engineers per 1,000 people. Western Europe averages a similar range: the UK sits at 13.2, Germany at 10.8. Now compare that to the fastest-growing emerging markets. Indonesia has 0.71. Nigeria has 0.48. Brazil, the largest economy in Latin America, has 2.3. The talent pool in these markets is a fraction of what founders in San Francisco, London, or Berlin take for granted.

And the SaaS landscape mirrors the same gap. The US has about 80 SaaS companies per million people. Brazil has 2.4. Indonesia has 0.4. Nigeria has 0.4. That means there are entire categories of business problems in these markets for which no software solution exists, in any language or at any price.

Only 8% of global private capital is deployed outside the Big Six economies (the US, China, India, Germany, the UK, and Israel), despite these markets representing 38% of global GDP. The capital mismatch is well documented. But the tooling mismatch gets far less attention. In developed markets, no-code saves you time and money. In emerging markets, it may determine whether something gets built at all.

Why now, and why here

Four things are converging, making this moment different.

These are the youngest societies on earth. The median age in Nigeria is 18. In Kenya, it’s 20. In Indonesia, 31. In Brazil, 35. These populations grew up with smartphones in their hands. They are digitally native in ways older demographics in developed markets often aren’t. When you combine that digital fluency with newly accessible building tools, you get a generation that’s ready to build now.

The tools got good enough. Lovable lets you describe a product in plain language and get a working, full-stack application. According to Lovable, 67% of its users have little to no coding experience. This matters because the AI-assisted building threshold has crossed a line into usable output. Some of our portfolio companies are already using Lovable to prototype products before committing to a full engineering build, a smart way to validate ideas without burning through months of runway.

The people closest to the problems can finally solve them. This is the part that excites me most. Emerging markets are full of people who have understood local gaps for years but never had the technical means to address them. Now they can. And they bring something that no Silicon Valley SaaS company will ever replicate: deep local context. They know the workflows, languages, payment habits, and cultural nuances that shape how business actually runs on the ground. 76% of consumers globally prefer to buy in their native language.

Linda Rottenberg, Endeavor’s CEO, made this point powerfully in her 2025 Gala speech: the companies building foundational AI models are based in Silicon Valley and China, but the application layer, where AI meets lived experience, is being built elsewhere. The founders she highlighted didn’t set out to build AI. They set out to solve problems that matter. Tools like Lovable accelerate exactly this pattern.

The cost math finally works. $25/month puts serious building capability within reach of entrepreneurs across markets where custom software projects usually cost tens of thousands of dollars, and often much more. This price point unlocks a massive population of builders who were previously priced out entirely.

What’s still in the way

The opportunity is real, but there are bottlenecks.

The biggest one is payments. Credit card penetration remains very low in many emerging markets (for example, in sub-Saharan Africa, an estimated 3-5% of people use credit cards). You can build the most accessible development platform in the world, but if people can’t pay for it, it doesn’t matter. The mobile money infrastructure already exists in many of these markets, and no-code platforms that integrate with local payment systems will unlock these markets.

Language is the other bottleneck. Most no-code platforms are English-first, but English proficiency varies widely across emerging markets. As AI-powered interfaces get better at accepting prompts in Arabic, Portuguese, Hindi, and other local languages, the addressable market will expand significantly.

The future is bright

The cost of building software just dropped by an order of magnitude, and the people who benefit most are the ones who had the least access to begin with. The no-code AI market is projected to reach $37-44B by 2033. But the more interesting thesis is what gets built on top of these platforms in underserved markets. A flagship example is a Brazilian EdTech company, Q Group, which generated $3M in revenue within 48 hours of launching a premium product for its existing user base, built on Lovable.

Endeavor’s data shows there are now over 1,400 unicorns globally, half outside the US. Their question resonates: if founders from overlooked markets have already built this much with limited tools, what happens when they get everything they need?

I think we’re about to find out. And I think no-code platforms will make a massive contribution to the development of emerging market economies.

Go explore it, find a spot near you, or in a place you’re travelling to next and go get yourself a slice. You’ll thank me later 😇

Explore the guide

This whole website was built in one evening on Lovable, and I had so much fun playing with it!

Bon Appetit,
Mal

As Qatar celebrates National Day and 2025 comes to a close, it feels like a natural moment to take stock of how the country’s venture capital and startup ecosystem has evolved. Having lived in Doha for the past three years, I have noticed the change not in a single dramatic headline, but in the accumulation of smaller, structural shifts. Capital is being deployed with clarity, institutions are better coordinated, and Qatar’s role in the global startup and VC landscape is becoming more defined.

The $1 Billion Deployment: QIA and Global Funds

Venture capital activity in Qatar continues to be closely linked to the Qatar Investment Authority, which remains the central force shaping the market. There is a strong emphasis on partnering with experienced fund managers and building long-term institutional capabilities.

By February 2025, QIA had committed nearly $500 million across the first six managers selected under its $1 billion Fund of Funds programme: Rasmal Ventures, B Capital, Builders VC, Deerfield, Utopia Capital Management (A-Typical), and Human Capital. Later in the year, QIA expanded the programme further by adding Founders Circle Capital, strengthening its exposure to global growth-stage expertise.

Despite this momentum, the venture capital programme still represents less than 0.2% of QIA’s total assets, estimated at $526 billion, underscoring both the strategy's early-stage nature and its potential for expansion.

Alongside QIA-backed initiatives, 2025 also saw increased activity from independent international venture capital firms choosing Qatar as a strategic base. Most notably, Golden Gate Ventures strengthened its presence in Doha as part of its global platform, actively building a bridge between Southeast Asia and MENA. The firm made a couple of investments and used Qatar as a hub to support early-stage investments, help founders expand across regions, and connect two fast-growing emerging markets.

Launch of QVCA

To unify these new arrivals with local players, the Qatar Venture Capital Association (QVCA) was launched in May 2025 at the Qatar Economic Forum.

Designed as the “one voice” for the investment community, QVCA is led by founding members including A-typical Ventures, Golden Gate Ventures, and Rasmal Ventures. Its primary mission is to coordinate policy advocacy and provide a structured framework for the influx of capital and talent entering Qatar.

The National Bet on AI

Qatar has made AI a strategic priority, anchoring its ambitions in a clear advantage: abundant, low-cost energy to power large-scale computation and next-generation AI infrastructure.

In December 2025, QIA launched QAI - “a national company specialising in artificial intelligence (AI), aimed at developing advanced digital ecosystems to support innovation and contribute to sustainable development”. Shortly after, Qai announced a $20 billion joint venture with Brookfield Asset Management to develop high-performance computing centres and AI infrastructure in Qatar and internationally: one of the largest AI-focused infrastructure commitments globally.

On the venture-creation front, A-typical Ventures, a new venture studio backed by QIA and QDB and managed by Utopia Capital Management, debuted at Web Summit 2025. “The Studio” is actively recruiting entrepreneurs to build companies from the ground up, with a strong focus on AI.

Accelerators and Support Systems

Accelerator activity in Qatar continued to mature in 2025, evolving from a broad set of founder programs into a more specialised support stack that links local innovation with global expertise. Startup Qatar, led by QDB, remains the primary entry point for early-stage founders, while sector depth is increasingly shaped by QDB’s FinTech Hub and Scale7, which focuses on creative and fashion-tech startups with regional scaling ambitions. The TASMU Program continues to anchor venture development around national digital priorities, particularly in logistics, mobility, and smart city infrastructure. Alchemist Doha solidified its role as a premier B2B and enterprise hub, serving as the bridge between Doha and San Francisco for B2B companies. Additionally, the Cure by Deerfield Middle East Health Accelerator launched its inaugural 12-week hybrid program in late 2025, offering mentorship and connectivity between NYC and Doha for 15 selected healthtech startups. Startup Grind Doha continued to play an essential role as a neutral platform for open, candid discussions, bringing founders, operators, and investors together.

Major International Events: Web Summit and MWC

Doha’s role as a regional tech hub was reinforced by its hosting of Web Summit Qatar 2025, which provided the stage for several of the year’s most significant ecosystem announcements and meaningful investor–founder engagement. This international momentum was complemented by strong local platforms, including ROWAD by Qatar Development Bank, which continued to anchor founder development, and the MENA Insurtech Summit & FinTech, led by Qatar Insurance Company (QIC), which strengthened ties between startups and regulated incumbents. Later in the year, MWC Doha hosted its inaugural edition, further validating Qatar’s ambition to become a recurring destination for global technology and innovation events.

A Hotter Angel Scene

Qatar’s angel ecosystem also picked up real momentum in 2025. Doha Tech Angels (DTA) closed three new investments, signalling an active local angel base. At the same time, the market saw the arrival of new angel investment clubs, including Finjan VC, adding fresh capital, structure, and deal-sharing dynamics to the ecosystem.

The Exit: Snoonu’s QAR 1 Billion Milestone

The ecosystem’s most significant validation came in July 2025 with the Snoonu-Jahez deal. Saudi-based Jahez Group agreed to acquire a 76.5% stake in the Qatari delivery platform for $245 million. This deal valued Snoonu at approximately QAR 1.165 billion (~$320 million), making it the first Qatari tech startup to surpass the billion-riyal valuation mark. This “soonicorn” (or snoonicorn 🙈) exit provides a much-needed success story for local founders and proves that Qatar-born startups can achieve regional scale.

2025 was a year of progress

Overall, the momentum going into the end of 2025 is hard to ignore. A lot of this progress is the result of sustained, often unglamorous work by founders, investors, ecosystem builders, and public institutions, and many friends and peers deserve real credit for how far things have moved in a relatively short time. From Seedstars International Ventures’ global portfolio perspective, it has also been encouraging to see two of our companies building meaningful collaborations and products with Qatari corporates. If I had one wish for 2026, it would be to see even deeper engagement from prominent national champions: QNB, Qatar Energy and Qatar Airways, in particular, playing a more systematic role as customers, partners, and early adopters of local and regional innovation.

2026 already looks exciting!

Looking ahead, there are good reasons to believe that 2026 can be even stronger, judging by who showed up in Doha over the past months 🤫. For those who remember how quiet and fragmented the ecosystem felt just three years ago, the contrast is striking.

On a lighter note, the calendar also brings things to look forward to beyond venture. Art Basel is coming to Qatar, which I’m genuinely excited about, and it feels like another signal of how the country is broadening its global cultural footprint.

And finally, for anyone still debating it: Qinwan cheesecake remains the best in Doha, and I’m yet to be convinced otherwise.

Happy holidays,
Mal

La Maritxu's Basque cheesecake has lived on my Google Maps list for over two years, propped up by endless recommendations and one headline that kept popping up: "I tried London's viral Basque cheesecake and it's the best I've ever had." I went there last week wanting to agree.

The set-up is perfect: Soho, that burnt top catching the light, a slice that looks like it knows exactly what it's doing. First bite delivers the right cues: warm custardy centre, a clean bake. Then it goes flat. The flavour is safe and creamy, too much Philadelphia cheese, with a sweetness that starts to crowd out the subtle bitterness you want from a great Basque. I kept waiting for the depth to arrive, the caramelised edge to push, a little salt to lift, but the slice stayed boringly polite.

Is it good? Somehow. It's well-executed and easy to like. Is it "best I've ever had"? Not even close! It's the kind of cheesecake that wins on Instagram and by consensus.

No change to the Global Cheesecake Ranking. London still owes us a Basque with a personality!

Verdict: 2/5 worth the calories.

But as a Venture Capitalist, I couldn't stop thinking: do top VCs follow similar paths? To find out, I analysed the backgrounds of 120 investors from the 2024 and 2025 Forbes Midas Lists. Only 20 new names appeared in 2025, so I merged the two years into one dataset.

I wanted to know what the patterns are in their career paths. What can we learn from the life and career choices of people who consistently back billion-dollar companies?

VC Pathways Chart

Subscribe now

It all starts with an international background and an elite university

Just like unicorn founders, many top VCs have global roots. Nearly half either studied abroad, worked in a different country, or migrated to a major startup hub. It's hard to measure exactly what impact this had, but it likely gave them a wider lens on the world and helped them build diverse, global networks early in their careers.

Speaking of network, the best of them are being built at the top global schools: 79% of Midas List VC investors attended elite universities. It doesn't come as a surprise. As Professor Ilya Strebulaev published recently, three out of every five senior VC investors got educated in a top US school and almost half studied at an Ivy or Ivy+

Across the board, elite universities emerge as the strongest early-career lever by providing access to networks that become a deal flow and co-investor relationships for decades.

54% of successful VCs have science or engineering backgrounds, compared to just 38% with business majors. This technical skillset becomes even more pronounced when looking at early career paths: 36% of Midas VC investors started in product or engineering roles.

It appears that VCs who can evaluate technical feasibility, understand product roadmaps, and speak the language of engineering teams have a significant advantage.

Best VC investors founded “SOMETHING”

Perhaps the most telling statistic in the entire dataset: 42% of Midas List VCs founded their own startup(s) before moving into investing. And it does make sense: founders-turned-investors bring a unique perspective. They've been in the trenches, they understand the emotional rollercoaster, the operational challenges, and the nuances of building something from scratch. This experience allows them to empathise deeply with founders and offer practical, often battle-tested advice. VCs of that profile might also have a higher likelihood of access to great deals, and founders might find them incredibly valuable for opening doors, making introductions, and helping startups gain traction.

54% of top VCs founded their own venture capital funds rather than climbing the ladder at established firms. The traditional model of spending 15 years working one's way up from analyst to partner is not very common among top performers.

Best VCs live and breathe their work

90% of the world's best VC investors invest their capital as angel investors, and 94% actively advise companies. This level of engagement extends far beyond traditional investing, suggesting that the most successful VCs view venture capital as a lifestyle rather than just a job.

Jack Altman once noted that being in the right networks and seeing the best deals is more critical than being an exceptional picker. By immersing themselves in the ecosystem, through angel investing and advising, VCs increase their surface area for opportunities and build trust with founders.

Surprise!

The best VCs aren't necessarily building big personal media brands. Very few run podcasts or focus on constant self-promotion, contrary to the image often portrayed online.

Another unexpected finding was that none of these top investors were college dropouts, a path sometimes glorified in Silicon Valley. Instead, most followed more traditional educational routes before carving out their own unique paths in the venture world.

Only 45% have MBAs, suggesting advanced business education is just as good as operational experience.

Take it with a pinch of salt

The Forbes Midas List, widely seen as the definitive ranking of top venture capitalists, deserves a more critical look. Its ranking method focuses on big exits and high valuations within a five-year window. This naturally favours late-stage investors and short-term wins over early-stage VCs who often take bigger risks and earn the highest returns. The methodology struggles to separate individual versus firm credit and doesn't fully capture geographic diversity beyond Silicon Valley.

In short, while the patterns are interesting, they don't tell the whole story, especially when it comes to early-stage investors, diverse managers, or exceptional investors outside of the leading VC hubs.

"The future is built elsewhere"

The patterns revealed in this analysis may represent the last generation of a distinctly American venture capital archetype. As venture capital continues its rapid globalisation, with US investments dropping from 95% of global VC twenty years ago to just 40% today, the elite university networks and Silicon Valley operational experience that define today's Midas List may become less relevant predictors of success.

"In 2013, Aileen Lee coined the term "unicorn" to describe the rare breed of private billion-dollar startups. At the time, there were 39 of them, all US-based. Fast forward to today, and there are over 1,400 unicorns globally. Half of them are outside the US. If this follows a similar path as capital deployment did, likely, we're only a year or two away from having a majority of non-US unicorns around the world."

Endeavor monthly roundup, July 2025

The next generation of top VCs will likely emerge from different educational systems and build companies in markets such as MENA, CEE, LatAm or SEA. As unicorns increasingly originate from economies beyond the traditional Big Six (the US, China, India, Germany, the UK, and Israel), the venture capitalists backing them will need different skill sets, networks, and cultural fluency than today's Midas List winners.

The credentialed operator-founder archetype documented here may soon give way to a more globally diverse set of paths to venture capital excellence: one that reflects the reality that the future of this industry is increasingly built outside of the major hubs.

Share

DATA EXPLAINER

Migrated to a Unicorn Country: The investor—or their parents—moved to the US, India, or China at some point. These are the countries that have produced the most unicorns globally.

Studied or Worked Abroad: The investor completed a university degree or held a full-time job in a different country from where they grew up.

Elite University: The investor earned a bachelor's degree from a university ranked in the top 100 of the 2025 QS World University Rankings.

Other University: The investor earned a bachelor's degree from a university outside the top 100 of the 2025 QS World University Rankings.

Science Major: The investor pursued a university degree in a scientific or technical field (e.g. engineering, physics, computer science).

Business Major: The investor studied business, economics, or a related field at university.

MBA: The investor completed a Master of Business Administration degree.

Early Career in Finance: The investor started their career in investment banking, private equity, hedge funds, or a similar finance-related field.

Early Career in Product/Engineering: The investor began their career in a technical or product-related role at a startup or tech company.

Founded a Startup: The investor previously started their own company, regardless of whether it was successful or not.

Exit Event Exposure: The investor either:

– founded a company that was acquired or IPO’d,

– worked at a company that went through a major exit,

Invests as an Angel: The investor makes personal investments in startups, outside of their institutional role.

Founded a VC Fund: The investor is a founding partner or co-founder of a venture capital fund.

Advises Companies: The investor actively advises startups (formally or informally), often taking advisory roles.

Teaches at a University: The investor holds or has held a teaching or guest lecturer position at a university.

Over the past two and a half years, I've spoken with more than 300 potential advisors for my portfolio companies, made over 100 introductions, and ultimately hired 40 advisors to support the growth initiatives of the companies we've invested in.

The results have been very different. Some advisors joined formal advisory boards, others became fractional team members, and in one remarkable case, an advisor launched a new business that became a customer of the startup they were advising.

But not every match was successful. Some advisors vanished after initial meetings, while in other cases, startups became discouraged after a few unproductive sessions. After seeing so many interactions, I've learned a lot about what makes an excellent advisor—and how to find them.

Note: My insights below relate to finding go-to-market, growth, marketing, or sales advisors at the pre-seed and seed stages.

Why consider hiring an advisor

We often hear, "There are so many playbooks out there; why would an early-stage founder hire an advisor? It's a waste of time and money, and founders already have a lot on their plate."

Well, that's because most startup advice is terribly wrong if applied in the wrong context. Every company is unique, and no universal growth playbook works for everyone. My favourite example is Sam Altman, who spent years telling YC founders to "launch fast, get feedback, and avoid stealth mode"—yet with OpenAI, he did precisely the opposite, keeping it secret for years, focusing on research, and only launching when they were far ahead of competitors.

The right growth advisor, however, can be transformative. Luc Levesque, Shopify's Chief Growth Officer, has advised major companies like Canva and Twitter. He shared an inspiring story in one of Lenny’s Podcast episodes - on his first day consulting for a company (now publicly traded), he quickly identified a critical flaw in their strategy. His simple adjustment led to significantly improved growth metrics in just three weeks.

This is why good advisors matter—they distil years of experience, help apply the right playbook to the right situation, speed up decision-making, expand networks, and ideally help founders avoid common (but painful) mistakes.

Timing matters

However, hiring an advisor isn't always the right move. It's usually better to build momentum internally before bringing in an advisor.

A good rule of thumb is to seek external support when it becomes critical to reaching your next milestone. Advisors are usually helpful before major events like raising funds, launching products, shifting your GTM strategy, or expanding into new markets. They can help refine the pitch, improve sales materials, and sharpen your overall strategy and execution plan.

Another key moment is when your company faces unfamiliar challenges. Suppose you're tackling something for the first time. In that case, whether it's scaling growth, navigating enterprise sales, improving activation rates, or launching a referral program—an advisor can bridge that knowledge gap and help you avoid costly or time-consuming mistakes.

Most importantly, only hire an advisor when you clearly define their role. If you're unsure what you need, you probably don't need an advisor (yet).

Must-haves of Solid Advisors

Relevant experience is non-negotiable. Early-stage startups face countless problems, and the fastest solution comes from someone who has repeatedly solved similar challenges.

But experience alone isn't enough. The best growth advisors have performed various experiments and learned a lot while running them. A proven track record in growth means that the advisor has driven measurable results, whether scaling from zero to millions in revenue, building repeatable growth engines, or mastering specific channels.

Strong communication skills are essential, too. Great advisors break down complex concepts into simple, digestible advice. This clarity demonstrates deep understanding.

Ideally, an advisor should have a relevant network and be able to open doors to investors, customers, and talent. However, introductions are not everything. The real value lies in guiding you through challenges after those doors open.

The Non-Obvious Qualities of Great Advisors

Ability to be tactical. Great advisors provide actionable insights. The best can distil years of experience into a sentence. They've seen enough experiments to know what works and what doesn't.

Willingness to challenge you. Valuable advisors aren't afraid of difficult conversations. They'll identify blind spots, question assumptions, and push you to think differently. If you struggle with being challenged by smart people you hire, that's a different problem 🙊.

Adaptability and curiosity. Growth constantly evolves, and the best advisors stay on top of new trends, tools, and tactics.

The best growth advisors don't try to solve every problem and know when to say no. They recognise their strengths and focus where they can make the most significant impact. If something falls outside their expertise, they'll admit it and direct you to someone who can help.

Maximising Advisory Relationships

Finding the right advisor is only half the battle. Many promising advisory arrangements don't work because founders skip essential groundwork. Here are a few things to consider that, in my experience, make all the difference.

1. Start Small: Run a small project or workshop with the advisor before committing. This helps you test chemistry and see the actual value of an advisor. Ask about past projects to understand their adaptability and insight.

2. Align Expectations: Clearly define what you expect. Agree upfront on specific challenges they'll address, meeting frequency, deliverables, and success metrics. A simple one-page "advisor agreement" can clarify expectations and prevent misunderstandings.

3. Structure incentives for a long-term partnership: You’re running a marathon, not a sprint, and your advisor arrangements should reflect this reality. Consider implementing vesting schedules for equity compensation that align the advisor's incentives with your company's growth and fundraising journey.

If you're considering giving up the equity to your advisor, Carta provides fantastic benchmarks and playbooks.

Red Flags 🚩

Oh, I have a lot to share here 🥲

Some advisors can do more harm than good, and I experienced it firsthand. The wrong advisor can waste time, give misleading guidance, or be more focused on building their own personal brand than actually helping startups. Here are some warning signs to watch out for:

1. Lots of consulting gigs, no real operator experience – Some advisors hop from one consulting role to another without ever implementing their own advice. If they can't share concrete examples of applying their insights in real situations, or the results of experiments they did - that's a red flag 🚩

2. No network in your space – Advisors should bring both knowledge and connections. Without industry-specific contacts, their impact will be limited.

3. Generalists – Avoid those who claim expertise in everything (product, marketing, sales, fundraising) and promote one-size-fits-all playbooks. True experts have a clear focus.

4. Excessive LinkedIn/X activity without substance – Advisors who flood social media with memes and generic startup advice are often more focused on personal brand-building than actual impact. They do it usually to get lots of consulting gigs - see #1.

5. Vague case studies or name-dropping – If an advisor references impressive companies but can't explain their specific contributions, their role was likely minimal.

6. (Controversial one) Charging only a fee/hourly rate – I get it, equity doesn't pay the bills. However, advisors who insist on cash-only compensation often operate more like full-time consultants or fractional leads. There's nothing wrong with that—just make sure it aligns with what you need.

Final thoughts

Startup advice is everywhere, but most of it is either too generic, outdated, or misapplied. The right set of advisors can make all the difference. The most valuable advisor-founder relationships are built on mutual respect, shared goals, and genuine commitment to your mission. These rare individuals are worth more than the equity you'll offer them.

For most of 2024, the Global Cheesecake Ranking stayed as steady as an overbaked New York cheesecake. But then December arrived, and with it, a game-changer that shook things up.

I was genuinely disappointed after trying dozens of cheesecakes in my second home, Warsaw. Polish cheesecakes were just very boring, too creamy, not cheesy enough or with raisins (who does that?) 😵. Worst of all, some weren’t even real cheesecakes but the dreaded no-bake, frozen impostors 🥶. Let’s be clear: those aren’t cheesecakes; they’re just regular desserts.

And there it comes, the hero of Warsaw… 🥁🥁🥁 Basque cheesecake with honey and truffles at Koneser Grill. Its texture is pure perfection, and the flavour is a harmonious blend of sweet and salty, with honey adding a mellow richness and truffle, bringing an unexpected yet exquisite depth.

🎉 It’s a new #4 place.

Happy 2025!

And, with that, 2024 comes to an end. Wishing you all a Happy New Year filled with fantastic investments, incredible success for your portfolio companies, and partnerships that make magic happen (if you’re a startup founder). And, of course, exceptional cheesecake. 🥂🎉

Special thanks to Oksana Vodonos for trying this fantastic cheesecake with me in Warsaw in December (she liked the other one with raisins more, though 🙊)

Across the globe, most VC funds share a common goal: helping their portfolio companies reach their full potential. The range of initiatives funds implement to drive portfolio success—and ultimately enhance their own performance—falls under what’s known as the "VC platform." In the last twenty years, Platform roles in VC have grown significantly faster than the industry itself.

VC Platforms now cover a wide range of roles focused on delivering strategic value both pre- and post-investment.1 In this article, I'll dive into the world of post-investment platforms at the early stage.

I see the post-investment platform as a portfolio success engine. For VCs, it’s a way to stand out in competitive deals by offering startups more than capital and to differentiate the fund when pitching to LPs.

Talent, Business Development, and Community/Network are the most popular ways VCs engage with portfolio companies after the investment (according to a study of 850 VC firms). Other fairly popular post-investment platform strategies are listed below.

While all these initiatives aim to help portfolio companies scale, only a few VCs take a step back to focus on growth itself, especially with a structured, framework-driven approach.

Startup = Growth

Growth is a critical factor that can make or break a startup. It validates the scalability of the business model, attracts investors, and often leads to long-term success.

Startups are designed to grow quickly. Their success depends on capturing market share, outpacing competitors, and achieving scale before resources run out. Unlike traditional businesses, which can grow steadily over time, startups often operate in fast-moving, high-risk environments where rapid growth is critical to survival. Citing the timeless Paul Graham's post from 2012, Startup = growth: "The only essential thing is growth. Everything else we associate with startups follows from growth."

Focusing on the right goals at the right time

The common belief in the startup ecosystem is that founders should follow a structured path through each funding stage, with specific goals at each step. At the pre-seed stage, the priority is to validate the problem and solution and test the MVP with early users to confirm demand. At the seed stage, the focus shifts to achieving product-market fit. Here, founders refine their product based on user feedback, engage a core group of customers, and test growth channels. By Series A, the focus is on scaling.

Growth is a process

But, ironically, growth isn't always about growing. Adopting the growth mindset very early can be a crucial part of the journey to achieving product-market fit. Developing a growth hypothesis and testing it early on helps founders identify the right channels and strategies that align with their product’s value. For example, if targeting product-led growth, the product should be designed to drive acquisition and retention from the start.

Early growth efforts can help to establish key growth engines. For instance, Duolingo's initial growth was significantly driven by word of mouth, which accounted for about 90% of its DAU growth. By focusing on growth from the start, Duolingo created a self-sustaining loop where user acquisition feeds into product improvement, leading to more users and so on. Another great example is Airbnb: from the beginning, the team worked hard to enhance the experience for hosts and guests. They knew that building trust was essential, so they made key decisions to support that—like investing in professional photography for listings, which helped boost both trust and the number of bookings. During the early days, Airbnb also launched a host referral program, turning word-of-mouth into a powerful growth engine. Prioritising growth from day one enabled Duolingo and Airbnb to lay a strong foundation for long-term success, allowing founders to quickly grasp market dynamics, customer needs, and product effectiveness—ultimately accelerating their ability to iterate and improve.

Duolingo’s and Airbnb's stories prove that growth needs a solid foundation; skipping this foundation phase can lead to failure. For instance, Clubhouse, founded in early 2020, saw explosive 10x growth during the pandemic in late 2020/21, but the hype faded quickly. Even CEO Paul Davison acknowledged, "Extreme hypergrowth is not good for a company. The ideal is to grow at a steady pace."

Could Clubhouse's investors have prevented that? Maybe. Some VCs build teams to ensure sustainable growth, aiming to avoid clubhouse-like stories.

Leading examples of growth-centric platforms

Harry Stebbings' 20VC fund, which recently closed a new $400M fund (and invested in 6 seed unicorns in just 5 years! 🤯), stands out by offering more than capital. Stebbings has structured the firm with specialised sub-funds, including 20Growth, 20Sales, and 20Product.

Not surprisingly, 20Growth started as a post-investment platform. 20VC initially assembled leading growth and product experts to assist its founders, which grew into 20Growth, a dedicated sub-fund with nine industry veterans from companies like Shopify, Dropbox, Pinterest, and DoorDash. The US$5M fund provides hands-on and practical guidance in critical areas like user acquisition, retention, marketing, and revenue growth. Portfolio companies "get nine of the best growth leaders with one check."

Stage 2 Capital is another fund that takes growth support to the next level. The fund invests in early-stage B2B software companies and works closely with leadership teams to establish and drive sustainable revenue growth. Mark Roberge, the Managing Director of Stage 2 Capital developed a fantastic guide, "The Science of Scaling," which showcases the proven approach to building a revenue engine—from product-market fit through go-to-market fit all the way to growth and the moat phase. Additionally, the fund's network of 250 experienced GTM executives provides portfolio companies with direct access to seasoned professionals.

Growth is also our main focus at Seedstars International Ventures, making Seedstars the first global early-stage fund in emerging markets to build a platform centred on growth. The execution follows three elements: Our Entrepreneur in Residence hosts regular growth-related webinars, open to all portfolio team members and available for repeated participation, ensuring continuous learning for new hires. To turn knowledge into action, each portfolio company is paired with a Growth Partner—an industry expert, often with unicorn experience—who guides them in applying best growth practices. Finally, we foster collaboration through peer-learning sessions, where companies share insights and strategies across the portfolio.

At its core, the growth focus we propose as a fund involves running rapid experiments across different marketing channels and product development initiatives to discover the most efficient ways to drive business growth.

Growth Resources Beyond VC Support

Undoubtedly, a holistic approach to growth is a must for every ambitious startup. Luckily, there are great resources that founders can use in case they can't rely on their investors.

The first is Reforge, a platform offering in-depth growth programs led by top industry experts. Their Growth Series is particularly well-known for providing actionable frameworks and strategies used by high-growth companies such as Dropbox and HubSpot.

Lenny's Newsletter: run by Lenny Rachitsky, a former product manager at Airbnb. This newsletter offers deep insights into growth tactics, product management, and scaling companies. I couldn't recommend it more!

Given that the founders know what they’re looking for, it’s worth checking out Growth Mentor. This platform connects founders with experienced growth professionals for one-on-one advice. It's ideal for those seeking hands-on help.

The Power of Diverse VC Support

It is still rare in venture capital to make growth a core part of platform strategy. While it’s a perfect fit for some funds, others may create more impact with different approaches. At the end of the day, this diversity is beneficial, as it allows founders to choose investors based on the specific value they bring to the table, ideally giving each investor a unique role.

Ultimately, the market rewards growth above all else. More VCs, especially those in emerging markets, need to step up with hands-on, practical support, whether for hiring, product development, networking, or growth.

Thank you to Konstantin Hapkemeyer, Charlie Graham-Brown, Cyrine Ben Fadhel and Tiziana Bombassei for providing feedback on the early drafts of this post.

Criticism of the “VC Platform” profession (i.e., the role in VC primarily responsible for the value creation component) is a boomerang in industry conversations, always coming back around.

Twitter, LinkedIn, and Instagram are full of memes about VCs “adding value” (like the one below).

Last year, Kate Clark’s article “Why VC's Platform Teams Are on the Chopping Block” generated considerable buzz among the platform professionals' community who disagreed with the statement that “…firms should run their shops like pro sports teams. Get rid of the poor performers [portfolio services team members] and optimise the roster.”

The recent summary of Fortune’s 2024 Brainstorm Tech conference in Park City, Utah, “What GPs and LPs say to each other behind closed doors” by Allie Garfinkle, features a spicy comment of one of the attendees saying that “VC platforms are BS” and claiming that VCs using platforms to court founders are just posturing. Platforms meant to offer resources beyond funding are seen as unnecessary distractions by founders. They prefer direct access to partners over constant platform support. This comment, again, caused a lot of disagreement among the audience.

Contrasting Views on VC’s Role

It seems to be a controversial topic in the entrepreneurial community that is divided into two groups:

(1) Self-Reliance Advocates: People who believe that VC exists to write checks and pick exceptional founders who don’t need any support because the GPs wouldn’t back them in the first place

(2) Collaborative Partners: People who believe VC funds should offer smart money. Once they invest, they become almost an extension of the founding team and do everything they can to contribute to the company's success.

So, in an attempt to do a reality check, it’s worth considering facts, not opinions, to answer the controversial question: Is VC platform BS?

Fact 1: Founders want their investors to help

The Forward More Than Money Report 2021 indicates that 61% of founders want more than money. The number is even higher if we look at female founders (a vastly underrepresented group in most ecosystems worldwide): 86% of female founders consider value-add necessary when picking a VC - that's 26% more than their male counterparts.

Another report, The Frontline What Founders Want, shows that founders see VCs as an extension of their sales team: 63% of US-based founders (30% in Europe) chose ‘introductions to prospective customers’ as one of the three factors they consider when selecting VCs. Other ‘value add’ factors considered include fundraising support, help to expand into new markets, help to hire talent, peer network and PR support (these, in fact, are the primary platform categories defined: see VC Platform Strategy Matrix by Cory Bolotsky).

The research Do VCs add value?, led by three Kauffman Fellows, confirms that founders believe VCs can help in three main areas: fundraising (39%), founder coaching (17%), and hiring support (14%).

Founders can exist without Venture Capital, but VCs are helpless without founders. The power dynamic is clear: VCs must bend or break.

Though only a tiny fraction of companies raise venture capital, many of the biggest tech successes—Google, LinkedIn, Twitter, Facebook, Apple, Cisco, Uber —did. Half of all US public companies founded since 1970 had VC support. This underscores the critical role venture capital plays in shaping the future of innovation and the global economy, acting as the driving force behind many of the most transformative companies in history.1

Fact 2: Funds with value creation platforms perform better

These VC funds that listen to founders and provide value-added services have historically outperformed those that don’t.

The VC Platform Community analysed 850 VC firms between 2020-2022 and found that VCs with Significant Platform produced 1,160 basis point improvements in Net IRR and 0.9x TVPI compared to VCs with No Platform in the last decade.

As the Platform function has matured over the last 10 years, the difference in fund performance across these categorical cohorts is far more pronounced than in the early years of the century.

Reality check: Founders often don’t know how to ask for help

As a venture capitalist, I frequently encounter founders who express frustration over not receiving the promised benefits from their so-called "value-add" investors. However, are the founders fully aware of how to leverage the potential value their investors could offer?

Sam Corcos, the founder of Levels, shared an interesting point of view in my all-time favourite Lenny’s Newsletter post:

”Between June 27, 2019, and October 26, 2022 (about 3 years and 4 months), I facilitated 2,626 requests through our investor network. Out of those, 1,664 received a response, and 1,151 successfully delivered on the ask.”

The reality is that investors typically have limited insight into the day-to-day workings of your company or your immediate needs. Expecting them to proactively offer value without clear guidance is unrealistic. Founders need to develop the skill of making precise, actionable requests—a task that may seem straightforward but actually requires significant practice, and many founders struggle with it.”

Levels’ cap table includes A16Z, Long Journey Ventures, TriplePoint Capital and many prominent angel investors, including Lenny Rachitsky. 60% of them tried to help, and every 7 out of 10 responses to the founders’ request met his expectations. Not bad, right?

Reality check: VCs often overpromise and underdeliver

VCs like to think they’re adding value, but founders don't always agree. In 2021, 92% of VCs said they were value-add investors, yet 61% of founders rated their experience below average (Full report). The numbers back it up: in 2018, VCs rated their impact on portfolio companies as a 7 out of 10. Founders gave them a 5.3. By 2022, nothing had changed—VCs still rated themselves a 7, while founders scored them even lower, at 5.2 (Full article). The gap is clear, but it’s not surprising. VCs think they're helping, but founders are looking for something they’re not getting.

To add to this, founders often say that VCs' value-added efforts aren’t goal-oriented. What’s the problem, then? No one knows what the end result is supposed to be. If there’s no clear target, it’s hard to measure success—or even see if you’re on the right track. VCs might think they’re helping, but without a clear goal, it’s just noise.

Proactive VCs with a clear superpower win

A proactive portfolio strategy outperforms a reactive one by intentionally creating value rather than waiting for founders to request support. It actively drives value instead of waiting for founders to seek assistance. With a clear plan in place, VCs are not just responding to problems—they're preventing them and aligning efforts with financial outcomes. By leveraging pattern recognition, VCs can anticipate potential challenges and take action before they become issues.

As my fellow platform leader, Dan Kozikowski of FirstMark, put it: “The question isn’t whether the Platform works. It’s whether your Platform is working toward the right things.” The key is focusing on one superpower that can become the fund differentiator. For example, YCombinator would probably put fundraising as their superpower, and 500 Global might cite their global network (at Seedstars International, the focus is on growth).2

In the end, success comes from proactiveness and a clear focus. By adding value early and honing a specific strength, VCs can stand out and deliver real results.

Final thoughts

As the startup ecosystem evolves, the relationship between founders and VCs is bound to become even more collaborative. Founders and VCs clearly need more upfront discussions to align expectations from the start. Founders should also put effort into thoroughly vetting their investors to ensure the best fit. Doing due diligence on VCs is just as crucial for founders as it is for investors.

VC Investors adding value are BS only when executed poorly… by both.

I’m Mal. I manage a diverse VC portfolio of over 140 startups from 35+ countries for Seedstars International Ventures. 🌍🇨🇭

Outside of work, I’m on a mission to build the ultimate global cheesecake ranking.

Writing helps me think and organise my thoughts, develop opinions, and compare them against others. I only publish my notes when I have something worthwhile to say.

I decided to start sharing my notes for a couple of reasons:

• To organise my thoughts;

• To dig deeper into ideas, research them, and get feedback from smart people (whether they agree or not);

• To recommend the best cheesecakes I’ve found from around the world.

✨Please reach out via Linkedin if you’d like to chat.

* Disclaimer:
I actually love my dog and husband more. I’ve tried to update the world about them... Didn’t work. Some friends even left the group chat over too many dog pictures (sorry, not sorry) 🥲

Eight months after the loud US $1B Fund of Funds (FoF) announcement by Qatar Investment Authority (QIA) at Web Summit Qatar last February, the buzz around Qatar's growing VC ecosystem has only intensified. But beyond the headline-grabbing announcements, what's really happening on the ground?

A recent Startup Grind Qatar event in Doha [Venture Capital Unplugged: The Ecosystem & Funding Blueprint] provided some answers. On stage, we had Michael Lints (Golden Gate Ventures), Alexander Wiedmer (Rasmal Ventures ), and Muhannad Taslaq Alchemist Doha) and the chat was moderated by Salman Surti.

The Impact of QIA's US$ 1B

The much-publicized QIA $1 billion FoF was undoubtedly a major moment for Qatar's ecosystem, but was it truly a turning point? According to Alexander Wiedmer, who has been in Qatar for over five years, the country's ecosystem had been evolving in the right direction long before this announcement. He emphasised that the ecosystem has become increasingly sophisticated over the past four years, not only since February.

Michael Lints, with his extensive experience in Singapore's VC scene, agreed, noting the parallels between Qatar's journey and Singapore's rise as a VC hub. He referenced Singapore's Technology Incubation Scheme (TIS), which attracted international funds to the region. Qatar's current trajectory, especially with the $1 billion injection, mirrors that growth and presents a unique opportunity to attract VCs committed to being on the ground and building the ecosystem.

New Funds and Investment Strategies

Rasmal VC and Golden Gate Ventures, now operating in Qatar, offered insights into their investment strategies. Rasmal, a Qatari-born fund, allocates 15-20% of its assets under management (AUM) to Qatar, 60% to the broader MENA region, and 20% to international deals. The fund is a generalist but focuses primarily on tech, with a preference for Series A companies.

Golden Gate Ventures, which originated in Singapore but is now operating also in Doha, focuses on B2B companies with strong product or tech components. While the fund is MENA-focused, it is not obligated to invest solely in Qatar. Michael shared that Golden Gate has a couple of open deals in the pipeline and is actively deploying capital so we might be expecting some first announcements soon 👀

Both VCs highlighted the collaborative nature of the VC space. Michael Lints shared that in his 15-year career, only two deals his fund backed were done independently, with no co-investment partners. This spirit of collaboration is expected to drive co-investments between Rasmal and Golden Gate Ventures.

The Role of Accelerators in MENA's Growth

The Alchemist Accelerator is making waves in Doha, aiming to attract global founders and foster a robust entrepreneurial community. Both Alex and Michael emphasised the importance of accelerators in their investment pipelines. However, they also noted that participation in an accelerator is not a must to get a VC investment.

That said, accelerators can add value to a startup's journey, often helping to fine-tune business models, build networks, and prepare for fundraising. The Alchemist's industry-agnostic approach ensures that founders from various sectors can benefit from the program and contribute to the ecosystem's growth.

The Angel Investment Scene in Qatar

Angel investors play a crucial role in Qatar's VC ecosystem. Alex highlighted the presence of strong angel investors in the region and the need for further development of this type of investment. Doha Tech Angels LLC is an excellent example of an angel network that has been a critical contributor to early-stage funding in Qatar. Given the wealth in Qatar, there is room for even more activity, and key institutions like Qatar Development Bank (QDB) are working to boost angel investment further. For example, QDB launched a training program for people interested in angel investing to help them make smarter investment decisions.

Michael added that serial entrepreneurs often transition into angel investing in mature ecosystems, and Qatar is likely to follow this pattern as its ecosystem continues to grow and mature.

The Role of Grants

Grants were briefly discussed during the panel. The key takeaway was that grant funding can benefit startups as long as strategic angels or early-stage VCs complement it. Standalone grants, however, might not be sufficient to sustain long-term growth.

Value-Add from Qatari-based VCs

Alex and Michael emphasised that their funds aim to back founders only if they can add value. While they didn't elaborate much on their specific value-add strategies, Alex mentioned Rasmal's "open-door" policy, which allows entrepreneurs to pitch their ideas and receive feedback, even if they aren't ready for investment.

Final Thoughts

The room at the Startup Grind event was packed with young entrepreneurs full of ideas and eager questions, showing just how exciting Qatar's tech scene is becoming. With more VCs, accelerators, and founders coming together in Doha, the entrepreneurial ecosystem is set to take off. The evening saw two announcements of new initiatives launched in Qatar: Alchemist Doha and the next wave of Qatar FinTech Hub.

Qatar's VC ecosystem may still be young, but the groundwork is being laid for something remarkable. With a collaborative investment environment, increasing angel activity, and new accelerators, the future looks promising. My hope is that as we continue to grow, we will see more diversity in the ecosystem and more female investors and entrepreneurs involved.

This post was previously published on Linkedin in September 2024