Eric Friedman ⚙️

Fractional CFO for VC/PE firms prev. @expa, @foursquare, @usv

[Eric Friedman ⚙️ @EricFriedman]

@tanmaye_bhatia They are lucky to have you doing this. We are doing this for other firms and this is a good reminder to share more about how we are solving these things

[Eric Friedman ⚙️ @EricFriedman]

@jasonfried @fredericrenken What do you think they need today from software that they don’t have?

[Eric Friedman ⚙️ @EricFriedman]

@chamath We’ve found the costs are well worth it https://t.co/ydYeqhCcmK

[Eric Friedman ⚙️ @EricFriedman]

@rywiggs @mercury I didn’t realize this and will have to try it out + Books + doing more here via CLI.

So far MCP has been great.

[Eric Friedman ⚙️ @EricFriedman]

“We only hire 52x engineers”

[Anthropic @AnthropicAI]

Each time we release a model, we run the same test: give it code that trains a small AI model, ask the new model to speed it up. It takes a skilled human 4-8 hours to reach 4x faster.

In May 2024, Claude Opus 4 averaged a ~3x speedup. This April, Mythos Preview achieved ~52x.

[Eric Friedman ⚙️ @EricFriedman]

I was hoping it would be a little longer. This is one of those gradually then all of the sudden moments. At least we can tell our kids we surfed the web with more humans than bots

[Matthew Prince 🌥 @eastdakota]

Welp, that happened faster than I predicted. Thought it would be end of 2027, then early 2027, but agentic traffic growing so fast that bots have now passed human traffic online for the first time in the Internet's history. https://t.co/2zX5bHdhsa

[Eric Friedman ⚙️ @EricFriedman]

@bryce “What could go wrong”

[Eric Friedman ⚙️ @EricFriedman]

@hnshah We should show you sometime soon what we’re building

[Eric Friedman ⚙️ @EricFriedman]

@eglyman How much does it cost?

[Eric Friedman ⚙️ @EricFriedman]

Also this was before we changed our name so the link should be to https://t.co/pqjAycoohQ 😆

[Eric Friedman ⚙️ @EricFriedman]

#3 “the zombie VC era” needs a solution for what the GPs do with the fund and I wrote our solution from 2023 https://t.co/we0T9Z45kb

[Pavel Prata @pavelprata]

Monthly VC/LP debrief.

What I actually saw in May 2026:

1/ SF is in full gold rush mode again, but history says the current winners won't stay on top forever. Every dominant technology eventually gets surpassed – newspapers, telecom, cable, Google in ads, IBM in computers. In AI the same pattern is already playing out: compute will hit walls, chips get dramatically more efficient, new energy sources emerge, and entirely new model architectures appear. The people feeling left behind today may just be early in a much longer cycle. (h/t @TurnerNovak)

2/ The largest $10B+ funds went from 140–150 collective early-stage deals per year in the SaaS era to 370–400 in the AI era. But the concentration is at the top of the market – top-decile rounds, known founders, proven operators. @kevinhartz calls it "option value": a small check today for the right to lead Series A tomorrow. The average seed round remains territory for EMs.

3/ We might be entering a Zombie VC era. ~85% of 2017–2018 vintage funds still haven't returned 1x DPI after 7–8 years. Median DPI sits at $0.34 on the dollar, while median IRR for the same cohort looks respectable at 11.6%. Paper returns hide the reality. The liquidity window opening over the next two years will be the moment of truth for most of these funds.

4/ @SpaceX IPO might be the single largest DPI event in VC history dropping into the lowest-distribution moment in venture capital history. @foundersfund alone, with an early $20M check in 2008, could return $60B+ (~3000x). When that capital hits LP accounts, it needs to be redeployed and that will circulate a new wave of fundraising for the same funds and fresh allocations from LPs who finally have liquidity to work with.

5/ The @cerebras IPO was the first real data point on crossover returns after two years of everyone writing off the model – both early-stage VCs and late-stage crossover funds made money on the same company, and LP conversations shifted from "do we have any exposure to the winners" to "how do we get into the next one." The same strategy that was declared dead in 2022-2023 got fully rehabilitated by a single exit. (h/t @MeghanKReynolds)

6/ Monte Carlo across 1,391 VC funds: concentrated portfolios (15 companies) and diversified ones (100 companies) produce the same average fund return – 2.44x. But compounded across multiple vintages, diversified wins: 2.25x vs. 1.78x. Concentrated funds carry more variance per fund, and variance drag compounds against you over time. The extreme outcomes (15x+) are almost exclusive to concentrated funds but the probability is tiny either way. (h/t Steve Kim)

7/ EM activity is showing the first real pulse in years. @cartainc logged 78 new US venture funds in the $10M–$100M range in Q1 2026 – a 34% jump from Q1 2025. Still well below the 2022 peak of 147, but the post-winter bottom might finally be in. The managers raising right now are doing it without a favorable macro, without easy LP recycling, and into a market where mega-funds are more active at seed than ever. (h/t @PeterJ_Walker)

8/ 76% of all EM-focused FoFs are American. The entire addressable market for a Fund I or Fund II isn't 132 FoFs – it's roughly 33. The other 100 exist, but Classic and Government-Led FoFs structurally can't anchor an early-stage vehicle: the check size doesn't justify the overhead, and a pension board can't be sold on a first-time manager without a track record. Geography and fund type filter out 75% of the market before the first meeting. (via @murphcapital)

9/ The 10-year fund is structurally mismatched with the assets mega-funds are holding. @SpaceX has been private for 18 years. @stripe for 15. For managers at that scale, @sequoia's move makes sense – open-ended, permanent capital, indefinite horizon. For small funds the logic runs the opposite way: the 10-year horizon enforced as a hard constraint, secondaries at Series C/D as the default exit, actual distributions on schedule. (h/t @credistick)

10/ There are only 3 positions that matter in a startup's cap table story: first investor, most helpful investor, biggest investor. Biggest is reserved for ~10 megafunds. First requires conviction most managers don't have – and LP preferences for concentrated portfolios often push against it structurally. So 90%+ of firms end up competing for "most helpful," which is why every pitch deck has a platform slide and every GP talks about their right to win oversubscribed rounds. (h/t @arian_ghashghai)

Every month I track new fund launches, LP events, market reports, and what's actually moving in VC/LP.

All of it in the @murphcapital newsletter: https://t.co/Wi8pAGQHLB

[Eric Friedman ⚙️ @EricFriedman]

@NikMilanovic @marvinliao @ThriveCapital I want to talk to them.

[Eric Friedman ⚙️ @EricFriedman]

@trq212 This is awesome

[Eric Friedman ⚙️ @EricFriedman]

@lukepierceops Great list

[Eric Friedman ⚙️ @EricFriedman]

@brianmichel Have you tried restarting your router?

[Eric Friedman ⚙️ @EricFriedman]

I need Claude CoWork<->Claude chats connector to take things from a mobile convo back to CoWork

[Eric Friedman ⚙️ @EricFriedman]

@nic_carter @giansegato 🔥

[Eric Friedman ⚙️ @EricFriedman]

@hnshah @SamAsante Ah maybe it has that already with “learn as you” that was my main question. How it learns to suggest like you write.

[Eric Friedman ⚙️ @EricFriedman]

@hnshah @SamAsante Can you train/retrain on your own writing as you change somehow?