Dharmash Mistry

Chair/NED (@premierleague, @halmaplc, @Rathbones), @BBC, @BritishBBank | VC Lakestar @Balderton | Founder @blowLTD | TheDirectorBrief AI Intelligence for Boards

[David Sacks @DavidSacks]

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.

You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.

I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.

But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.

Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.

Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.

So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.

If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.

[Dharmash Mistry @Dharmash]

The board exercise, once a year:
With £100m, frontier models, no legacy and no sacred cows — which of the four routes would we use to attack ourselves first?

Full framework (the Six Ps) in this week's Director Brief.

[Dharmash Mistry @Dharmash]

Three companies your board probably hasn't discussed — and the four ways AI-natives attack.
Every challenger picks one route in: reinvent the product, the workflow, the economics, or the distribution.

[Dharmash Mistry @Dharmash]

Same mechanism is now moving from information to transactions.
What does agentic commerce do to the consumer interface for retail banks, insurance, travel, consumer goods?

[Dharmash Mistry @Dharmash]

Squads of the last 4 teams (and top 4 ranked by FIFA) - Spain, Argentina, France, England - the Premier league leads with 41/ 104 (39%)
- @premierleague 41
- LaLiga 29
- Ligue 1 13
- Series A 8
- Bundesliga 6

[Dharmash Mistry @Dharmash]

Congratulations to Spain, fully deserved #FIFA2026 world cup winners. Looking at this another way - medals table by club (gold, silver, bronze) - shows the concentration within the squad (familiarity & talent ecosystem - playing like a club side?)

@FIFAWorldCup

[Dharmash Mistry @Dharmash]

https://t.co/0diLmrwz7L

[Dharmash Mistry @Dharmash]

Only 5% of companies show real financial gain from AI.

That 5% posts 4x the shareholder return of everyone else.

[Dharmash Mistry @Dharmash]

The Six Ps of AI strategy, the one-page board AI dashboard, and the £100m clean-sheet test. link below

[Gavin Baker @GavinSBaker]

Kimi K3 may be an important inflection point for AI. Potentially negative for Anthropic and OpenAI while being net positive for essentially every other company in the world. I mean that very literally. Although the real “Sputnik moment” would be an open-source frontier model that was also token efficient unlike Kimi K3 which is 50-70% more expensive to run than GPT 5.6 per Artificial Analysis.

Rationale:

A world where there are only 2-3 dominant frontier labs with 90% inference margins is net negative for every other layer while being awesome for those 2-3 labs. Those labs would become monopsonies for power, data centers, semiconductors and hyperscalers and would obviously vertically integrate over time into all those layers while also completely subsuming the application/software layers. 

Anything that lowers margins and increases competition at the model layer is good for every other AI layer: power, semiconductors, hyperscalers, neoclouds and yes even software.

This is why Jensen is so supportive of open-source. An open-source model requires the *exact* same amount of compute to run as a closed frontier model of similar size and architecture. Kimi K3 is roughly the same price as GPT 5.6 Terra on a per token basis, which actually suggests that it is less computationally efficient as I am sure that GPT 5.6 is priced to a higher margin than K3. And given that K3 is a token wastrel, i.e. token inefficient, it is significantly more expensive per task than GPT 5.6 and Grok 4.5, which are much more token efficient. Cost per token and token efficiency (i.e. intelligence density per token) are the drivers of intelligence per unit of cost. The winning AI companies will be those that offer the most intelligence per $ over time.

Lower margin % at the model layer = more margin $ at every part of the infrastructure layer and is a godsend for software. This can happen either through open-source models like K3 at the frontier *or* having a vertically integrated model company like Meta, SpaceX or Google at the frontier. Both outcomes result in a lower margin % at the model layer as vertically integrated model companies don’t really care where the margin $ come from. This is why it was so painful for OpenAI and Anthropic when Google was right there with them from a model competitiveness perspective and why Grok 4.5 and Muse 1.1 were just as important as Kimi K3.

The reason Kimi K3 is only *potentially* negative for Anthropic and OpenAI is 1) the @ericvishria point that the Claude and ChatGPT products and harnesses may be more important than their models today and 2) the hypothesis that they have much more advanced model checkpoints internally that are already being used for RSI. In the latter scenario, reaching RSI even a few months ahead of other labs might be enough to cement a permanent lead.

Time will tell on both points. And likely fairly quickly.

Caveat would be that since Kimi K3 is not token efficient and thereby actually more expensive than ChatGPT 5.6, we may need to see a more token efficient open-source model at the frontier or see Grok 5/Composer 4/Muse 2 at multiple points on the Pareto frontier for this potential risk to Anthropic and OpenAI to play out. And I am sure they will both vertically integrate as quickly as possible while continuing the product/harness strength they have shown over the last 8 months.

[Dharmash Mistry @Dharmash]

4/Full six-week programme — free, published in full: https://t.co/HhbEf8OqbK

Try Week 1 before your next board meeting.

#AIGovernance @The_IoD @NACD

[Dharmash Mistry @Dharmash]

1/Who in this boardroom has used an AI tool to build something consequential in the last 30 days?

[Dharmash Mistry @Dharmash]

3/The result: 6 weeks, 30 min/week, zero coding, zero company data anywhere near it. By week 6 — a scheduled AI brief, a saved skill, a vibe-coded tool, sharper board questions.