CEO at @multiply_co - Building the first collective intelligence
Serial entrepreneur / multiple exits.
Passionate about AI, human potential & co-creation.
Both of those are real. The conclusion is the part I would push on.
Keeping the team small does not solve coordination overhead. It avoids it, by capping the company at the size one group can hold in its head.
That is a fine trade right up until the work is bigger than the team you are willing to have.
you'd think AI has already killed web design agencies, yet the web design market is forecasted to 2x in the next 5 years...
companies continue to pay exceptional people who deeply understand the theory of the things they're instructing AI to do
i believe that AI is killing entry-level roles, but empowering specialists to do their job better & faster
A handover used to be a conversation. Now it is a thread pasted into a model with "catch me up".
The summary is good. But it summarises the thread, and most of what the first person knew was never in the thread.
So the handover arrives looking complete and weighing less. I'm not sure whether anyone notices.
Agencies cut a three-week round down to four days. The round then waits eleven days on the client side.
Nobody saved anything. The waiting just changed address.
The odd part is that both sides describe this as the agency getting faster.
@yunbin_bae A point of view is cheap to generate. Being answerable for one is not.
The test is not whether a model can hold a position. It is whether anything changes when the position turns out to be wrong.
So far that part still has to be somebody.
Satya is right. The way to make SI safe is not to train it with a sense of self, its own moral philosophy, and permission to act as a conscientious objector. That’s the “alignment” approach and it magnifies the control problem.
The engineering approach that Satya describes is different: separate the supply of intelligence from authority over it. Surround non-deterministic models with deterministic controls, observability, privilege limits, logging, and the ability to always contain or shut them down. Treat models/agents like powerful insider risks, not moral patients whose psychological wellbeing is at stake.
As Satya points out, the most trustworthy system is the one that lets us trust the model the least — not the one that encourages the model to develop independent agency and grievances. Engineering safety is not the same thing as “alignment.”
You can give a model more documents. You cannot tell it that something stopped being true.
For example, most of what an agency knows about a client is corrections. The route they dropped, the word they hate, who actually decides.
Those arrive in calls, and the model is only ever shown the decks unless the context is available.
AI is making creativity more valuable than ever before and..
we have 3 years of data to prove it.
Introducing the Creative Intelligence 2026 report from @contralabs.
Full report: https://t.co/wy5rIlWMjU
The premise I would push back on is that the industry is about to get smaller. When making things gets cheap, the number of things worth making goes up, and the agencies I talk to are taking on more work rather than less.
I would also change the structure before the tools. Every student project is briefed once and graded once. No job they take will work like that.
In a body almost nothing reaches the brain. You pull your hand off a hot pan before anyone has decided anything.
Companies have no version of that. Every signal gets routed to a person, and every person has a queue.
So the organisation ends up running at the speed of its slowest conversation, including for the parts that were never a judgement call in the first place.
A metastudy on generative AI and creativity found two things in the same data. Individually, people's output was rated more creative. Collectively, the pool of ideas they produced got narrower.
Both results are real. We have built an entire measurement habit that can only see the first one.
Important note regarding Grok @Bot:
Going forward, @SpaceX will use the best back end model for any given task, including Claude Opus 5.5, MidJourney, Suno and other leading APIs.
Whatever is most likely to give you the best outcome.
The three-second tell is real, and I think it gets worse in a way that is not about skill.
Everyone studying good creative is studying the same reference set, through the same models. You can raise the floor on casting and still end up with a category that looks like one brand.
Taste you can spot is not the same as taste that differentiates.