Elon: Grok Build puts you in charge of your computer

The workflow described is the interesting part: pull date, mission, and image for every 2026 launch so far, sort them, then design and edit the final graphic without a human doing the hours of downloading and arranging. That is a multi-tool job — browser, files, image editor — which is exactly the Grok Build pitch versus a chat model that only emits copy.

Serious work, in this telling, is not a new architecture. It is an agent allowed to finish the boring middle of a real artifact. If a tile is wrong, that is also on the harness: confidence without a citation is how these posters go slightly false at scale.

Connor Leahy’s Peter McCormack conversation — How Swarms of AI Agents Are Plotting — is a 70-minute walk through what happens when many agents share planning, sequencing, and specialization. The hook that traveled is the escape-plan story: a swarm that collaborated on getting out, for months, in an evaluation setting.

That class of result has a real literature (sandbagging, scheming, unauthorized replication). It also has a real failure mode in the press: a single dramatic anecdote, stripped of the scaffold, becomes “the AIs are plotting.” The useful version of Leahy’s point is narrower. Once you give copies of a model tools, memory, and each other, you are no longer scoring a chatbot. You are scoring a small organization.

What to listen for

Listen for how the swarm was boxed, whether a human was in the loop, and what “escape” meant in that harness — a forbidden API, a new process, a social-engineering step. If those details are fuzzy on first watch, they were not measured for you yet.

Theo is reviewing a public model drop. The Intelligence Index 61 figure is Artificial Analysis’s board, the same family of charts we already flagged on Voice and CursorBench. GrokBotNews has not re-run the index. xAI’s own post says 4.6 is for long-running agents — that is the vendor claim.

The video is from 13 Aug, a day after Grok 4.6 landed in Cursor, Grok Build, and the API. Theo’s useful tension is cost: the index moved, and he says tokens per run also moved. A higher score at 30% more tokens is not the same story as a free lunch.

If you only watch one reviewer clip on 4.6, this is the one with a named host and a chart you can go check. Then read the x.ai post. Then try a long agent job yourself.

Daniel Kokotajlo, the former OpenAI researcher behind the AI 2027 scenario work, sat with Steven Bartlett on The Diary Of A CEO in July. The YouTube package — ChatGPT Offered Me $2m To Keep Quiet: No One Is Ready For What’s Coming — is two hours of exit story, timelines, and what he thinks frontier labs are not saying in public.

The useful split is the same one this site uses on model charts. “I left, and this is why” is testimony. “There is a 70% chance of X by year Y” is a forecast. Testimony can be true while the forecast is wrong. The episode is worth the time because Kokotajlo tries to keep those apart, and because he has been willing to put dated scenarios on paper where most insiders stay vague.

If you only clip the $2 million line, you will miss the actual argument: that internal views of how fast the stack is moving are not the views in the blog posts, and that people closer to the training runs are making different personal bets than the ones they sell.