AI 2027, 6 Months Later - FutureSearch

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> **Andrej Karpathy:** "There's some over-prediction going on in the industry..."
>
> **Dwarkesh Patel:** "What do you think will take a decade to accomplish? What are the bottlenecks?"
>
> **Andrej Karpathy:** "Actually making it work."
>
> — [Dwarkesh Podcast, Oct 17, 2025](https://www.dwarkesh.com/p/andrej-karpathy)

6 months ago, in April 2025, [Dwarkesh announced the _AI 2027_ project](https://www.dwarkesh.com/p/scott-daniel) on his podcast, interviewing authors Daniel Kokatajlo and Scott Alexander. Now, Karpathy justified his much longer timelines to Dwarkesh, on what's holding back coding agents, the first step in the _AI 2027_ timeline:

![FutureSearch co-authored the AI 2027 timeline forecast showing predictions for Superhuman Coders](https://futuresearch.ai/ai-2027-6-months-later/timelines.webp)

[FutureSearch](https://ai-2027.com/research/timelines-forecast) co-authored the AI 2027 timeline forecast. We predicted that Superhuman Coders would take about 3x longer than the other [AI Futures](https://ai-futures.org/) forecasters predicted.

## The Not-So-Fast Thesis

For AI experts, Karpathy's view is a better counterargument to short timelines than [ours](https://futuresearch.ai/ai-2027). But for non-AI-experts, we think the practical considerations we raised are worth reflecting on with 6 more months of evidence. As forecasters, this is more of an "outside view" - regardless of how exactly AI improves, what problems might slow down an R&D-based takeoff scenario?

One key point was: "Commercial Success May Trump the Race to AGI". We wrote:

> So far OpenAI, the leading contender to be the company in the _AI 2027_ story, has spoken more about consumer revenue growth and less about transformative AI.
>
> This piece requires at least one frontier lab to dedicate the majority of their resources towards building AI for their own internal use. We have reason to doubt that many of them will.

An AI takeoff as soon as 2027, in the scenario, depends on a stupendous capital investment in running a vast number of expensive AI agents to do AI research inside the companies. So are they actually preparing for this, and trying it?

## Are AI Companies Focusing on R&D Speedups?

So, since April 2025, what have we learned about frontier labs investing their AI into superhuman coding to accelerate their internal rate of R&D? Here is a quick assessment:

- **Anthropic**: Heavy focus on R&D speedup via coding agents, notably Claude Code being used extensively internally.
- **OpenAI**: Moved strongly towards consumer, e.g. with the Sora app, shopping features. Did build Codex, seemingly to compete with Claude Code.
- **Google Deep Mind**: No change, similar emphasis on fundamental research, always invested heavily in developer productivity.
- **xAI**: Focusing on Grok for the X algorithm, sexy companions. Grok 4 is not a top tier coding model and likely not speeding up their R&D at all.
- **Meta**: Sex

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