Lighting $ on fire, Waymos, & $1.5/Month agents

TLDR;

Welcome back! Today, we take a look at announcements from OpenAI and Anysphere, but this week is less about names and more about trends, such as:

Leading labs embracing adaptive-compute models,

progress is increasingly tied to human-in-the-loop effectiveness,

And venture investment is flowing toward teams that train their own systems rather than wrap others.

At the same time, frontier economics look more strained than ever, with rising inference costs and aggressive price pressure from China, which isn’t making things look any better.

ANNOUNCEMENT

Coaching Calls

Additionally, I’m officially launching one-on-one calls to discuss any AI topics you desire, scheduled at your preferred time. These calls cover a range of topics, from product strategy to company and sector due diligence, tailored to your specific needs.

Please note that my time zone is GMT+1, so US mornings and evenings in Asia are ideal.

Book your call today below!

MODELS

OpenAI’s Release of GPT-5.1 Holds some Surprises

In a surprisingly low-key fashion, with very little benchmark data and a very small model card, OpenAI launched GPT-5.1 yesterday. The biggest improvements come from better instruction following and, more importantly, better adaptive thinking.

As you can see in the above graph, the GPT-5.1 models (Instant and Thinking) have an improved capacity to identify request complexity and think for longer or not on the task. They think much faster for more manageable tasks, and will think for much longer on the more complex tasks.

In case you don’t know, much of the improvement in AI models over the last year has been an increase in ‘test-time compute’, the amount of compute allocated to the task. Models remain largely unchanged in structure, they just “think for longer” on the task.

TheWhiteBox’s takeaway:

We still have no updates for Pro and Codex (no GPT-5.1 Pro, no GPT-5.1 Codex model), which I assume will come soon and could be the actual release (this looks more like a small taste update to improve their non-thinking models, which had become way worse than competitors).

Moreover, I believe OpenAI is abandoning the smart router (or, more accurately, not being the sole method for model variations) and moving towards hybrid models, such as those developed by Anthropic or Google.

Hybrid models, not to be confused with hybrid architectures, are models that autonomously decide how long to think on a task. Previously, OpenAI had a smart router that would process your request and decide whether it should be answered by thinking or non-thinking models.

Based on the fact that they refer to GPT-5.1 Instant (a singular model) as an adaptive model, it suggests that they are also using hybrid models (or adaptive models, as they are called). It turns out, OpenAI was wrong.

AGENTS

Claude’s Robot Effort

I think this is a video everyone should watch, because it perfectly illustrates what AI is today and, perhaps more importantly, what it isn’t.

In this one-day experiment, two teams, one with access to Claude and the other as “Claude-less,” were tested to see which one…

Enjoyed the introduction? Subscribe or sign in to continue with this edition.