Derya Unutmaz has spent most of his career studying T cells. He gave GPT-6 Astra a single prompt: "Create a 5 minute educational video about T cells."

One prompt, one lecture@DeryaTR_
Astra wrote the script, generated the visuals, used the Remotion plugin for the animation, and added narration.

Watch it before reading on, because the reaction is the finding. A researcher of more than 35 years in the field said he could not have explained it that well, and is now planning a full lecture series the same way.

This is the most impressive demo of launch week and almost nobody outside biology saw it.

The same week, a closed piece of hardware

Claire Vo owns a Divoom Bluetooth pixel speaker. Closed device, no API, undocumented protocol. She calls it her "personal Everest" and has been trying to crack it across model generations. Earlier models, in her words, "barely let me flash a 'hello world' message."

Astra built her a web app that connects to the device and lets her draw on it live with a mouse. Then a CLI so the speaker could talk back. Then, given a prompt about her latest podcast episode, it found the episode information and streamed a scrolling message and an animated graphic to the speaker's screen.

Claire Vo
Claire
Vo

"The ability to finally interact with hardware in this meaningful way is a step-change."

How I AI · September 2026

These are the same problem

A protein-signalling pathway and a Bluetooth protocol have nothing in common except the thing that matters here: the documentation did not exist.

Divoom never published the protocol. And 35 years of immunology intuition is not written down anywhere in the shape a teaching video needs, which is exactly why making one is hard and why Unutmaz was impressed. In both cases Astra had to construct the missing map before it could produce anything.

Figure 1. Two runs, one move
The map had to be built before anything could be
A protein pathway and a Bluetooth protocol, same gap. THE ASK WHAT WAS NOT WRITTEN DOWN WHAT CAME BACK IMMUNOLOGY  /  DERYA UNUTMAZ, 35 YEARS IN T CELLS One sentence: "Create a 5 minute educational video about T cells." 35 years of research intuition, never written down in teaching shape A 5 minute video: script, visuals, Remotion animation, narration HARDWARE  /  A CLOSED DIVOOM BLUETOOTH SPEAKER Control a pixel speaker with no API and no published protocol The protocol itself. Earlier models managed a "hello world" message A web app that draws on it live, then a CLI, then a scrolling episode graphic IN BOTH RUNS THE MODEL HAD TO BUILD THE MAP BEFORE IT COULD BUILD ANYTHING.
The middle column is the asset. Every company has one, and nobody has written it down.

The 3D work in Part 1 is the third instance of the same move. A 2D sketch does not document a steam train's parts, and Astra returned 3,295 of them.

Anatomy, twice

Put the immunology run next to the 50-bone skeleton from Part 1. Same competence, different domain. One arranges bones so a wolf runs correctly. The other arranges concepts so T cell memory formation makes sense to a student. Both need a working internal model of a system, not a lookup.

Spatial reasoning showed up as its own claim too.

Mapping a space, then shooting it@higgsfield_ai
Higgsfield: Astra mapped the museum, the cast and the shot list, and kept the blocking in the viewport.

Why this matters more than the games

Every kart racer and FPS map from launch week is a build in a domain where success is obvious and the model has seen ten thousand examples.

These are different. In each one the person holding the stopwatch was a specialist evaluating work inside their own speciality, and the specialist was impressed. That is a harder test to pass and a harder result to wave away.

It is also the one your company should care about. You do not have a shortage of kart racers. You have a shortage of the thing Unutmaz has: knowledge that lives in one person's head and has never been written down in a usable form.

The operator read

Find your undocumented system. Every company has several. The pricing logic only one person can explain. The integration nobody has touched since the engineer left. The onboarding knowledge that lives in a senior rep's habits.

The old answer was to schedule interviews and write it down, which never happened. The new option is to point a model at the artifacts, let it construct the map, and have your specialist correct it. Correcting a draft is a job people will actually do. Writing from scratch is not.

One caution, and it is the whole of Part 4: each of these was one attempt, by an expert, on a task they chose.

Keep reading.

Teardowns, benchmarks and playbooks on building AI-native products.

Browse the Playbook →

Part 3 of Astra, Week One.

Sources
1Derya Unutmaz, MD (@DeryaTR_), September 3, 2026, embedded above: the video was produced from the single prompt "Create a 5 minute educational video about T cells," using the Remotion plugin for generation. Unutmaz has devoted most of his career to T cell research. Additional detail on his reaction and the planned lecture series as reported at favtutor.com.
2Claire Vo, How I AI, September 2026, on the Divoom Bluetooth pixel speaker: "a closed device with no API", her "personal Everest"; earlier models "barely let me flash a 'hello world' message"; Astra "built me a web app that allows me to connect to the device and draw on it live with my mouse. Then, it built a CLI so I could have it talk to me about anything it wants." chatprd.ai
3Higgsfield AI (@higgsfield_ai) and Matt Wolfe (@mreflow), September 3, 2026, for the spatial-reasoning and rigging claims respectively.
John Tan
John Tan

Founder of nativefirst.ai and ex-CEO of Depict (YC). Runs everything on agents and writes down what works.