There's a specific kind of tired that comes from being the person at work who's expected to have a take on every new AI model. If you’re that person, this week must’ve been exhausting. My inbox and feed filled up with takes on the same model. Some calling it a DeepSeek moment, some finding the American upside in a Chinese model, and the rest just listing specs.

Kimi K3 is one of the biggest open-weight models anyone has announced, sitting just behind Fable 5 and GPT-5.6 Sol. Except you cant download it yet, the weights land July 27. "Open-weight announced" is the honest version, not "open-source."

The day before Kimi K3 launched, Mira Murati's Thinking Machines dropped Inkling, which is smaller, downloadable today, not trying to win anything. Just a base other people can bend to their own work.

Neither of these models kills Claude or ChatGPT. What they do kill is the idea that any one company owns intelligence for good, which is exactly why I recently said that you shouldn’t marry a single model. Six labs now have a model that would've been the frontier in early June and the price keeps falling. It’s now crowded and cheap at the same time.

And this is where the model race runs into the much slower reality of work👇

Window into the Future

The uncomfortable truth about AI at work right now is it doesn't always lift an entire team or business as much as it creates outliers. Boris Cherny, who built Claude Code, shared this week that he keeps hearing the same line from teams everywhere: one person 10x's their output with AI while the rest of the org never catches up.

Boris is talking about engineers. Swap engineer for a marketer, a finance analyst, the person who owns hiring, and the shape doesn't change. And notice that clearing one blocker just reveals the next, and it’s almost never the model or the tool but whether people can manage the thing in front of them.

Everyone's fighting over who owns the frontier, open weights, closed weights, Kimi, Fable, etc... but you can download the best open-weights model on earth tomorrow and your company still won't have changed how it works.

Say you run people at a company of a few thousand. Five of your staff are basically AI-native now who changed their work around AI without being asked to. Everyone else is still waiting to be told what to do with it. We watch this split all the time at 100 School. Giving everyone a licence or more AI training on its own doesn't fix that. The issue is not access or enthusiasm but that no one owns the next step:

• who redesigns the workflow?
• who checks the output?
• what does the manager reinforce?
• how does anyone know it worked?

That last one is where a lot of the market cheats. Someone pulls up a usage chart: logins up, tokens up, and calls it ROI. I wrote a while back that usage tells you the tool got opened, not that anyone got better at their job. Boris, who has every reason to love a usage number also says usage "measures activity, not return”. Would you have paid a person to do this work? how many hours? that's the only number worth putting in front of your boss. Everything else is just people opening a tool.

The companies that get through this do it slowly, and someone owns it. We've run AI training inside HiBob for over 18 months: 9 departments, 1 function at a time, because what works for sales doesn't work for product. Nowhere near as fun to post about as a 2.8-trillion-parameter model. Also the only version I've seen that sticks.

Two weeks ago, I asked how you were feeling about and one of you said: “there's a new tool every day, and I'll always be behind”. You will. We all will. That race has no finish line so stop using “caught up” as the goal. Pick one workflow, decide who owns improving it, give them the time to try, check whether the result is actually better. The next model will arrive before you’ve finished. That’s fine. The advantage isn’t knowing every tool. It’s getting good at turning useful experiments into normal work.