weekend ai reads for 2026-01-09

Design almost never benefits from straight lines. Some ideas only show up when you take the long way around, when you don’t quite know what you’re looking for yet. When there’s room for detours, dead ends, side-quests, and a bit of adventure.

But—and this is important—you still need design thinking and systems thinking. AI handles the syntax, but you need to know what you’re building, why you’re building it, and how the pieces fit together. The hard part was never the code. The hard part is the decisions.

Nothing works on the first try. You refine. You push back. You say “make it heavier” or “this feels too corporate” and the AI adjusts. The conversation is the design process.

That “house-building” work involved in that might involve legal consulting, deciding which LLMs are suitable for a brand’s needs, as well as the boring but necessary hours required to collate a brand’s identity and past output into a guide or brief digestible by a generative AI tool — as well as the trial and error, red herrings and dead ends involved in testing an automated system that handles something as commercially sensitive as a brand identity.

It all takes time — unfortunate news when marketers also judge the success of such investments on the time they’re able to shave off ordinary processes (81% of marketers use time saved as the main KPI, according to the Gartner study).

The future of education is not about integrating AI to make learning easier. It’s about constraining AI to make learning hard enough to matter.

LLMs are emerging as a new kind of intelligence, simultaneously a lot smarter than I expected and a lot dumber than I expected. In any case they are extremely useful and I don’t think the industry has realized anywhere near 10% of their potential even at present capability.

Nine men’s morris may be the world’s oldest board game, dating back to pre-Christian times. Versions of it were played in ancient Egypt, and Shakespeare referred to it in A Midsummer Night’s Dream. In the 1990s, though, computer analysis discovered a strategy that meant you’d never lose. That knowledge made playing a lot less appealing, as mathematician Marcus du Sautoy notes in his book Around the World in Eighty Games. Against a true expert, the best anyone could hope for was to eke out a draw. “And so,” du Sautoy wrote, “after thousands of years of people enjoying playing nine men’s morris, it would seem that the computer has finally succeeded in killing the game off.”

the thing i got wrong at first is thinking vibe coding is about learning to code

and... it’s not! it’s about learning to communicate

the skill isn’t python or javascript or whatever, the skill is clarity.

7. Privacy is a misunderstanding that does not apply to data.

8. Data is made more valuable by being connected to other data. Solitary data is worthless. Unconnected data is dead.

9. Data is made more valuable by moving. Storage is weak because it halts; “Movage” is better. Unless data keeps moving, keeps connecting, unless it is exercised, it will die.

10. Both directions of movage are important — where it came from, where it goes.

11. The meta data about where data goes, and what it is linked to, is as important and valuable as the data itself.

No sync issues. No “wait, which repo has the current pricing?” No deploy coordination across three teams. Just one change, everywhere, instantly.

At Kasava, our entire platform lives in a single repository. Not just the code—everything

I took 6 top Hollywood cinematographers with ZERO AI experience and taught them a simple framework to master the tools.

You can easily learn this process in minutes

Here are the exact tips, prompts, and framework we used

Goal: I want to write a Pindaric ode-style poem to lab animals, praising them and their unwitting yet noble sacrifices, in their teeming hundreds of millions over the centuries.

Best anti-AI death metal album
That would be The Diseased Machine, by Mutagenic Host.

Guiding policies are typically going to be implicit or explicit tradeoffs. If a guiding policy doesn’t imply a tradeoff, you should be suspicious of it (e.g. “working harder to get it done” isn’t really a guiding policy)