How These Briefs Work

Every brief in this bundle follows the same shape. Once you know it, you can read any brief here in a couple of minutes and know exactly where to look for the part you need.

What's in every brief

Each brief opens with a short paper header: the title, the authors, where and when it was published, who it's really for, and a link to the original. The link matters — a brief is our read of the paper, not a replacement for it. If a brief changes how you think, go read the source.

Then six sections, always in this order:

• The one-line takeaway — what the paper found and why you'd care, in a sentence.
• What they did — the study in plain language. Enough method to trust the rest, no more.
• What they found — the few results that matter, with the actual numbers.
• How much to trust it — the honest read. Sample size, who funded it, peer-reviewed or preprint, whether the conclusions follow from the evidence, and where it overclaims.
• So what — for you — what you'd do differently because of this. The reason you're here.
• The fine print — limits, scope, and where not to over-apply the result.

How to read "How much to trust it"

This is the section to slow down on. A paper can be interesting and still be thin, early, or funded by someone with a stake in the answer. We flag those things plainly so you can weigh the finding yourself.

Treat it as a flag to slow down, not a final verdict. A preprint with a small sample isn't worthless — it's early. A well-funded result isn't fake — it's worth a second look. The section gives you the questions a careful reader would ask. You decide what the answer is worth.

How briefs are grouped

Briefs are sorted into themes so you can follow the area you care about. A theme shows up on the site once it has its first brief, so the list fills in over time. The themes we're working toward:

• Agents and tool use — AI that takes multi-step action and uses tools.
• Reasoning and capabilities — what models can and can't do, and how they plan.
• Training and efficiency — how models are built, tuned, and made cheaper to run.
• Evaluation and benchmarks — how AI gets measured, tested, and compared.
• Safety and alignment — keeping AI useful and reducing real harms.

What a brief is not

A brief is a starting point, not a citation you can lean on. We summarize one paper and add our own plain-language read; we don't re-run the experiments. The numbers in a brief are checked against the paper itself, but the paper can still be wrong. When a decision rides on a result, read the original and check it for yourself.

Each brief reflects the paper as it stood when we wrote it. A later paper doesn't change an old brief — it gets its own. So a brief is a snapshot, dated at the top, of one piece of work at one moment.