The Frontier Got a Guest List

OpenAI taped out a custom inference chip in nine months. The question isn't whether it works — it's when owning the silicon actually pays, and who keeps the savings.

When a model price cut is a moat move, not a gift.

How training on another model's outputs actually copies it — and why black-box access turns the copy into a volume game.

the retry stopped being an edge case — now it's the loop, and your tools are exposed.

The usable context budget is smaller than the advertised one — drive below the line, and don't let compaction pick what survives.

Why a model can emit tokens faster without changing a single one of them — and the two numbers that decide how much faster.

Why parallel coding agents collide, and the twenty-year-old git feature that fixes it before you reach for a new VCS.

The export ban made "go multi-provider" the reflex. A gateway swaps your URL in an afternoon. It can't swap your prompts, your tools, or your evals.

Why mixture-of-experts decouples a model's size from its price — and the two numbers to read on every model card.

how Claude Code's context compaction works, and how to stop it summarizing away the thing you needed.

What you actually buy — and build — when you ship an "agent."

The advertised discount is real; almost nobody collects it, and the reason is one number.

What it actually takes to replace Claude with a local model on your own machine.

"Open" tells you almost nothing about an AI model; the license — and whether it caps you — tells you the rest.

The crypto wars already ran this experiment. The government lost — and left American products weaker for a decade.

Nested sub-agents just shipped 5 deep. Here's what each one actually costs, and when one context is cheaper.

A coding benchmark number is a claim about a harness, not about your codebase — read it like one.

A funded, adopted, well-built open-source LLMOps startup just gave its money back. The product worked. The position didn't.

Two npm worms beat code review, signed provenance, and install-script scanning in one week. Here's why every layer failed, and what actually changes now.

When the model commoditizes, who owns the off-ramp?

We made agents proactive by default before we shipped the cost-control, consent, and observability to make proactive safe. Who pays, and who has to disclose?

Can AI coding tools survive honest pricing — and was the flat rate ever real?