Martin Alderson

Z.AI ran a full model release on domestically manufactured Chinese chips. Impressive, but EUV lithography is a hard wall and the gap with Western inference hardware is more likely to widen than close.

Winter 2025 was the tipping point for coding agents. Summer 2026 is shaping up to be the same for open weights - and compute supply, not model quality, is now setting the price.

A practical framework for reducing AI costs - auditing token spend, killing legacy models, moving workloads to open weights providers, and fixing the agent and tool inefficiencies that quietly burn tokens.

For long agentic sessions cache reads are most of the bill, not input or output tokens. KV caches have shrunk dramatically while cache read pricing has barely moved.

For the first time I'm choosing my daily driver models on tokens per second rather than raw intelligence. Why ~100tok/s might be the new 100ms, where the speed gains stop mattering, and the price war that's coming.

Breaking down the Hugging Face security incident caused by OpenAI's own models during a benchmark run - the sandbox escape, the package proxy, and whether it's really a marketing stunt.

GLM 5.2 is the first open weights model I'd call a genuine competitor to Opus and GPT for agentic work - at ~15-20% of the price. Part one of why AI inference margins are about to collapse.

xAI is renting huge amounts of GPU capacity to Anthropic and Google. Financial engineering ahead of the SpaceX IPO, a real compute shortage, or a genuine datacentre advantage? Probably all three.

Figma's reliance on non-designer seats made it uniquely exposed to AI. Claude Design's launch deepens the problem.