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A storefront whose WebMCP tools hand the agent a question instead of a guess — and that reads a whole sentence: budget, refusals and all.
A storefront whose WebMCP tools hand the agent a question instead of a guess.
A drop-in Transformer layer that is 2.28x faster across all 13 graded shapes while staying 1049x inside the tolerance gate — and runs the 100,000-token shape whose reference needs 20.5 TB and cannot.
Your agent says the run completed. The trace says which step actually failed. Glass Box middleware: a span waterfall per Agent Run, plus a policy gate that denies secret exfiltration.
An ML research agent that owns the whole loop — it forms the hypothesis, writes the code, trains, and grades itself. 23 experiments, zero human code, and it caught its own data leak before we did.
We stopped optimizing how the agent ranks and started optimizing when it knows enough to rank. 2.75 turns to converge, 0 LLM tokens, $0 per session, and +60 rank-1 hits on 800 unseen sessions.
