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THE INTEL LIBRARY
WebKit opposes WebMCP, Mozilla is neutral, one client ships. Use this surface-bet table to choose ARIA, WebMCP or both for each job your site lets agents do.
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PhotoCraft rebuilt Photoshop's menus in a week; its README says behaviour lags far behind. Audit what a clone of your product could copy and what it would lack.
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ChatGPT's Intelligent UI puts forms and buttons inside answers. Classify every rendered control, gate the ones that act, log them, re-run when defaults flip.
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Fast serving tiers turned coding agents into something you steer mid-sentence. Route each task to steer or hand off, and meter tool time before buying speed.
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When agent credits run out, what still works? Put a never-paywalled table on your AI agent pricing page, and run the lapse test before you sign for one.
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TypeSafe Jev belongs in a decision seat, not a reply seat. Sort fleet decisions with four tests, keep judges and compactors off it, and ship the table.
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Agent dashboard cards now mean four things: widgets, sub-agents, deliverables, threads. A dialect map of what each card is, what it can do, who owns the kill.
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Cursor Projects puts a fleet coordinator in the IDE. The ownership table: what it runs, what a local tray owns (stall flags, kill switch), and what breaks.
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AI agent security gates should act before each tool call: approve, prune, broker, revoke, and record. Use the matrix, vendor questions, and Tuesday drill.
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An AI agent coordinator copies its first mistake N times. The decision rule, a sixty-second self-test, and four brakes for sensitive or air-gapped work.
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What Databricks is, who owns it, and whether the lakehouse can own enterprise agents: the data-gravity thesis, the MCP counter-case, and a verdict by workload.
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Muse Spark is Meta's first proprietary model since Llama. What it is, what happens to Llama open source, and how teams standardized on it should hedge.
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Every OpenAI Dev Day decoded, 2023–2026: the agent primitives that survived, what the Assistants API sunset teaches, and what to build on without whiplash.
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DeepSeek collapsed the cost of running AI agents. We price one real workflow across three tiers — down to $0.14/M — and show you which steps to re-route.
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RL environments are the new training data. Why labs pay for agent gyms, who sells them, and how reward hacking and benchmark contamination could sour the rush.
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SWE-bench Verified is saturating — open models post 78–93%. What scores still predict, how vendors dress them up, and a checklist for reading agent benchmarks.
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Anthropic explained for builders: the founders, the safety strategy, Claude Fable 5 and Mythos 5, MCP, real critiques, and how to bet on the agent-first lab.
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AI subscription plans decoded for heavy users: Claude Max, ChatGPT Pro, Copilot's new AI credits, Chinese flat plans, and the math that picks your stack.
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Kimi K3, GLM-5.2, DeepSeek V4, and Qwen3-Coder-Next: a lab-by-lab guide to Chinese AI models for agent work, covering capability, licenses, access, and trust.
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