A Pending Approval Made My Release Gate Skip Its Install Audit
A pending approval put an entry in the error list, and one guard clause then skipped my installer's real install audit. The gap serialized as an empty object. Here is the fix.
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A pending approval put an entry in the error list, and one guard clause then skipped my installer's real install audit. The gap serialized as an empty object. Here is the fix.
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A builder-in-public field note on wiring ChatGPT and Gemini as tool-connected workers in a real browser tab — why Gemini complied, why the ChatGPT account refused, and why framing decides everything.
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An AI agent can pass every eval and still take an action it was never allowed to take. Permission drift is a control-plane failure, not a model failure. Here is the fix.
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A builder-in-public story about replacing tool-reported success with independent live-page, archive, image, and signature proof in Skynet.
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A Skynet Blog field note on why directed AI video belongs in the operating record, how Platform differs, and how audio-video proof gates work.
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Why a smarter LLM will not fix an AI system that fails at orchestration and verification: reliability comes from the weakest coordination layer, not the model.
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A 2026 field note on why multi-agent AI fleets fail at the control plane, and how live probes, decoupled agents, fallback chains, and independent monitors keep capability alive.
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A transparent Codex credit estimate for producing one Platform post and one Blog post, with official OpenAI rate-card inputs and clear limits.
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A source-backed reflection on Skynet, anti-drift AI orchestration, provider routing, TODO memory, CDP proof, and execution speed.
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Published: March 18, 2026 • Part of the Philippine Food Price Prediction series This post documents the upgraded system as deployed on March 18, 2026. Engineering validation companion This Blog page documents the March 18, 2026 system upgrade, test coverage, implementation architecture, alert pipeline,
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I wanted to know whether two decades of Philippine food-price data could produce a forecast that survives a real holdout period, not just a clean training score. I trained the Random Forest on 2000-2019 data and held out 2020-2023. It reached R² 0.91, MAE
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