<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>tech4talk</title><description>Proof-first technical writing on local AI and systems engineering.</description><link>https://tech4talk.com/</link><item><title>Simulation First, Then Go Live: I Built a Bench That Proves an AI Harness Before It Touches Real Data</title><link>https://tech4talk.com/blog/local-ai/the-same-harness-live/</link><guid isPermaLink="true">https://tech4talk.com/blog/local-ai/the-same-harness-live/</guid><description>Building a local, privacy-first agent taught me one discipline worth writing down: never let an AI harness meet real data until its declared invariants have been verified — reproducibly, in simulation, where every tool and inbox is a safe scripted stand-in. I built Harness Lab to make that discipline mechanical: prove the harness in simulation first, then go live by rebinding one tool. This post is the method, the five rules the bench enforces, and the proof — my agent&apos;s email path run both ways, the two traces the same shape event for event, differing exactly where going live must differ. Updated 2026-07-15: the bench is now open source, and the proof is now one command.</description><pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate></item><item><title>The Spine, Drawn: I Made My Agent&apos;s Governance a Graph You Can Sweep — and Can&apos;t Bypass</title><link>https://tech4talk.com/blog/local-ai/the-spine-drawn/</link><guid isPermaLink="true">https://tech4talk.com/blog/local-ai/the-spine-drawn/</guid><description>Last post I argued the harness is a deterministic spine and the guards, not the model-judges, hold the line. This one earns the next claim: I rebuilt that spine as an explicit graph on a bench, swept every governance knob, and watched the safety line appear as a number. When governance is topology instead of an aspect, the bypass isn&apos;t a test you keep passing — it&apos;s an edge that doesn&apos;t exist.</description><pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate></item><item><title>The Harness Has a Spine: Why Deterministic-First Beats Pure Agentic for Local AI</title><link>https://tech4talk.com/blog/local-ai/the-harness-has-a-spine/</link><guid isPermaLink="true">https://tech4talk.com/blog/local-ai/the-harness-has-a-spine/</guid><description>Two experiment campaigns on a local, privacy-first agent — a tuning-lever sweep and a judges-on red-team. Both times, reliability and safety came from the deterministic scaffolding, not the model or the knobs around it. For local agents, the leverage is a harness with a spine.</description><pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Local AI Agents in 2026: The Model Isn&apos;t the Bottleneck, the Harness Is</title><link>https://tech4talk.com/blog/local-ai/harness-not-the-model/</link><guid isPermaLink="true">https://tech4talk.com/blog/local-ai/harness-not-the-model/</guid><description>An eagle-eye view from three experiments on local open-weight models, run on an Apple-Silicon laptop with MLX. The model on your machine is already good enough for most real work; what decides whether it works is the engineering around it — and every failure I found was a locatable, fixable harness problem, not a model limit.</description><pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate></item><item><title>The Buffer-Size Cliff: The One Setting That Stops Your Local AI Agent Hallucinating</title><link>https://tech4talk.com/blog/local-ai/hallucination-cliff/</link><guid isPermaLink="true">https://tech4talk.com/blog/local-ai/hallucination-cliff/</guid><description>A sharp quality cliff at buffer_size ≈ 0.5 × prompt_tokens makes local AI agents stop calling their tools and start hallucinating — measured on six open-weight instruct models on Apple Silicon.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate></item></channel></rss>