How AI Agents Search Their Memory
In my last video, I covered how AI agents store memory. But storing it is only half the problem. In this one, we dig into how agents retrieve the right memory at the right time.
I cover keyword search, semantic search, hybrid retrieval, and re-ranking, then dig into how OpenClaw implements all of it in practice using SQLite, BM25, and vector embeddings.
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Stop Giving Your Agent Every Tool
Large tool catalogs break agent context. Tool search fixes that by letting agents discover and load only what they need.
Stop Letting AI Agents Run the Whole Workflow
One inbox agent should not classify, research, score, route, and draft replies in one loose loop.
Harness Engineering: 4 Levers to Diagnose Any AI Agent
Most agent failures aren't model failures. They're harness failures. Here's the 4-lever framework I use to diagnose what broke.
Building Approval Gates AI Agents Can't Route Around
How to wire human-in-the-loop on tool calls — and why system prompt instructions like "always ask before sending" don't actually hold.
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