Deep-dive guides on AI agents, agent orchestration, MCP, and developer tooling.
3 posts found
AI coding assistants aren't one architecture — they're three separable design decisions (how context gets assembled, how edits get applied, how execution gets contained) that every tool from Claude Code to Cursor answers differently.
Long-running agents rarely fail because they run out of context window — they fail because nobody designed what happens to attention quality once the transcript outgrows what the model can usefully weigh. Here is how tiered compaction, tool-output pruning, and sub-agent isolation actually work.
Vector similarity search answers what text is topically related — but long-running agents need to know what is true right now. Conflating the two is why agents keep resurrecting overturned decisions.