Anthropic's Fix: 2 Agents + 3 Files for Cross-Session Memory
sujingshen · x · 2026-07-03
Anthropic's solution to the Agent memory problem is surprisingly simple: an initialization Agent breaks down tasks (like cloning claude.ai) into a 200+ item feature list, each marked "failed". Every time the coding Agent starts, it reads three things—the feature list (what to do), a progress file (where it left off), and the git log (correctness). It then executes exactly one task, commits, updates progress, and passes the state to the next Agent. The entire flow relies on files, not memory, to transfer context.
More from coding & agent
- Resin lets an agent build standalone LLM inference engines; vLLM and SGLang optimize DeepSeek kernels differently — AccBalanced · 2026-10-27
- How I let my cloud Grok Bot code on my Mac mini via Tailscale, no public ports — talkaboutdesign · 2026-10-27
- Context layout is a cost decision: one memory edit can bust your entire agent prompt cache — dscape · 2026-10-27
- Alchemy adds effect/Workflow support across Durable Objects, Workflows and Lambda Durable Functions — samgoodwin89 · 2026-10-27
- Alchemy's Lambda Web Functions run plain Node web servers on Lambda, no OpenNext needed — samgoodwin89 · 2026-10-27
- Alchemy makes all ~2,850 AWS bindings work from any cloud, not just S3/Lambda/DynamoDB — samgoodwin89 · 2026-10-27