It is hardly to imagine daily software engineering work without AI, but issues like babysitting, losing context, and hallucinating can ruin the experience. It often feels faster to just do it yourself rather than carefully cooking prompts for an agent that seems to forget the project structure halfway through.
Anthropic’s recent insights on long-running agents offer a glimpse into this future - pattern that might solve this: treating AI agents like engineers working in shifts. Instead of trying to maintain one massive context window, the agent is forced to act like a fresh developer coming on duty—reading git logs, checking a persistent progress.txt, and validating the current state before writing any code.
The idea of separating an "Initializer Agent" (who defines the tasks) from "Coding Agents" (who execute them using external memory) feels like the missing link between a cool demo and a truly autonomous tool.
https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents
Research text:
https://lnkd.in/d_PHhs3W
Framework examples:
https://lnkd.in/dC7ZXXNG
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