Agent best practices - grind mode and various hooks
A comprehensive guide to working with coding agents, from starting with plans to managing context, customizing workflows, and reviewing code.
AI Research
Summary
Factory Research evaluated context compression for AI agents using probe-based tests. They found structured summarization preserves more details than OpenAI or Anthropic methods during long sessions.
Highlights
- Traditional metrics like ROUGE fail to measure functional context preservation.
- Probe-based tests verify if agents recall specific details after compression.
- Structured summarization outperformed OpenAI and Anthropic in debugging tasks.
- Optimizing for tokens per task improves agent productivity over tokens per request.
- Testing covered debugging, code review, and ML research scenarios.
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Context
Audience
AI Engineers and Developers
DomainArtificial Intelligence
Formatlong-form article
Accessfree online
Topics
Related
Context CompressionAI AgentsStructured SummarizationOpenAIAnthropicEvaluation Frameworks