agent-project-developmentlisted

# Project Development Methodology Principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. Applies whether building a batch processing pipeline, a multi-agent research system, or an interactive agent application. ## When to Activate - Starting a new project that might benefit from LLM processing - Evaluating whether a task is well-suited for agents versus traditional code - Designing the architecture for an LLM-powered application - Planning a batch processing pipeline with structured outputs - Choosing between single-agent and multi-agent approaches - Estimating costs and timelines for LLM-heavy projects ## Decision Tree: Task-Model Fit ``` Should you use LLM processing for this task? +-- Does it require synthesis across sources? --> Likely YES +-- Does it involve subjective judgment with rubrics? --> Likely YES +-- Is natural language the desired output? --> Likely YES +-- Is there tolerance for individual errors? --> Likely YES +-- Is the domain knowledge in the model's training? --> Likely YES | +-- Does it require precise computation? --> Likely NO (use traditional code) +-- Does it need real-time sub-second responses? --> Likely NO +-- Does it require perfect accuracy? --> Likely NO (hallucination risk) +-- Does it depend on proprietary data the model lacks? --> Likely NO +-- Must same input produce identical output? --> Likely NO | +-- Mixed? --> Manual prototype f