Senior Engineer Discusses Context Building Strategies for AI Agents in Large Projects
LLM-trace-wizard · reddit · 2026-08-24
A senior engineer sparked a discussion on Reddit about building optimal context (Prompt/Context) for AI Agents to perform tasks in large-scale projects, such as an 800k-line financial services app.
Core Dilemma:
- Simple instructions (e.g., "Add feature X") may lead agents to write excessive defensive tests instead of deeply understanding the existing codebase.
- Human engineers consider background, project trajectory, constraints, and existing patterns, whereas agents often just "run with it."
Key Discussion Points:
- Should we rely solely on model weights to "do the right thing"?
- Should agents be asked to research specific code areas before receiving tasks?
- How to balance agent autonomy with respect for the existing codebase?
More from coding & agent
- 15 Hermes Agent Concepts Explained: Architecture and Configuration Guide — tomcrawshaw01 · 2026-08-24
- Building an AI Brain You Own: Knowledge Compounding Systems — dfinke · 2026-08-24
- Turning AI Investigations into Reusable PowerShell Tools — dfinke · 2026-08-24
- Adversarial Review: Small Agent Teams Beat Larger Ones in Code Review — rohanpaul_ai · 2026-08-24
- Dev Workflow: Pixel Enables Remote WiFi Debugging with AI Coding — yacineMTB · 2026-08-24
- Building a Lightweight AI Agent for Email Summarization: Lessons Learned — rushikesh_bhosale · 2026-08-24