Beyond Prompting: A 5-Layer Debugging Framework for AI Agents
mehdiweb · reddit · 2026-08-01
The author argues that improving AI agent performance relies on refining the surrounding system architecture, not just endlessly tweaking prompts. When an agent forgets, repeats work, or falsely claims completion, debugging should occur across five layers:
- Prompt: Are the instructions clear?
- Context: Does it have the right information?
- Harness: Are tools, permissions, and state handled properly?
- Loop: What happens when the first attempt fails?
- Graph: Does the task genuinely require multiple roles or approvals?
The most effective practice is defining "done" before the agent starts: setting a specific goal, clarifying verifiable outcomes, providing tests or schemas, and setting stop conditions (e.g., verification passed or attempt limit reached). Additionally, do not let the same agent create and approve its own work; introducing a fresh reviewer agent or deterministic check is usually more effective than adding more prompt instructions. System design should start with a single task and a reliable check, only introducing loops or multi-agent collaboration when strictly necessary.
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