My AI Coding Agent Is Brilliant Until the Bug Is in Production

说明与用途

AI 编码代理可以修复错误，但没有实时生产数据，它们效率低下。将生产会话数据集成后，代理可以快速定位并修复问题。

问题

AI coding agents can modify code based on repository knowledge, but they lack real‑time production context, leading to ineffective bug fixes.

结果

By feeding production evidence into AI agents, debugging becomes faster and more accurate, reducing manual detective work.

工作流

• 1. Production system detects a bug (e.g., checkout failure).
• 2. Session replay and logs capture user actions and errors.
• 3. HeronSignal aggregates evidence and presents it to the AI agent.
• 4. AI agent analyzes production data and repository code to identify root cause.
• 5. AI generates a fix and drafts a pull request.
• 6. Developer reviews the PR and decides whether to merge.

证据

The agent knows 40,000 lines of my codebase. It just doesn’t know what happened 30 seconds ago.

来源

Instead of treating production context as something only a developer reads, they’re making it available to the agent too.

来源

HeronAgent can go from the production interaction to the repository, investigate the relevant code, prepare a fix and open the PR.

来源