The latest articles on DEV Community by Sai Rathod (@sia2008). https://dev.to/sia2008 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4100227%2Fbd03de81-54a2-4aed-80e2-3c55435b615c.png https://dev.to/sia2008 en Sai Rathod Sat, 29 Aug 2026 12:25:12 +0000 https://dev.to/sia2008/building-an-ai-auto-patch-agent-with-trueforge-and-qodo-3b36 https://dev.to/sia2008/building-an-ai-auto-patch-agent-with-trueforge-and-qodo-3b36 <h1> Building Auto-Patch Agent: From Production Incident to Reviewed Code Fix </h1> <p>Production incidents require investigation, debugging, code changes, review, and deployment. I built Auto-Patch Agent to automate this workflow while keeping the code change reviewable.</p> <h2> What does Auto-Patch Agent do? </h2> <p>Auto-Patch Agent is an AI-powered incident response agent.</p> <p>Given a production failure such as an HTTP 500 error, the agent:</p> <ol> <li>Investigates the repository</li> <li>Finds the root cause</li> <li>Proposes a targeted fix</li> <li>Creates a GitHub Pull Request</li> <li>Gets the change reviewed by Qodo</li> <li>Merges the fix after review</li> </ol> <h2> The Demo </h2> <p>I created a vulnerable Node.js order service for the demonstration.</p> <p>An invalid customer ID caused the customer lookup to return undefined. The application then tried to access customer.id, resulting in an HTTP 500 error.</p> <p>The agent investigated the repository and identified the failure path.</p> <p>It then added validation and improved the error handling so an invalid customer request is handled properly instead of causing an unexpected server error.</p> <p>The change was committed to a separate branch and submitted as a Pull Request.</p> <h2> How I Used TrueForge </h2> <p>TrueForge is the runtime and orchestration layer for the agent.</p> <p>I used TrueForge to:</p> <ul> <li>Run the AI agent</li> <li>Connect Gemini as the model</li> <li>Connect development and repository tools</li> <li>Handle agent tool calls</li> <li>Give the agent access to the project for investigation</li> </ul> <p>This makes the project more than an LLM generating code. The agent interacts with the development workflow.</p> <h2> How I Used Qodo </h2> <p>Qodo provides an independent code review layer.</p> <p>After the fix was submitted as a Pull Request, Qodo reviewed the changes for bugs and code quality issues.</p> <p>The review helped validate the remediation before merging.</p> <p>The final review reported 0 bugs found, and the Pull Request was merged into main.</p> <h2> Workflow </h2> <p>Incident<br> ↓<br> Repository Investigation<br> ↓<br> Root Cause<br> ↓<br> Targeted Fix<br> ↓<br> GitHub Pull Request<br> ↓<br> Qodo Review<br> ↓<br> 0 Bugs Found<br> ↓<br> Merge</p> <h2> Tech Stack </h2> <ul> <li>TrueForge</li> <li>Gemini</li> <li>GitHub</li> <li>GitHub MCP</li> <li>Qodo</li> <li>Node.js</li> <li>Express.js</li> </ul> <h2> Why I Built It </h2> <p>The goal was to connect an AI model to a real engineering workflow.</p> <p>Instead of only asking AI for a code suggestion, Auto-Patch Agent investigates the repository, creates a targeted remediation, submits it through GitHub, and gets the change independently reviewed by Qodo.</p> <p>The final merge remains controlled and reviewable.</p> <p>This project shows how AI agents can assist with practical incident response and software maintenance.</p> wemakedevs trueforge ai devops