This is How I Automated My GitHub PRs with AI Agents & Agentic Workflows!

Based on the article, here are key points about how to automate GitHub pull request (PR) reviews using AI agents and a developer platform like Port.io:

1. The goal is to provide automated PR review comments that summarize context and flag potential risks for human reviewers.

2. Key components:

• Connect your Git repo with a developer platform
• Gather relevant metadata about the service being modified
• Call an AI agent/Large Language Model (LLM) with structured input data
• Post back a concise, actionable comment to the PR

1. Steps:

• Authenticate and fetch related entities from the dev platform API
• Build a prompt for the LLM including ownership info, readiness status, deployment context etc.
• Call the AI agent and get a JSON response
• Parse the output and post a human-readable comment back to GitHub
• Update metadata fields in the developer platform

1. Important considerations:

• Use structured prompts and outputs rather than freeform text
• Don't rely solely on code diff - need full context from dev platform
• Have an always-on webhook server for reliability
• Treat AI output as decision support, not final approval
• Ensure data quality in your metadata catalog

1. Benefits:

• Faster PR reviews with

Read the full article at DEV Community

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