I Built an AI Code Review Agent That Remembers Every Developer's Mistakes

Sharadha R — Thu, 21 May 2026 16:51:20 +0000

The Problem

Every code review starts from scratch. A developer makes the same SQL injection mistake twice — the reviewer has no memory of the first time.

What if your code reviewer actually remembered?

What I Built

A Code Review Agent that:

Reviews GitHub PRs automatically
Remembers each developer's past mistakes
Gets more personalized with every review
Routes simple PRs to fast models, complex PRs to powerful ones

How It Works

Review #1 — Alex submits a PR with a SQL injection bug. Agent reviews it and saves: "Alex tends to write unsafe SQL queries."

Review #2 — Alex submits another PR. Agent recalls the history and immediately flags SQL patterns — personalized feedback.

Tech Stack

Groq — Free LLM API (llama-3.1-8b + llama-3.3-70b)
Python — Core language
PyGithub — Fetch real GitHub PRs
Rich — Beautiful terminal output

Key Code — Memory System

def save_developer_memory(developer, review_summary):
    if developer not in developer_memory:
        developer_memory[developer] = []
    developer_memory[developer].append(review_summary)

def recall_developer_history(developer):
    memories = developer_memory[developer]
    return "\n".join([f"- {m}" for m in memories])

Smart Model Routing

Simple PRs (under 100 lines) → fast cheap model
Complex PRs → powerful model

Saves cost without losing quality.

GitHub Repo

https://github.com/sharadha26052006-eng/code-review-agent

What I Learned

Memory transforms a generic AI tool into a personalized assistant. Even a simple dictionary-based memory makes a huge difference in output quality.

DEV Community: Sharadha R

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