Build an AI code review bot in 30 minutes with Vercel Eve

Key takeaways

AI can significantly alleviate PR backlogs by automating the review of low-risk pull requests.
Building an AI-driven PR review bot can be straightforward using frameworks like Vercel Eve and Codex, relying mainly on instructions and simple prompts.
Risk scoring models considering factors such as blast radius, reversibility, data security, and operational impact can enable automated approvals while maintaining safety.
Auto-approving PRs can be compliant with SOC 2 and other frameworks if processes are transparent, auditable, and integrated into existing policies.
Automating routine reviews allows human engineers to focus on more complex and high-impact code changes, increasing overall development velocity.

Summary

The Challenge of Managing AI-Generated PRs

The host discusses the overwhelming influx of pull requests (PRs) generated by AI, emphasizing that anyone can code and push PRs directly to repositories, creating a queue that is difficult to manage. This problem is particularly acute for companies embracing AI in their development processes, necessitating smarter ways to handle PR reviews without overwhelming human resources.

Automating PR Review and Risk Scoring with AI

The core theme explores building an automated system to review, score, and approve low-risk PRs, thus freeing human reviewers to focus on more critical changes. Inspired by Intercom’s success with AI-approved PRs—which increasedSpeed, safety, and quality—the discussion details how AI can be integrated into review processes to enhance safety, reduce revert rates, and ensure compliance with frameworks like SOC 2 and HIPAA. The episode provides a step-by-step guide to creating an AI-driven PR review bot using Vercel’s Eve framework, Codex, and Chrome browser automations, emphasizing simplicity, transparency, and the importance of auditability.

Technical Deep Dive into Building the PR Bot

The episode offers a detailed technical walkthrough of building an AI-powered PR review agent. It covers choosing the Eve framework for ease of deployment, writing prompts for Codex to generate the review logic, and using Chrome browser automation to handle setup challenges. The process includes defining risk metrics like blast radius, reversibility, data security, and operational impact. The host demonstrates how the bot reads PR diffs, scores risk, and escalates or approves PRs automatically, emphasizing that such agents can be built with minimal code and effort.

Security, Compliance, and Operational Best Practices

The host clarifies that auto-approving low-risk PRs can be SOC 2 compliant if processes are auditable, queryable, and integrated into risk policies. The importance of escalation workflows, Slack integration for final approvals, and maintaining oversight is highlighted. The discussion stresses that AI tools should augment human reviewers rather than replace them entirely, ensuring compliance and security.

Live Demonstrations and Real-World Examples

Various live examples of the Merge Mommy PR bot in action are showcased, illustrating PR scoring, approval, or rejection based on risk assessments. The host shares how the bot handles different scenarios, such as documentation updates and major refactors, with some PRs auto-approved and others requiring human review. These demonstrations illustrate the practicality and effectiveness of the AI review system in real development workflows.

Show notes

AI writes most of my code now, and that created a new problem: a PR queue I couldn’t keep up with. In this episode, I walk through how I built Merge Mommy, a Vercel Eve agent that reads every PR after checks pass, scores it across six risk dimensions, auto-approves the low-risk ones, and pings me in Slack for anything that needs a human. I built the whole thing in one Codex session, it’s SOC 2 compatible, and it’s already cleared my backlog.

What you’ll learn:

Why AI-generated PRs create a review bottleneck and why the answer isn’t reviewing all of them
How Intercom 5x’d PR approval speed and reduced revert rates by putting AI in the review loop
Why Vercel Eve is the simplest framework I’ve found for deploying AI agents in Slack and GitHub
How I built a full PR review agent in Codex with one prompt and a few steering turns
The six components I use to score PR risk (blast radius, reversibility, data security, ops impact, verification gap, and change surface)
How I used Chrome browser use to handle Slack bot and GitHub app configuration so I never had to click through setup screens manually
Why auto-approved PRs can be SOC 2 compliant as long as the process is auditable, queryable, and in your risk policy
How to set up Slack escalation so low-risk PRs become a two-click merge with no manual review

—

Brought to you by:

WorkOS—Make your app Enterprise Ready today

—

In this episode, we cover:

(00:00) The PR review backlog problem nobody’s talking about

(02:35) Why you don’t have to review every AI-generated PR

(05:14) How Intercom built AI-approved PRs (and proved they’re safer)

(06:10) How the Eve framework works (directory, skills, channels, connectors)

(09:16) The Codex prompt I used to build the entire bot

(11:36) What the agent actually does: read, score, approve, or escalate

(13:07) Setting up your Eve agent