Eliminating Code Review: Overmind's Plan-First AI Engineering Shift

Dylan Ratcliffe, founder and CEO of Overmind, explains how his team removed human code review from most production changes and replaced it with reviewed execution plans plus AI-driven loops. He describes the bottlenecks that led to this decision, the concerns about team knowledge and compliance, and the internal experiments that reshaped engineering roles.

The talk covers:
■ Why code review was eliminated
- What peer review previously provided: bug detection, SOC 2 / ISO 27001 compliance, onboarding, and shared system understanding
- Why AI-generated code is difficult to review like human-authored code, and how AI responds to review comments

■ Redefining engineering work
- Moving from detailed specs to high-quality code toward handling ambiguity, constraints, and tradeoffs
- A one-page spec and 24-hour demo rule; engineers resolve ambiguity themselves rather than asking product

■ Plan-first until loops
- Human-reviewed execution plans before automated code generation
- Writer/reviewer AI loop iterates until implementation matches the approved plan
- Peer review shifts before the loop; plans are easier and cheaper to reject than pull requests

■ Implementation, metrics, and tradeoffs
- Internal MCP-based tool with no UI for plan sharing and review
- Three-week comparison: more issues completed, more deploys, shorter lead time, and less context switching
- Rejecting a plan adds about 40 minutes; rejecting a pull request adds about 16 hours
- Compliance through pre-approved changes and sampling instead of line-by-line review
- “How” decisions still matter, and engineers should keep making them
- About 8% of planned work is abandoned after planning, which the speaker presents as a positive option
- The internal add-on is published at until.dev

The talk is aimed at engineering leaders, senior engineers, and product managers exploring AI-assisted development and review workflows. Viewers gain a framework for moving peer review earlier, clarifying which decisions should remain human, and measuring the impact of loop-based automation. It also points to the published until.dev add-on for those who want to examine the internal approach.