
Quality Over Velocity: The Case for Slow AI Coding
AI coding should be used as a tool for methodical, high-quality engineering rather than just a 'slop cannon' for fast output.
Practices, tools, and processes for reviewing code, including peer review, automated review, and AI-assisted code review workflows.

AI coding should be used as a tool for methodical, high-quality engineering rather than just a 'slop cannon' for fast output.
AI models tend to unnecessarily rewrite code when fixing bugs, but this 'over-editing' can be solved through targeted prompting and Reinforcement Learning.
GitHub Stacked PRs provide a native CLI and UI workflow to manage and review large changes as a sequence of small, interdependent pull requests.

AI is creating a supervision tax that forces senior engineers to process machine-speed output at biological-speed capacity, leading to systemic burnout and a collapse in software quality.

AI-assisted coding requires active human oversight and iterative conceptual guidance to prevent the messy, redundant outcomes of 'vibe coding.'

ProofShot is an agent-agnostic tool that enables AI coding assistants to autonomously record, verify, and document their web development tasks.

AI-generated code can be safely used without human review if it is validated through a rigorous suite of automated verification tests and constraints.

To manage the flood of AI-generated code, developers must define clear acceptance criteria upfront and use automated tools to verify behavior instead of manually reviewing diffs.
A technical protocol for maintainers to identify, reject, and penalize low-effort AI-generated contributions to software projects.

Build the independent auditor and automate the review loop so code validation can run itself.

Rapidly shipping unread LLM-generated code creates a mounting comprehension debt that will slow teams down when real changes are needed.

Make AI work in big, messy repos by compacting context and reviewing specs, not just code: research → plan → implement, with humans focused upstream.

OpenAI’s GPT‑5-Codex is a tooling-first, code-focused upgrade that boosts review and refactoring while the API and polish catch up.

Define problems clearly, automate verification, and review thoroughly so AI can build in the background while you focus on higher-leverage engineering work.
Run many AI coding agents in parallel, orchestrate and review their work, and you’ll ship more by trading precision for throughput.