Engineering methodology that makes AI coding reliable
Wrought brings structured engineering methodology to AI-powered development — so you ship reliable software, not prompt experiments.
In active development · Built with Wrought
How It Works
Three pipelines, one methodology
Incidents & Bug Fixes
From incident to verified fix — structured methodology at every stage
Incident
Document the incident — classify severity, identify affected components, and capture the timeline.
Investigate
Form hypotheses, trace execution paths, and narrow down the failure domain through structured analysis.
RCA & Fix
Root cause analysis and fix design — examine code paths, state transitions, and edge cases.
Implement
Apply the fix — produce correct, tested code with built-in verification loops.
Review
Multi-agent code review — parallel analysis of correctness, performance, security, and architecture.
Incident
Document the incident — classify severity, identify affected components, and capture the timeline.
Investigate
Form hypotheses, trace execution paths, and narrow down the failure domain through structured analysis.
RCA & Fix
Root cause analysis and fix design — examine code paths, state transitions, and edge cases.
Implement
Apply the fix — produce correct, tested code with built-in verification loops.
Review
Multi-agent code review — parallel analysis of correctness, performance, security, and architecture.
Why Wrought
A better approach to AI engineering
The Problem
AI tools treat every task the same
- ✗ One model handles architecture, debugging, testing, and reviews — badly at some, expensively at all
- ✗ No methodology — just raw prompts with no structured engineering process
- ✗ You're the orchestrator, manually switching between tools and context
The Solution
Wrought brings structured methodology to every engineering task
- ✓ Structured methodology — each pipeline stage applies proven engineering practices for the task
- ✓ Structured methodology — reactive, proactive, and audit pipelines with proven engineering stages
- ✓ Guided orchestration — Wrought enforces methodology and suggests next steps, you make the engineering decisions
From the Blog
Building in public
88 Sessions. 201 Commits. Zero Users. What Building an AI Tool With AI Actually Taught Me.
88 sessions. 201 commits. Zero users. What building an AI tool with AI actually teaches about process, design, and distribution.
From Zero to Production: An Artemis II 3D Tracker Built in One Session
How the Wrought pipeline turned a live NASA mission into a production 3D web app — with every decision documented and every critical bug caught before deploy.
Building Wrought with Wrought: An Introduction
Why we're building an AI engineering methodology platform in public — and what it means for the future of software development.
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