Forge

The Challenge

After shipping five client products, a pattern emerged: the first week of every project involved the same scaffolding work — Next.js setup, authentication integration, database configuration, CI/CD pipeline, testing framework, and deployment. This repetitive work consumed 25-30% of every project timeline. We needed an internal tool that could go from a product idea to a working, deployable scaffold in hours instead of days, while encoding all the architectural decisions and patterns proven across previous projects.

Discovery Phase

We audited every project we had shipped and identified 47 common patterns: authentication flows, database schemas, API route structures, component architectures, testing configurations, and deployment pipelines. We categorized these into must-have (present in every project), common (present in 80%+), and optional (project-specific). This taxonomy became the decision tree that Forge uses to generate project scaffolds.

Our Solution

Forge is a multi-phase autonomous system. Phase 1 (Deep Discovery) asks targeted questions about the project scope, target users, and business model. Phase 2 (Smart Stack Selection) recommends a technology stack based on requirements, using decision rules derived from our production experience. Phase 3 (Autonomous Team Build) spawns specialized AI agents that build the scaffold in parallel — one handles authentication, another builds the database layer, another sets up CI/CD. Phase 4 (Auto QA) runs MANIAC against the generated scaffold to catch issues before the first human review.

Architecture

Forge operates as an orchestrator that coordinates multiple specialized AI agents. Each agent has a defined scope (auth, database, UI, testing, deployment) and works in an isolated git worktree to prevent conflicts. The orchestrator merges completed work, resolves conflicts, and runs integration tests. The entire process is checkpointed, so if any phase fails, it can resume from the last successful state.