Overview
Everyone’s using AI to code, but most teams are “vibe coding” their way into production—throwing prompts at ChatGPT and hoping for the best. The result? Hallucinations, broken deployments, and the same bugs creeping in over and over. There’s a better way.
As a fractional CTO who bridges design and development teams, Martin Laws has discovered that the secret to production-ready AI isn’t better prompts—it’s systematic frameworks that teach AI to build YOUR way, not the generic way it was trained. Through cursorrules files, project templates, and self-correcting workflows, teams can transform AI from an unpredictable tool into a reliable production partner. Martin will show you the exact systems that eliminate “garbage in, garbage out” and unlock AI’s true potential for shipping real products.
Objective
Transform your AI development workflow from chaotic prompting to systematic, production-ready processes that consistently deliver quality results.
Five Things Audience Members Will Learn
- Why your AI outputs are inconsistent (hint: it’s not AI’s fault) and the mindset shift that changes everything
- How to create “lint rules for AI” using cursorrules files that eliminate recurring bugs and ensure consistent code style
- Template systems that capture your project’s architecture, style guide, and constraints so AI builds exactly how you want
- Building self-correcting AI workflows with proper tooling (TypeScript, linting, tests) that catch mistakes automatically
- The future opportunity: how design-to-dev handoffs could include AI-readable style guides and design systems
Target Audience
Front-end developers, designers, and creative technologists who want to move beyond experimental AI usage to reliable, production-ready workflows.