A working software prototype
You leave the workshop with a real repo, not a slide deck — a useful workflow built in your stack and ready to extend on Monday.
A practical workshop for turning ideas into functioning software with Codex, Claude Code, Pail, and disciplined engineering habits. Start with the fun part, then make it real with TDD, architecture decisions, hardening, and a deploy path your team can repeat.

You leave the workshop with a real repo, not a slide deck — a useful workflow built in your stack and ready to extend on Monday.
Codex, Claude Code, and Pail together — with the prompt patterns, review loop, and test seams that keep the build honest.
A grounded picture of what it actually takes to turn a fun prototype into something reliable — testing, deploy, ownership, hardening.

You have an idea, a Notion doc, maybe a Figma. You can write, you can think in systems, and you want to ship a working version without hiring a team yet.

You ship software for a living and you're tired of AI demos. You want a delivery loop with agents that respects tests, types, and the production bar you already hold.

Your team is adopting AI coding agents and the rollout is uneven. You want a shared playbook — prompts, review habits, deploy story — that engineers, leads, and reviewers can use.
Three formats. Same delivery loop. Public cohorts ship publicly; private team sessions adapt to your repo, your conventions, your constraints.

A focused first taste of vibe coding with engineering discipline. We pair on a scoped feature, get green tests, and leave with a clear sense of the loop.

Idea to small working product. We move fast with Codex and Claude Code, then slow down for TDD, architecture decisions, and a deploy path you can keep.

Run it on a real codebase your team owns. We adopt your conventions, sharpen the agent loop against them, and leave behind documented patterns.
Anchored on the full-day intensive. Intros compress this shape; private team sessions adapt to the host repo.
Every attendee leaves with the same toolkit I use on client engagements — built around Pail, the dev-utility suite we use during the workshop.
Every attendee leaves with a year of Pail — the dev-utility suite we use during the workshop and the daily driver for AI-assisted building.
The same scaffolds I use on real client work: a starter repo, a prompt library, and the conventions that keep an agent loop coherent.
Debugging, launch, and demo-to-production checklists — the small lists that catch the issues that always bite right before a release.
A 60-minute follow-up window once attendees have a few weeks of building behind them — review the repo, unstick the loop, plan the next slice.
Workshop alumni who later book a Discovery Sprint or Build Sprint get a credit toward the engagement — the workshop seat counts.
No. The prompt work is the entry point. The workshop moves quickly into test seams, data boundaries, review loops, and deploy decisions.
Public cohorts start from a blank repo with a small starter template. Private team sessions work best when we bring one real workflow from your stack.
Comfortable editing code and using Git. The workshop is practical for non-technical builders who can read code, founders who code, and engineers learning agentic delivery.
A working repo, a small test suite, notes on the architecture decisions, a deploy path, the prompt + project templates, and a Pail workspace your team can keep.
Tell me which format fits, the audience segment you're in, your location preference, and what you want to build. I'll follow up with the next available dates.