You can build with AI now. The hard part is shipping.

Most teams know tools like Codex, Claude Code, and Cursor can move faster, but they don't have time to learn the workflow, review every output, and turn prototypes into production-ready code.

I act as your AI Build Partner: scoping, building, testing, shipping, and documenting the result so your team can use it.

Tell Me What You Want to Build
Your IdeaAI ToolchainShipped BuildScope + prioritiesClear user workflowSuccess criteriaCodexClaude CodeCursorTesting + ReviewWorking MVP or toolClean code + docsDeployed + handoff

What I can build quickly

Internal ops tools

Dashboards, admin panels, and workflows that remove repetitive manual work from your team.

MVPs and feature prototypes

Validate an idea fast with a working product your users can test, instead of a slide deck.

Reporting and monitoring apps

Pull data from multiple APIs and systems into one place with alerts and scheduled summaries.

AI-assisted content systems

Research, drafting, formatting, and publishing pipelines with human checkpoints built in.

Workflow integrations

Connect your existing tools using APIs, webhooks, and automation platforms where needed.

Cleanup and rescue

Unstick half-built AI coding projects and get them to a stable, maintainable handoff state.

Tools I use

CodexClaude CodeCursorGitHub CopilotVercelNode.js / TypeScriptPython

I choose tooling based on fit, not hype. The goal is a shipped, maintainable result, not a flashy demo.

Quality guardrails

  • Clear scope and acceptance criteria before coding starts
  • Human review for architecture, security, and edge cases
  • Testing and bug-fix pass before handoff
  • Documentation and optional maintenance after launch

How an AI build sprint works

1

Scope

We define what gets built, what success looks like, and what can wait for phase two.

2

Build

I use AI coding workflows to move fast, with checkpoints for architecture and usability.

3

Test + Ship

I run QA, fix issues, and deploy to your environment with a rollback path.

4

Handoff

You get clean code, docs, and a walkthrough. Ongoing support is optional.

Engagement options

Start small or go end-to-end. Most projects begin with a sprint, then move into a full build or monthly iteration cycle.

1 Week

Sprint

Clarifying scope and shipping one high-impact feature quickly.

  • Kickoff and technical game plan
  • One prioritized workflow or feature
  • Working demo plus next-step roadmap
Start with a Sprint

2-6 Weeks

Build

Launching a new internal tool, MVP, or complex AI-enabled workflow.

  • End-to-end implementation and QA
  • Deployment with rollback-safe release plan
  • Documentation and handoff walkthrough
Plan a Build

Monthly

Ongoing

Teams that want continuous shipping without hiring full-time.

  • Backlog-driven feature sprints
  • Monitoring, fixes, and improvements
  • Regular updates and planning support
Discuss Ongoing Support

Questions

How is pricing structured?

Most work fits one of three models: a focused sprint, a scoped build, or ongoing monthly support. I'll recommend the best fit after understanding your workflow and timeline.

Is this only for technical teams?

No. Many projects start with founders or operators who know the workflow problem but do not have engineering bandwidth.

How long does a project take?

Small scoped builds are often done in 1-3 weeks. Larger builds are split into phases so you see progress early.

Do we own the code and accounts?

Yes. You own the repositories, infrastructure, and tool accounts. I document setup and handoff so you are never locked in.

Can this include WordPress or automation work too?

Yes. Many projects combine all three service areas: WordPress, automation, and custom AI-assisted software builds.

Have an idea you want built fast?

Send the workflow you want to improve. I'll tell you what to build first and what it would take to ship.

Start an AI Build Project