What We Do

Senior engineering judgment. AI-speed execution.

Build Track

For founders and early-stage teams

You have domain expertise and a product vision. You need it built — production-grade, on your infrastructure, with documentation your team can pick up tomorrow.

Early Stage Builds

From vision to production in weeks, not months

One senior engineer with AI-first tooling delivers what traditionally takes a team of 4-6.

How it works:

  • Short discovery sprint (1-2 weeks) — workshops, problem framing, architecture
  • Build phase — working application, deployed to your AWS account
  • Full documentation and knowledge transfer included

You get: Product strategy, complete documentation, production infrastructure you own, and handoff-ready architecture.

Case study: GridPulse — 7 weeks, 1 engineer, 5 vertical features, production AWS. See how APES works.

Post-Build Retainer

Your product shipped. Now keep it moving.

Ongoing architecture support, feature development, and operational guidance after your initial build. The relationship deepens from delivery into partnership.

Includes:

  • Feature iterations and roadmap execution
  • Architecture reviews as you scale
  • Infrastructure optimization and cost management
  • Technical guidance for hiring your own team
Leadership Track

For growth-stage and enterprise teams

You have engineers. You need senior technical judgment — someone who's built production systems for 20 years and knows how AI changes the calculus.

AI & Technology Leadership

Fractional CTO + strategy advisory

Senior technical leadership without the full-time hire. Architecture decisions, AI strategy, vendor evaluation, hiring guidance, and the judgment to know what not to build.

Flexible entry points:

  • Fractional CTO — regular cadence, ongoing technical strategy
  • Project advisory — bounded engagement around a specific decision
  • AI strategy — practical roadmap for adopting AI across your engineering org

Background: 20 years building production systems at Bosch, US Department of Energy (PNNL), and high-growth startups. Engineering leadership across IoT, AI, supply chain, and energy.

AI Adoption for Teams

Process changes that stick

Your engineers are open to AI-assisted development but adoption is uneven. We embed AI-first practices into your existing workflows — not a workshop you forget next week, but process changes that stick.

What this looks like:

  • Assess current development workflow and identify high-leverage AI insertion points
  • Set up tooling, context architecture, and role-based AI workflows
  • Train your team on spec-driven AI development
  • Measure: cycle time, quality, developer experience

Based on: The APES framework — the same methodology behind GridPulse and active client engagements.

How We Work

You own everything

Source code, infrastructure, documentation, architecture. No vendor lock-in, no black boxes. Hand it to your team tomorrow.

Senior judgment, AI speed

One experienced engineer with AI-first tooling. You get the quality of a senior architect and the throughput of a small team.

Discovery before commitment

Every build engagement starts with paid discovery. We align on what to build, why it matters, and what success looks like — before writing code.

Production from day one

Real infrastructure, real deployment, real monitoring. Not a prototype that needs to be rebuilt. Your v1 is production-grade.

Not sure which track fits? Let's figure it out.

Most engagements start with a conversation. Tell me what you're working on and I'll tell you honestly whether I can help.

Get in touch

I respond personally within 24 hours.