Let's work together.
From hourly consulting to standing your whole team up on Claude Code. Or skip the menu and brief Iris.
Consulting
Senior advice, on demand.
- Architecture review
- AI & tech strategy
- A senior second opinion
Build a project
End-to-end ownership of a shipped system.
- Production system
- Infra as code, deployed
- Docs + handoff
Embedded engineering
Senior firepower inside your team.
- Hands-on building
- Architecture + reviews
- Standards & mentorship
Fractional CTO
Senior judgment on a cadence.
- Weekly calls
- Technical reviews
- Hiring & roadmap input
Custom CRM
A CRM written for how your business actually runs — not a generic sales pipeline.
- Data model from how the day actually goes
- The modules the team already uses — rebuilt, not replaced with a funnel
- Live in production, with docs and a handoff
- Reusable where it earns it — branding as config, not a fork
Off-the-shelf CRMs fit generic teams. These were written for how the business already ran — see the custom CRM practice.
Claude Code for your team
I stand your business up on a real development setup — Claude Code, Cursor, and GitHub — then teach your team to build and ship their own internal tools.
- Your team set up on Claude Code, Cursor & GitHub
- A real repo, version control, and a deploy pipeline
- Hands-on coaching — your people writing and shipping code
- Your first internal tool or web app, built and deployed together
It's how I took the MyCareClub founding team from zero to writing and deploying their own web apps — a real development team, not a vendor they have to keep calling.
The whole stack, end to end — the data model, the infrastructure, the agents, and the product they live in.
AI agents & automation
Agents that do real work — planning the steps, calling your tools, and acting on what comes back — to take repetitive, multi-step jobs off your team's plate.
RAG & knowledge systems
A private assistant grounded in your own material: it finds the right document, policy, or record before it answers, so replies are backed by your data instead of guesses.
AI infrastructure
The plumbing that keeps AI alive in production — deployed as code, observable, and built to hold up under real traffic, where downtime and wrong answers cost real money.
AI-native products
AI designed into the product, not bolted on afterward — shipped as features people genuinely use and judged on outcomes, not demo-day applause.
Evaluation & testing
Tests and scoring for systems that don't have one right answer — so you can prove an LLM feature works, catch it the moment it drifts, and ship changes without crossing your fingers.
AI strategy
An honest read on where AI earns its keep and where it's just a distraction — then a plan to get there: what to build, what to buy, and how to get it into production.
A conversation, a short written proposal, then go or no-go. No long sales cycle, no decks.
Brief Iris
Tell the site's AI what you're building; she maps it to past work.
Intro call
30 minutes with Chris to firm up scope and fit.
Proposal
A short written proposal — outcomes, milestones, fees.
Kickoff
Work begins, with Chris hands-on from day one.