Methodical, and deliberately boring
Four phases, each ending with something you can use. The structure exists to reduce your risk: you see working software early, budgets are set before builds, and nothing depends on trust alone.
Discover
Audit the current workflow. Map data, decisions, and edge cases. Identify the highest-leverage automation surface — scored by effort and payoff, so we fix the most expensive problem first.
→ Deliverable: A prioritized automation roadmap
- Interviews with the people who actually do the work — not just leadership
- One real lead or job traced end-to-end through your systems
- A re-typing and silent-failure inventory across your tools
- Findings ranked by weekly cost, so priorities are economic, not vibes
Architect
Pick models, tools, and infrastructure. Draft eval criteria for anything AI-driven. Define cost and latency budgets up front, so there are no invoice surprises later.
→ Deliverable: A build plan with budgets
- Tool and model selection with the trade-offs written down
- Eval criteria defined for anything AI-driven — before it is built
- Cost and latency budgets set up front, so there are no invoice surprises
- A build plan your own team could execute if you stopped here
Build
Ship a thin slice end-to-end first, then iterate with real data. You see progress weekly, not at a big reveal. Claude Code does most of the typing; judgment stays human.
→ Deliverable: A working system on real data
- A thin slice live in week one or two — real data, real workflow
- Weekly demos of working software, not status decks
- You and your team try the system while it is still cheap to change
- Scope adjustments happen mid-build, based on what real usage shows
Harden
Eval suite, observability, error handling, and fallbacks. Documentation your team can operate from, training for the operator, and an optional retainer so the system keeps an owner.
→ Deliverable: A documented, monitored system
- Error handling, retries, and alerting on every critical path
- An eval suite and monitoring so quality is a number, not a feeling
- Documentation and training for whoever operates the system
- Optional retainer so the system keeps an owner after launch
See the process in the outcomes
Every case study documents its implementation path — audit weeks, thin slices, eval suites, and handoffs. The process isn't marketing; it's visible in the work.
See if this fits
A first call covers your bottleneck, whether this process suits it, and what phase one would look like.
30 minutes · no pitch deck · reply within 24h if you write instead