How we ship AI solutions.
Three phases — Audit, Build, Run. Every productized solution and every Custom engagement runs the same loop. The phases are not a waterfall; they’re a cadence we re-enter every quarter for as long as the system is in production.
Phase 01 · 1 week
Audit
A senior engineer maps a workflow (or a stack decision) and tells you what to build — or whether to build at all.
- Workflow walkthrough — we observe the work, we don’t ask the team to describe it.
- Ranked list of automation candidates by impact, effort, and risk.
- Build-vs-buy recommendation per candidate, with the reasoning shown.
- Honest answer on which tier (Starter, Pro, or Custom) fits — sometimes it’s “none, do this manually for another quarter.”
What you leave with: Audit report (PDF) + 30-min walkthrough + 30-day roadmap. $99 if it’s the standalone AI Workflow Audit; included in every Pro and Custom engagement.
Phase 02 · 2–6 weeks
Build
We ship the actual production system. Code in your repo (or our hosted infra), eval suite gating every prompt change, monitoring on day one.
- Prompts in version control with diffable PRs — no admin-panel pasting.
- Eval harness designed before the first prompt is shipped, not after the first regression.
- Cost guardrails and rollback plan written at design time — the kill switch exists before the system is live.
- Pair-implementation with your team if they’ll inherit it. Zero handoff if they won’t.
What you leave with: Deployed system (your infra or ours), eval suite, monitoring dashboard, runbook. Tier-priced: Starter solutions ship in 3–7 business days; Pro in 3–6 weeks; Custom builds run 3–9 months.
Phase 03 · Ongoing
Run
Pro and Custom solutions get a Run phase: monitoring, weekly iteration, on-call. The reason a six-month-old eval suite still passes is because someone is paid to keep it passing.
- Drift alerts when accuracy degrades — before a customer notices.
- Cost-per-call dashboards with hard token budgets and per-tenant rate limits.
- Weekly iteration cadence with a senior engineer — new few-shots, prompt tweaks, model swaps when the price/perf math changes.
- On-call rotation on Custom engagements; 24-hour SLA on Pro tier.
What you leave with: A working system that stays working. Monthly health report. Quarterly review of model + cost + accuracy trends.
Operating principles
Audit / Build / Run is the how. These are the why.
Pace, not speed
Productization IS our pace. We’re not racing to ship a one-off prototype in 48 hours; we’re shipping the version we’ve already shipped fifteen times, with the eval suite, monitoring, and runbook included. That’s how a Pro solution lands in 3–6 weeks instead of two quarters.
Writing is the work
Every decision — model choice, retrieval architecture, eval criteria — gets written down before it gets built. If we can’t write the argument clearly, we don’t understand it yet. This shows up in every PR description, every runbook, every audit report.
Evals before features
An eval suite is the first thing built and the last thing modified. New features ship through evals or they don’t ship. This is the difference between an LLM workflow that drifts silently in week six and one that surfaces its own regressions before they reach a customer.
Real-world cost guardrails
Hard token budgets, per-tenant rate limits, and circuit-breakers ship in v1. The first time a workflow tries to spend $400 on one retry loop, it gets stopped automatically — not after the bill arrives.
What we do not do
Four anti-patterns we won’t take money to perform.
Proof-of-concept theater
We don’t ship demos that work in a notebook and break in production. If we can’t monitor it, version-control it, and roll it back, we don’t ship it.
Slide-deck deliverables
Decks aren’t the product. The deployed system is the product. The audit report is a PDF because that’s the right format for a recommendation; everything else is a repo, an endpoint, or a dashboard.
Hours-based billing
Hourly billing rewards slow thinking and long calendars. We price productized solutions at fixed amounts and Custom builds at scoped milestones. The incentive is to ship the version that works the first time.
Model-of-the-month chasing
We don’t rebuild your stack every time a new model ships. Model selection happens at design time with cost/perf math written down; swaps happen quarterly, gated by the same eval suite, only when the math actually changes.
Start with the Audit.
The AI Workflow Audit is the cheapest, fastest way to see how we work. One week, $99, a senior engineer, a ranked list of what to actually build. If a productized solution fits, you can buy it on the same page.