I build the AI curriculum organizations actually run on.
Two tracks: deep technical enablement for field and engineering orgs, and practical AI fluency for everyone else.
Organizations are adopting AI faster than they can teach anyone to use it. Field teams get product decks that can't survive a technical question. Staff get tool licenses and a launch email. In both cases the training explains the tool but never touches the work — and that gap, between the explainer and the actual job, is where I build.
“Most AI training explains the tools. I build training on the work people actually do — real APIs for engineers, real workflows for everyone else.”
Developer & field enablement
For companies whose product is an API, an SDK, or a developer platform — and whose field org has to be credible in front of engineers.
01
Curriculum Audit + Roadmap
2–3 weeks · fixed fee
A low-risk first step. I assess what enablement material exists, map the gaps against your current product surfaces, and hand back a prioritized build roadmap — so the next call is an easy yes or an easy no.
02
Build Sprints / Backlog Burn-Down
Per-project or monthly retainer
Shippable courses, hands-on labs that run reliably live, demos, and decks with facilitator guides — built to stay current as the product changes, not to go stale the next release.
03
AI-Assisted Engineering Enablement
4–6 weeks, or ongoing
Your engineers have coding assistants and agent tooling. Adoption is uneven and nobody agrees what good looks like. I build the practices, review standards, and hands-on curriculum that turn scattered usage into a consistent way of working.
04
Fractional Enablement Lead
1–2 days/week, embedded
I own a product surface's curriculum end-to-end, partnering directly with enablement leads, program owners, and PMM as if I were on the team.
05
Workshops & One-Offs
Scoped per engagement
Developer Day and hackathon-in-a-box design and delivery, train-the-trainer sessions, and facilitator-guide production for teams running their own enablement.
AI fluency for knowledge workers
For organizations that have bought AI tools and now need the people using them to get real work done — no code required.
01
Role-Based AI Fluency Program
Cohort-based · 4–8 weeks
Not a tour of the chat box. Curriculum built per function — sales, marketing, finance, ops, support, legal — around the tasks those teams actually own, with tested prompt and workflow libraries they keep.
02
Rollout & Adoption Sprint
3–4 weeks · fixed fee
You bought the seats and usage is flat. I find where adoption is actually stalling — unclear permissions, no trusted use cases, no visible wins — and build the enablement that moves weekly active use, measured against a baseline.
03
AI Champions Program
6 weeks, then handoff
Train-the-trainer for an internal cohort, so capability compounds after the engagement ends. Champions get the curriculum, the facilitation skills, and the maintenance model to keep it current.
04
Executive & Leadership Briefing
Single session
What's real, what's hype, and where the leverage actually is for your business — plus the governance and safe-use questions leadership has to answer before a broad rollout.
Who this is for
On the technical side: Series B–D companies (or big-tech AI orgs) with a live product, a growing field org — SAs, SEs, DevRel, ADMs — and no dedicated capacity to build technical curriculum. On the workforce side: any organization that has rolled out AI tooling and is watching adoption stall. The person reaching out usually owns enablement, L&D, GTM, DevRel, or an AI center of excellence.
Why this, from me
25+ years across solutions engineering, DevRel, and technical training
Built and led the MongoDB SA-enablement program — onboarded incoming sales, AMs, and SAs with measurable pre-sales impact
6 years as a MongoDB Developer Advocate
160-episode podcast and active conference speaker
A shipped portfolio of products built directly against AI APIs — Anthropic SDK/Claude API, MCP, agents
Curriculum delivered to audiences from career engineers to people opening an AI tool for the first time
Why not a generalist
Generic enablement consultants can describe a product but can't build against it. Instructional designers know pedagogy, not the API surface. DevRel-for-hire is broad, not curriculum-focused. The AI-training market is filling up with people one course ahead of the room. Big training agencies are slow and expensive. The lane I work in is the intersection none of them own: technical enough to build the lab, and experienced enough to make it teach well — to engineers and to everyone else.
Let's talk about your backlog
The fastest way to find out if this is a fit is a short call — what exists today, where the gaps are, and whether an audit or a build sprint makes more sense to start.