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Coaching Path · Detail

How we coach in-house teams

Foundation Workshops, CTO Advisory, and AI-Native Roadmap. Three offerings for companies building their own AI engineering capability, independent of any vendor (us included).

This page is the long form for Path B. If you're a CTO or COO who has decided to build AI capability inside your team rather than outsource it, here's exactly what each offering covers, what gets produced, and who it's for. We coach you through the same Embed Method we use ourselves; the difference is your team owns the building.

Foundation Workshops

1–2 daysFixed fee per cohort

Foundation Workshops compress the first six months of self-taught AI engineering into two days. We work through your actual workflows: where the calendar bleeds, what your stack supports, what an agent can realistically own. By the end of day 1 your team has a working prototype against your real APIs; by day 2 they've iterated on it, written the operating notes, and identified the next two roles worth building. We do this on-site by default. The goal is a team that has shipped something. The output is muscle memory. Companies that run this workshop usually go on to engineer Path A or Path B with much sharper questions, because the abstract is now concrete.

Format

On-site or remote, cohort of 6–12 people across engineering, product, and ops. Working sessions on your real workflows, not generic exercises.

Deliverable

A team that has built and shipped at least one working agent against your stack by the end of day 2. Plus the working notes, prompts, and runbook drafts.

Who it's for

Engineering and product teams that need a practical baseline before committing to a Phase 1 Architect engagement, internal or external.

CTO Advisory

Quarterly retainerQuarterly fee

CTO Advisory is a quarterly retainer for the engineering leader who needs a sounding board. Each quarter we run a working session against the questions actually on your plate: which AI bets to fund, which platform to pick, when to build internally vs. license, how to triage a pilot that's drifting. Between sessions we're available for short, specific calls (vendor demos, architecture review, hire-vs-contract decisions). The output is a written decision log you can hand to your board and your team. CTO Advisory is intentionally light-touch; if you need full-time AI engineering, you need an AI lead. We will tell you that, in writing, when it's the right call.

Format

Quarterly working session plus on-call advisory between sessions. Senior engineering perspective without a full-time hire.

Deliverable

Quarterly architecture decision log plus ad-hoc advisory on build-vs-buy calls, pilot triage, vendor selection, and team capability planning.

Who it's for

CTOs and VPs of Engineering at 100–500 person companies who need senior AI engineering judgment without bringing in a full-time AI lead.

AI-Native Roadmap

4–6 weeksFixed fee

AI-Native Roadmap is what Phase 1 Architect looks like when the customer is the building team. Four to six weeks of joint work mapping your team, your stack, your existing AI workflows, and your 12-month direction. The output is a multi-quarter capability plan: which agents to build internally, which to delay, what to license, who to hire, what to train. Our role is the senior engineering perspective and the writing. Your role is the institutional knowledge and the sequencing decisions. The blueprint is yours; we don't retain copies, and the deliverable lives in your repo from day one. Companies that do this work tend to skip the long vendor-evaluation cycle that most enterprise AI initiatives waste, because they already know what they want to build.

Format

Four to six weeks of joint work with your senior leadership and engineering. Deep dive into your stack, team, and current AI workflows.

Deliverable

A written capability blueprint (current state, target state, role-by-role build plan, hiring map, and 12-month sequencing) plus the supporting decision logs.

Who it's for

Companies committing to in-house AI engineering as a capability. Typically 200+ employees with an existing engineering org and at least one AI workflow in production.

Curriculum

What in-house AI capability actually requires

Across the three offerings, the coaching covers the same six competency areas, calibrated to your team's current depth.

01

Agent design

Reading the workflow, naming what an agent owns, defining the read/write contract with each tool.

02

Prompt boundaries

Where the prompt ends and the runtime begins. Versioning prompts as code. Eval-driven iteration.

03

Stack integration

Wiring agents into the tools you already run. Auth, audit, retry, idempotency, fallback.

04

Evaluation & observability

What to measure, when synthetic benchmarks lie, building operator confidence as the gate.

05

Operating model

Operator pool, runbook, escalation paths, decision audit log. The post-launch reality.

06

Decision discipline

Build vs. buy vs. delay. When to retire an agent. Quarterly review of what's still earning its keep.

Next step

Two ways to test the fit.
Diagnostic, or Maturity Assessment.

Book a Diagnostic if you want a peer engineering conversation about where your team is today and the fastest path to in-house AI capability. Output is a 4-page written diagnosis you own. Take the AI Maturity Assessment if you want a structured scorecard before any conversation. Either route ends with you owning a written document.

Book a DiagnosticTake the AI Maturity Assessment

Both deliver inside 48 hours · No follow-up unless you ask