Four ways to work with me.

You email me, I reply with a short intake (what you are prepping for or want to get better at), we book a 60-minute slot over video. Sessions are worked against your real material: your repository, your resume, your interview loop, your recurring workflow. Recorded on request. I send targeted homework at the end so the next session picks up mid-stride, not from zero.

If you are not getting value out of the first session, I refund it. For 5-hour packages, unused sessions are refunded on request. The point is that you leave every session with something you can use tomorrow; if that is not landing, we do not spend more of your money on it.

Coding rounds first (data structures, algorithms, communication under pressure), which is what most engineers actually need at Amazon-tier loops. System design is available on request but not the default; I stay out of Staff-and-up system-design coaching because that is not the depth I ship at day-to-day. Behaviorals I coach as part of a package (STAR framing, tricky-question rehearsal) but do not sell as their own service.

Yes, this is a big part of who I take on. If you work in sales, finance, operations, marketing, or as an executive and want to actually use Claude on real work (not toy prompts), sessions are shaped around the recurring work you already do: research, memos, analysis, decks, email, workflows. We use Projects and prompt patterns, not code. No prior Claude experience required.

It is the diagnostic on-ramp to the fix: where your AI-coding spend is leaking, what system change would recover it, and whether to keep, renegotiate, fix, or cut. The full fee is credited toward the Accelerator if you decide to go deeper within 30 days. If the price still gives pause, the Startup tier is $2,500.

Good, most teams do not, so you are ahead of the field. The Readout then benchmarks what you already have against independent research from DORA and METR and pinpoints where the value is leaking, which is usually downstream of the individual coder. If you track license and acceptance rates but not delivery outcomes, that gap is exactly the wedge.

You get a practitioner who ships under this model daily, not a slide deck from someone who has never merged an AI-written pull request. At The New York Times I was on the AI Champions team that rolled Claude Code out across the roughly 500-engineer org, delivered three presentations including a CLAUDE.md talk at the internal EngX conference, and was the second-most-prolific contributor to the internal Claude Code plugin marketplace. The work is tool-agnostic and every number is anchored to independent data.

Your internal champion already exists, and adoption still stalled, which is precisely why there is pain. An outside seasoned read and a sanctioned, org-wide standard are things an insider cannot self-grant, because no single engineer can authorize the whole team to change how it works. I make that call easier to sanction, then hand it back to your team to run.

No. Claude Code is the tool I know deepest, so it is the natural wedge, but the methodology is tool-agnostic and built on durable principles rather than any one model or agent. The bottlenecks it fixes, review bandwidth, missing baselines, and a workflow built around humans reading every line, are the same whether you run Claude Code, Copilot, Cursor, or whatever wins next.

Honesty is the whole point, so there are no 10x promises. Independent research from METR and DORA sets the frame: gains are modest and uneven, and the larger wins come from clearing the downstream bottleneck, not from speeding up the coder. The Accelerator proves it on your own code with a one-team pilot and a before-and-after delta on review time, throughput, and revert rate, and that number becomes your attributable case study.

The front-door Readout is deliberately low-access: dashboards and interviews, not a repository deep-dive. For anything that touches code, I work read-only inside your environment, time-boxed, so code never leaves your infrastructure, under a mutual NDA. I state delivery practices plainly and never claim a certification I do not hold.

Engineering orgs of roughly 20 to 500 engineers, with the mid-market sweet spot around 20 to 200, where a coding-agent rollout is already live but the system of work around it was built for humans reading every line. The front door is sized to approve on a team budget, so the buyer is usually an engineering manager, director, or Head of DevEx, not a procurement committee. Mid-market software and media teams usually need enablement and measurement most; regulated enterprises need the risk-tiering most. If you are under a dozen engineers on greenfield code, you likely do not need this yet.