Ship AI features that survive production

Ship AI features that survive production

Six weeks, live, with twenty-three other product leads who are past the demo stage and answerable for what happens after launch.

Six weeks, live, with twenty-three other product leads who are past the demo stage and answerable for what happens after launch.

Program starts

Mon, Oct 5, 2026

Format

6 weeks · live + async

Time commitment

5–6 hrs / week

Taught live by

Howard Vance

ex-Staff PM, Anthropic Applied

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Alumni

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Rating

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Completion

Alumni ship at

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01 — The shift

Six weeks from now you are the person who settles the argument with numbers.

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Scope a feature that survives contact

A spec with named failure modes, a fallback path and a kill criterion. Most AI features ship without all three and die of it by month two.

02

Build evals an engineer will actually run

Forty scored cases pulled from real transcripts, versioned in the repo. The numbers end the argument instead of starting it.

03

Price the feature before finance does

Unit economics end to end, three scenarios, caching and routing accounted for. You arrive at the budget review with the sheet already built.

04

Kill the wrong project in week one

Name the cases where a deterministic system beats a model, say it in the roadmap review, and bring the evidence that closes it.

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02 — Your instructor

Howard Vance
ex-Staff PM, Anthropic Applied

Shipped applied-AI product to 40 million users. Teaches the part nobody documents: the judgment.

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Years in product

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AI launches led

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Bootcamps led

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Years in product

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Bootcamps led

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AI launches led

Howard led applied-AI product at Anthropic and ran the ML platform team at Figma before that. He has written the eval harness, defended the cost model to a CFO, and killed two features that demoed beautifully. This bootcamp is the internal onboarding he never got, compressed into six weeks and taught live, so the uncomfortable questions get asked while the decision is still open.

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03 — Curriculum

Six weeks, six shipped deliverables

Week 01

What models are actually good at

2h live · 3h work

Week 02

Scoping a feature that can survive users

2.5h live · 3h work

Week 03

Evals before opinions

2.5h live · 3h work

Week 04

Cost, latency and the CFO conversation

2h live · 3h work

Week 05

Shipping, guardrails and the incident you will have

2.5h live · 3h work

Week 06

Your roadmap defence

3h live · 2h work

Week 01

What models are actually good at

2h live · 3h work

Week 02

Scoping a feature that can survive users

2.5h live · 3h work

Week 03

Evals before opinions

2.5h live · 3h work

Week 04

Cost, latency and the CFO conversation

2h live · 3h work

Week 05

Shipping, guardrails and the incident you will have

2.5h live · 3h work

Week 06

Your roadmap defence

3h live · 2h work

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04 — Format

Five to six hours a week, always on the same three days

Weekly split

Live sessions

2.5 hrs

Project work

2 hrs

Reading & async review

1 hr

Every live session is recorded within two hours. Miss one and you keep the breakout notes plus a 20-minute async catch-up from Howard.

Weekly rhythm

MON

Live teaching session

09:00 PT

WED

Workshop & peer critique

09:00 PT

THU

Open office hours (optional)

16:00 PT

FRI

Deliverable due

17:00 PT

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05 — Fit

Built for a specific kind of engineer

Enroll if you

Own a product surface where AI is already on the roadmap

Can hold five hours a week for six weeks, two of them live at 09:00 PT

Would rather be corrected by peers than agreed with politely

Have a live feature to bring as your project

Skip this if you

Want a certificate more than a shipped deliverable

Need an introduction to what a language model is

Plan to watch the recordings and skip the sessions

Are shopping for an implementation vendor, not your own judgment

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06 — Results

What alumni shipped in the ninety days after

  • Killed a six-month AI roadmap item in week three

    The eval work showed our retrieval was the problem, not the model. We shipped a boring fix instead and saved two engineers a quarter of work.

    Priya Raman

    Director of Product, Vela Health

  • Cut inference cost 61% in eight weeks

    I walked into the budget review with the scenario sheet from week four. Finance approved the feature in one meeting instead of three.

    Tobias Lund

    Senior PM, Orbital

  • Got promoted to lead the AI surface

    My roadmap defence from week six became the actual plan. I presented the same deck internally two weeks later and was given the team.

    Alina Costa

    Group PM, Figment

  • Shipped an assistant to 90k users with zero rollbacks

    The launch runbook is the only reason. We caught two bad-output classes in staged rollout that would have been a public incident.

    Marcus Oyelaran

    Staff Engineer, Northlane

  • Turned a stalled pilot into a paid product in 70 days

    We had been in pilot purgatory for a year. Scoping it properly with a kill criterion is what finally got it out the door.

    Hana Ito

    Head of Product, Kestrel AI

  • Rewrote how our design team specs AI flows

    Failure modes are now a required section in every spec we write. That single change came out of week two.

    Dev Shah

    Design Lead, Ramp

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07 — Pricing

Same bootcamp.
Two levels of access to Howard.

CORE PROGRAM

$2,400

one-time

or 3 × $840, no interest and no credit check

Six live sessions with Howard, capped at 24 people

Weekly workshop and a standing peer critique group

Six graded deliverables, ending in your roadmap defence

The eval harness, cost model and incident runbook templates

Permanent access to recordings and the alumni Slack

Full refund through the end of week two. No forms, no call.

6 Seats

PROGRAM + MENTORSHIP

$3,900

one-time

or 3 × $1,350, employer invoicing on request

Everything in Core Program

Three 1:1 sessions with Howard on your own live feature

Written review of your spec, eval set and roadmap

Direct Slack access to Howard for all six weeks

A session 90 days out to review what actually shipped

If the mentorship seats fill you move to Core and we refund the difference.

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08 — FAQ

Before you apply

How much time does this really take each week?

Five to six hours: one 2–3 hour live session, roughly two hours of project work, and an hour of reading. Alumni who treated it as a two-hour-a-week course did not finish the final project. That is the honest number.

What happens if I miss a live session?

Recordings are posted within two hours with timestamps and the breakout notes. For the two workshop-heavy weeks, Howard records a 20-minute async catch-up covering what the bootcamp argued about, and you can bring your work to the next office hours.

Do I need to be able to code?

No, but you need to be comfortable reading a Python notebook and running a script someone else wrote. Product managers and designers do fine. If you have never touched a terminal, budget an extra hour in weeks three and four.

What is the refund policy?

Full refund through the end of week two, no forms and no exit call, just one email to hello@appliedai.co. After week two the material is substantially delivered, so refunds stop.

Can my employer pay for it?

Yes. We invoice with a PO, W-9 and itemised receipt, and about 70% of each bootcamp is employer-funded. There is a one-page justification memo in the pre-enrollment pack you can forward to your manager.

How is this different from a self-paced course?

Twenty-four people, one instructor, a fixed six weeks and a deadline every Friday. You are critiqued by peers doing the same job, and nothing is pre-recorded except the recordings of your own bootcamp.

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The window closes Oct 2.

Applications close as seats fill, not just on the date.

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