Build AI into the way your whole team works: economics, processes, shared context, quality checks, the agent lifecycle and rollout. You’re Head of Product at an international tech company, and you work through all of it hands-on in Claude Code (Codex coming as a free update).
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Students include product managers and marketers from Meta, Amazon, Shopify, Booking, Revolut, OLX, Nebius, Yango, Plata and T-Bank~/hireflow $ claude
Mikhail, CEO“I need the team working twice as fast”
> /diagnose team
⚠ 3 PMs · 3 incompatible “personal systems”
⚠ The CTO re-checks everything by hand after 2 incidents
> /evals prd-review
✓ Golden set, rubrics and LLM judge ready
> /roi discovery-pipeline
✓ Cost per task calculated · payback: 6 weeks
>
BCG, Applied AI Index, 2026 · source
The share of employees in dedicated AI roles will grow from 7% to 22%. Almost half of companies already get real results from AI, and what sets the leaders apart isn’t the models: they rebuild entire processes, invest in people and oversight, and measure the impact on the P&L. BCG, Applied AI Index, 2026 · source
AI leaders, just 7.5% of companies, grow revenue 2.4 times faster than the laggards.
BCG, Applied AI Index, 2026 · source42% of companies want agents making decisions on their own by 2030, but only 5% have the full set of controls in place.
BCG, Applied AI Index, 2026 · sourceof employees get little to no guidance on what to do with the time AI frees up.
BCG, AI at Work, 2026 · sourceSwipe and tap a situation: the card flips to show which block covers it.
This advanced course isn’t about using AI on your own. It’s about how your whole team works with AI: which processes you need, and how to roll them out, keep them running and change them.
An international tech company that makes hiring software. You’ve just been promoted to Head of Product: the team already uses AI, but everyone does it their own way, and cleaning that up is now your job. The story starts in the foundation course for product managers, but you can take this one without it.
From rollout economics to a plan that pays off.
How to calculate an AI process’s payback and make go / no-go calls
Rebuild the process instead of bolting an agent onto the old one
What people and agents both know about the company, and how to set it up and keep it current
Who on the team owns what, and what an agent can and can’t do
Golden sets, rubrics and checks before you scale
Least-privilege access and where the agent gets its numbers
Solid discovery with agents, without silent failures
Registry, owners, incidents and sunsetting
A pilot, pushback, a team standard and new team meetings
A plan for your team that pays off
That’s how an agent graveyard starts. Once agents live inside your processes, they have a life of their own: model swaps, quality drift, incidents. In the course, you set up a system that keeps an eye on all of it.
One doc that lists every agent on the team, who owns it and when its quality was last reviewed.
What happens when an agent gets it wrong: who stops it, who reports it, who fixes it.
Shutdown conditions are written down at launch. Killing an agent that doesn’t pay off is totally fine.
You can’t roll out a new process by memo. It takes a pilot, working through pushback, a team standard and new rituals that keep the system alive. Here’s what your team’s week could look like after rollout.
Once AI is part of your processes, the economics change: instead of people’s hours, you’re paying for tokens, human review and the cost of mistakes. You learn to count all of it and make calls based on the numbers.
What the process costs today in time and money. Without that number, any AI impact is just a feeling.
What one task costs when an agent does it: tokens, human review, incidents.
When the rollout earns back what you put in, and what to report to the CEO week by week, not at the end of the quarter.
What to keep, what to scale and what to shut down because it doesn’t pay off.
Everything you build in the course lives in one repository. Your team comes back to it whenever they launch a new AI process, dig into an incident or onboard someone new.
~/work $ tree hireflow-course-pro
├── CLAUDE.mdcourse rules and context
├── hireflow-context/the company where you’re Head of Product
├── lesson-modules/situations and breakdowns by block
├── my-company/8 artifacts about your company
└── my-toolkit/audit, prioritization, agents
✓ ready for your real projects
Claude Code version now; the Codex version comes as a free update, with the same repo structure.
Every module works the same way: first you solve the task in the simulator, then you take the same step at your own company. No sensitive data needed: you work with roles and ranges, not names and exact numbers.
13 weeks of storyline: a team, deadlines and the fallout from your decisions.
Templates and tools that pile up as you go.
Every module ends with applying it to your own team.
Trust boundaries, an agent registry, economics, a team standard and a rollout plan for your team.
22 modules plus an optional one. Pick a route at the start and switch anytime: Full path (about 29 hours), Leader core (about 17 hours) or Trust already frozen (about 10 hours), for teams where agents have already been cut off from data.
Product leaders and founders who already have a team. This isn’t about learning prompts. It’s about owning the system: quality, data, owners and money.
A team of 3–10. Everyone’s “personal systems,” a CEO who wants “twice as fast” and eyeballed quality are already on your calendar.
Your mandate and boundaries with the CTO, rollout metrics, economics in dollars and a story for the board and investors.
Stop being the only one holding AI together: owners instead of you, a written standard instead of explaining everything out loud, and payback measured in your hours.
No team yet? Then this course is one to grow into: come back once you have one. At a very large company, pick one team and treat the course as a lab you run with it.
Head of AI reviews will appear here soon. For now, these are reviews of the foundation course it builds on. More are on Telegram (in Russian).
All reviews on Telegram ↗Both formats include the full simulator: all 7 blocks, my-toolkit, 8 artifacts for your company and a rollout plan. The course is in English and runs in Claude Code; the Codex version comes as a free update.
Instant access after payment
Checkout via Tribute: Visa, Mastercard or crypto
Leave your contact details and I’ll send you a payment link. I usually reply within a day.
The foundation course teaches you to work with AI yourself. Head of AI is about how your whole team works with it: processes, shared context, quality, data access, the agent lifecycle, rollout and economics.
This course is built for people who already work with AI on their own: agents, CLAUDE.md or AGENTS.md, skills. If that’s not you yet, start with the foundation course for product managers.
Yes. All 7 blocks are out: 22 modules plus an optional one. You pick a route at the start and can switch anytime: Full path (about 29 hours), Leader core (about 17 hours) or Trust already frozen (about 10 hours).
About 29 hours of practice on the full path, at your own pace. The shorter routes take about 17 or 10 hours. The simulator’s storyline covers 13 weeks of your work as Head of Product.
No. You build the artifacts for your own company using roles instead of names and ranges instead of exact numbers, so you never need sensitive data.
The course is about processes and rolling AI out across a team, not about one specific tool. Claude Code and Codex are the most widely used agents and easy to learn on. The Claude Code version is out now; the Codex version comes as a free update. Diagnostics, shared context, quality checks, trust boundaries, the agent lifecycle and economics carry over to any other agent.
Yes, for the tool itself: Claude Pro or higher for Claude Code. Once the Codex version is out, ChatGPT Plus or higher will work for it. You set up the subscription yourself before you start the course: it isn’t included in the course price, and we don’t help with setting it up or paying for it.
The curriculum is the same in both. The consultation format adds two one-on-one sessions with me about your team.
The course is available in English. My Telegram channel and YouTube videos are in Russian.
A simulator of HireFlow, a tech company: PRDs, customer discovery, data and your own prototype.
Course details → course 02 · foundationClaude Code and Codex for marketersA simulator of Pulse, a fitness startup: content, GTM and your own landing page.
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course authorJane OdudAbout the author →