Library
Learning tracks
Each track is a short series of lessons on one skill, with the best free courses and videos to go further.
Back to the library · All learning resources
Tracks
Product skills
Product discovery
Learn what to build, and for whom, before anyone writes a line of code. Frame the problem, interview real customers, map the whole product and decide with evidence.Personas and journeys
Turn customer evidence into personas, touch points and journey maps, then find the places where the journey breaks. Those breaks become the epics on your roadmap.Roadmapping and epics
Write epics by hand, order them with reasons, keep the plan in git and cut the first epic into milestones that AI agents can build from.Agile delivery
Run delivery in short cycles with a backlog you own, stories an agent can build, honest estimates, a written definition of done, and reviews and retrospectives that change what you do.Stakeholder communication
Map who is affected by your product, write the notes and one-pagers that keep them aligned, defend your roadmap in ten minutes and handle requests, risks and bad news without losing trust.Brand, website and mockups
Choose a name people can say, write the brand sheet, draw mockups tied to your epics, publish a small accessible website from git and test it with real people.Decision-making
Frame the problem, ask better questions, compare options in writing and brief agents to prepare a decision that you alone make and record in git.Leading people and agents
Set direction and written expectations, give and receive feedback, and run one team in which some of the workers are people and some are AI agents, with briefs, review and clear accountability.Research and evidence
Find out what is true before you build. Ask a question you can answer, find and judge sources, check everything an AI agent cites, and keep an evidence log in git.Thought leadership
Make your thinking visible: find a point of view you can defend, write a short post or demo write-up from your Product Package, and share it honestly, with AI use disclosed and no claim you cannot show.
Tracks
Working with AI
Working with AI agents
The flagship track: direct AI agents as your workforce. Write specs and acceptance criteria, orchestrate several agents, verify their work, measure it with evals and manage the risk, while people own the epics and the roadmap.Agent orchestration and policy administration
Advanced track: run many AI agent sessions as a command chain, bound them with written policy, hooks and gates, and keep the decisions only a person should make.
Tracks
Engineering skills
Git and GitLab
Enough depth in git and GitLab to direct agents and judge their work: read a diff, run a review, plan on the free plan, and fix forward.CI/CD
Read a pipeline, judge what it proves, and direct agents to build and fix pipelines: tests, images, quality gates, delivery and pipeline security.Cloud platforms
AWS, Azure and Google Cloud explained without vendor loyalty: the building blocks, identity, cost and reliability, so you can direct agents that build there and judge what they build.Kubernetes and GitOps
Understand how Kubernetes runs software and how GitOps keeps it honest, so you can direct agents that change a cluster and judge what they propose.Infrastructure as code
Describe cloud infrastructure in files, review the plan before anything changes, and judge what agents write with Terraform and OpenTofu.Security fundamentals
Know the threats that matter, keep secrets out of git, trust your dependencies carefully, and set the limits that keep agent work safe.Observability and service management
See what your product is doing, promise a level of service you can keep, respond well when it breaks, learn from it, and change it safely, with agents doing the legwork.
Tracks
Frameworks
Frameworks
The Dojo's shared language for strategy, planning, building and running a product: UBF, STAR, ORBITAL, ANDROID Ops, PHANTOMS and Launch Sequence, taught for the Product Development Manager who works across every discipline and directs AI agents.The PHANTOMS stack
A family of agent-ready starting points for building real products. Learn the pattern, choose and swap each piece by the job it does, and direct AI agents to scaffold TrailMug's order tracker, then verify what they built.
