Find your path.
The wiki is organised around the problems you actually face. Pick the role that fits and get a reading path built for your situation, not for a generic reader.

You are accountable for what ships. That means you need to understand what engineers are actually building, how long it takes, and when the AI approach is wrong. This path gives you the vocabulary to ask the right questions in every room.
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AI projects have real cost structures, lead times, and regulatory obligations. This path helps you evaluate proposals, build a business case, and understand what governance requirements apply to your industry.
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You use AI tools to build software. You direct. The AI writes. But things break, and you need to understand enough to debug, deploy, and keep it running. This path covers the vocabulary that makes you a better director.
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You are building your mental model from zero. No prior knowledge assumed. This path starts with computers, the internet, and code, then builds up through AI systems in a sequence that actually makes sense.
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You need to decide what to build, who to hire, and whether the AI approach your team proposes will actually work. This path gives you the technical literacy to make those calls without getting lost in the details.
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Your clients expect you to speak AI fluently. That means governance frameworks, risk vocabulary, EU AI Act basics, and the ability to tell a good architecture from a bad one. This path builds that fluency fast.
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You have shipped production systems for years. LLMs are the new part: non-determinism, evals, per-token economics, models that change underneath you. This path maps the delta without re-teaching what you already know.
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AI changes how content gets made, targeted, and measured. This path gives you the vocabulary to brief the tools, judge the output, and see through the hype in vendor pitches.
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AI is entering hiring, reviews, and people analytics, and the rules there are strict. This path covers what the tools actually do, where the risks live, and which uses count as high-risk under the EU AI Act.
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You learn by growing things, patiently and hands-on. Start in the soil with the basics, tend one layer at a time, and watch it grow into a real system. The garden metaphor runs the whole way: the Gardener Path and the video course are built for exactly this.
Start reading →Not sure which path fits?
Start with the basics. Level 0 assumes nothing and builds up from "what is a computer" through AI and production systems. Anyone can follow it.
Or try a different angle
Learn through a world you already know.
Technical role paths not landing? Choose a metaphor lens instead. The same concepts, explained through fashion, juggling, or analogue craft.





