Tendril
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A curated walkthrough of the library — ordered lessons, a 15-question quiz between each, and 3 next-steps so you stay in flow. Earn XP, badges, and a streak as you go.
Lessons · 6434 available · Intermediate view
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Lessons handpicked for the Intermediate shelf.
A chatbot answers. An agent does. Learn the line between a model that talks and a model that acts — and why crossing it changes everything about how you work with AI.
Every agent — fancy or simple, local or cloud — boils down to four parts. Learn the recipe and you can read any agent system like a menu.
Follow a real agent run step by step — from prompt to result — and see exactly what happens inside. No code yet, just the anatomy of a successful task.
Agents fail in weird, quiet, expensive ways. Learn the six failure modes, the warning signs, and the simple habits that catch problems before they compound.
Fresh Intermediate lessons added to the library.
Forget extinction for a minute. Here is the practical stuff: how not to get fooled, scammed, or worse in your daily use of AI.
Measured people at serious labs and universities publicly worry about AI going very wrong. Here is what they mean, what they disagree about, and how to read the headlines.
The big international AI summits produce non-binding declarations. Even so, they shape the rules. Here is what each one did.
The world's most ambitious AI law passed in 2024. Here is what it actually does, when it kicks in, and why it matters if you do not live in Europe.
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A chatbot answers. An agent does. Learn the line between a model that talks and a model that acts — and why crossing it changes everything about how you work with AI.
Every agent — fancy or simple, local or cloud — boils down to four parts. Learn the recipe and you can read any agent system like a menu.
Follow a real agent run step by step — from prompt to result — and see exactly what happens inside. No code yet, just the anatomy of a successful task.
Agents fail in weird, quiet, expensive ways. Learn the six failure modes, the warning signs, and the simple habits that catch problems before they compound.
Giving an AI the keys to your computer is a big deal. Learn the two simplest ways to keep an agent safe: wall it off from things it shouldn't touch, and put a human in the decision path.
Agents are only as useful as their tools. Tour the big three — filesystem, browser, code execution — plus the emerging MCP ecosystem, with examples of what each unlocks.
Your data can live in someone's data center or on your own laptop. Both are real options in 2026. Understand what you gain and lose with each.
OpenClaw is open-source software that runs agents on your own machine — no cloud dependency, your data stays put. A tour of why it exists and how its pieces fit together.
Ollama turns 'I want to run an LLM locally' into a one-line install and a two-word command. Here's the stack, the key commands, and the models worth pulling first.
No code. Just design. Pick a real task you do every week and draft a complete agent spec — goal, tools, loop, stop, approvals, and what success looks like.
AI-assisted coding is not magic and not cheating. It is a new way of working where a model drafts, you decide. Let's draw a map before we start building.
Let's actually feel what autocomplete is like. Write a comment, pause, and watch a full function appear. Then learn what to do next.
A prompt that writes a poem is not the same as a prompt that ships working code. Code has hidden standards. You need to make them explicit.
The AI will hand you code that looks right but isn't. Here are the most common bugs and the habits that catch them before they bite.
Bugs are where AI is most useful and most humbling. Paste errors, ask for causes, run experiments, and learn how to get a real answer instead of a guess.
Writing a test first is not just good engineering. It is the clearest possible prompt for an AI. Let's use tests to make AI code reliable.
Most of a developer's life is reading code someone else wrote. AI is astonishing at this. Here's how to get fast, honest explanations of unfamiliar code.
Refactoring means changing code without changing behavior. That used to be scary. With tests and AI together, it becomes routine.