Tendril
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Builders · Ages 11–13
Compare Claude, ChatGPT, Gemini, and Flux side-by-side. Learn prompt engineering and catch hallucinations.
Meet your guide: Wren — a sharp raven
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Chapters
Modules · 40
Instead of describing what you want, show the AI two or three examples. Few-shot prompting is often the fastest way to get consistent output.
Bad output is almost never random. It's a clue. Here's how to diagnose and fix a broken prompt instead of just mashing the regenerate button.
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.
Time to get hands on. Install a real AI coding editor, sign in, and write your first line together. No credit card required to start.
Git is a time machine for your code. Before we ship anything, let's learn the three commands that matter and what they actually do under the hood.
Let's make something real. A single-page site with HTML, CSS, and a little interactivity. You plan, the AI drafts, you review and ship.
Bring it all together. Pick one of three starter projects, plan it, build it with AI, and deploy it. You are now a builder who ships.
Claude.ai and the Anthropic API both run Claude. So why do they cost different amounts? Pull apart the two doors into the same model.
Artifacts is Claude's canvas. Charts, code, docs, and interactive React components render live next to the chat.
Deep Research is Gemini's multi-step research agent. You ask a question; it plans, searches, reads, synthesizes, and delivers a report.
v0 by Vercel turns a prompt, screenshot, or Figma file into a working Next.js app deployed in one click.
Upload a PDF, a set of docs, or a research paper. NotebookLM produces a two-host podcast conversation about the material.
A Space is a bookmarked, collaborative research context. Your sources, your prompts, your team — all persistent.
Three command-line coding agents, three flavors. Which one belongs in your terminal? Install all three on a weekend and decide for yourself, but here is the cheat sheet.
Every coder uses AI now. The skill is learning to code WITH AI from day one, not letting AI code for you.
Stats is 10 percent concepts and 90 percent careful arithmetic. AI is shockingly good at the arithmetic, which frees you to actually think about the concepts.
GitHub Copilot was the first AI coding assistant at scale. Look at what it is great at, where Cursor and Claude Code have passed it, and whether the $10 subscription still makes sense.
v0 by Vercel generates working React and Next.js code from prompts. Look at what it nails, what it still gets wrong, and why it's changed how startup MVPs get built.
Variables are named boxes for data. You'll write your first ten, then use AI to decode error messages and grow your intuition for types.
If-statements and loops are where programs come alive. You'll write both kinds, then see where AI autocomplete helps and where it lies.
A function is a reusable chunk of code with a name. You'll write three, add type hints, and let AI suggest better names and docstrings.
Lists are ordered rows; dicts are labeled lookups. You'll use both to solve a real problem, and catch the mistakes autocomplete makes.
A CLI quiz app: Claude generates questions on any topic, you answer, it grades. Teaches prompts, loops, and keeping state.
Variables, loops, and functions are the atoms of Python. Let an AI help you write them while you learn what each line actually does.
Lists hold ordered items. Dicts hold keyed pairs. Comprehensions make both sing. Learn the core patterns AI will push you toward.
Reading and writing files is where real scripts start. Learn the with-statement, path handling, and JSON round-trips.
TypeScript is JavaScript with types. Learn how `strict` mode catches bugs at compile time and how AI writes cleaner types than you might alone.
SELECT, WHERE, JOIN, GROUP BY. Four keywords run the data world. AI is excellent at SQL because it has read every StackOverflow answer ever.
The terminal is where real work happens. Pipes, variables, and loops in bash are a superpower — and AI is surprisingly good at shell one-liners.
Benchmarks are how AI progress gets measured. Understanding them is the first step in reading any AI claim.
When you change a prompt, how do you know the new version is actually better? A/B testing is the honest answer.
The imitation game became famous, but most AI researchers now think it measures the wrong thing.
Red-teamers try to make models misbehave before bad actors do. Here is how the job works, who does it, and what they look for.