Tendril
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Creators · Ages 14–17
The full LLM pipeline, agentic AI with OpenClaw + Ollama, subscription-tier literacy, and a real capstone.
Meet your guide: Atlas — a minimal octahedron
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Chapters
Modules · 75
Dive into the equations that governed the last five years of AI progress, and the fresh questions they raise now that pure scaling is hitting walls.
Use an AI to write, optimize, and debug your prompts. Meta-prompting is how top teams ship production prompts faster than humans alone could write them.
Before shipping, attack your own prompts. Inject, confuse, overload, and role-swap. If you don't find the holes, your users will.
You can't improve what you don't measure. Build an eval set, pick metrics, and turn prompt engineering from gut-feel into a rigorous discipline.
Red-teamers get paid to make AI misbehave. The field has grown into a real discipline — with its own methods, its own ethics, and its own unresolved questions.
The AI coding tool market fragmented fast. Let's map the 2026 landscape honestly: who is for autocomplete, who is for agents, who wins on cost, and what the tradeoffs actually feel like.
Claude Code is Anthropic's terminal-native coding agent. Let's install it, wire it to a project, and use the features most engineers miss on day one.
Codex CLI is OpenAI's terminal coding agent. It runs locally, supports MCP, and ships a codex cloud mode for background tasks. Let's install it and compare it honestly to Claude Code.
Autocomplete is a suggestion. An agent is an actor. The mental model you bring to each is different, and conflating them is the number-one reason teams trip over AI coding.
Model Context Protocol is the USB-C of AI tools. Learn the protocol, wire up a server, and understand why this standard quietly changed the ecosystem.
Frontier models now read a million tokens of your codebase in one shot. That changes how we architect prompts, retrieval, and the cost curve of agentic work.
TDD was already the gold standard. Paired with an agent, it becomes the tightest feedback loop in software. Here's the full workflow and the pitfalls.
Agents ship working code that's also quietly insecure. Red-teaming means actively attacking your own code. Let's build the habits that catch real-world exploits before attackers do.
AI app builders turn a prompt into a running app in minutes. Learn the strengths, the ceilings, and the moment you should eject to a real IDE.
There are real moments where AI coding is slower, worse, or ethically wrong. Naming those moments is as important as naming the hype.
Whiteboarding a LeetCode problem no longer predicts 2026 performance. Here's what coding interviews are becoming, and how to prepare for the new format.
Code review is the highest-leverage touchpoint in a team. Automating the noise with AI frees humans to focus on the irreducibly human parts. Let's design the workflow.
Sub-agents turn Claude Code from a coding assistant into a small engineering team that works in parallel. Let's build a real sub-agent workflow end to end.
AI belongs in CI/CD too. From PR previews to rollback judgment calls, agents can operate inside your pipeline safely — if you scope them right.
AI coding bills surprise teams that don't watch them. Let's break down the real cost drivers, the levers that actually reduce them, and how to set guardrails before your CFO does.
The creators capstone. You scope, design, build, test, deploy, and document a real full-stack project using an agentic workflow — end to end.
Underneath every agent framework is the same primitive — the model returns a structured tool call, you execute it, you feed the result back. Master this loop and every framework looks familiar.
Claude Code isn't just a coding assistant — it's a general agent runtime with MCP, subagents, hooks, and skills. Treat it that way and you get a free, powerful platform.
Computer Use lets Claude see your screen and use it — mouse, keyboard, apps. The capability is real, the gotchas are real. A hands-on look at what works in 2026.
Everything comes together. Design, code, test, secure, and ship a production-quality agent with open-source code you can fork today.
Behind the glossy UIs, video models expose REST APIs. Here's how to call Sora, Veo, and Runway programmatically and build production pipelines.
Going beyond the chat window. When you'd reach for the API, how pricing actually works, and how to start building. The API is where AI becomes a building block The consumer app is the most polished version of an AI experience.
Assemble the four or five AI tools that actually belong in your daily life. A tested template for the stack that earns its keep.
Perplexity Comet is a full web browser that treats AI as a first-class citizen. It reads, summarizes, and acts on pages you visit.
Skills let you package a prompt, tools, files, and configuration into a named capability Claude can invoke on demand.
ChatGPT's agent mode can browse, click, file taxes, book meetings, write code across multiple apps.
Cursor Agent is the editor equivalent of Claude Code — give it a goal, it reads, writes, tests, and commits across files.
Sora 2 moved from consumer-only to API in 2026. 60-second 1080p video from a prompt, callable from code.
Claude Code, Cursor, and Copilot write 40-60% of your keystrokes. The job is not gone — it mutated into reading, directing, and reviewing more code than ever.
Fine-tune, evaluate, serve, monitor. The ML engineer is the person who ships the models that now power medicine, law, and design. It is the highest-leverage engineering role.
NVIDIA GR00T, Physical Intelligence π0, and Figure Helix took the vision-language-action paradigm from research paper to factory floor. This is the hottest hardware-software frontier.
Cursor forked VS Code and rebuilt it around AI. It's now the de facto AI IDE for serious engineers. Deep dive on what makes it different, the Composer agent, and the $500/month enterprise pricing.
Windsurf (from Codeium, acquired by OpenAI in 2025) competes with Cursor via Cascade, its autonomous agent. Deep look at where it's ahead, where it's behind, and the post-acquisition future.
Claude Code runs in your terminal, operates on your actual file system, and treats your whole repo as context. Deep look at why senior engineers prefer it to IDE-based AI.
Codex CLI is OpenAI's open-source terminal coding agent. Look at how it compares to Claude Code, what it does uniquely, and why it matters to non-Anthropic shops.
Zed is a Rust-native code editor that integrates AI collaboration and pair-coding at the architecture level. Look at its strengths as a lightweight Cursor alternative.
Framer's AI turns a prompt into a publishable website with real code. Look at who's using it to ship portfolios and small-biz sites in 2026.
Zapier built the integration platform that connects 7,000+ apps. Zapier Agents and Zapier Central are its attempt to add AI agents on top. Deep look at where it works and where it breaks.
Classes let you bundle data with the behavior that operates on it. You'll build a class for a real thing and use AI to refactor it with confidence.
Async lets your program make 100 API calls at once instead of one at a time. Essential for LLM apps. You'll write the two patterns that solve 90% of cases.
Scrape a site with httpx and BeautifulSoup, then hand messy text to Claude for structured extraction. A full project in 60 minutes.
An agent is a loop: model decides, tool runs, model reads result, decides again. You'll build one in 100 lines without a framework.
Pull data from an API, clean it with pandas, ask Claude to enrich each row, save to SQLite. The pattern powers most data-engineering AI work.
Classes group state and behavior. Dataclasses cut boilerplate. Let AI scaffold while you understand what's under the hood.
async/await lets one program wait on many things at once. Perfect for HTTP calls and LLM APIs. Let AI help you avoid the common traps.
type vs interface, optional fields, and structural typing. Model your data once and let every function benefit.
Generics let a function work for many types while keeping type safety. The syntax looks scary and the concept is simple.
The App Router uses React Server Components by default. Learn the folder conventions and the server/client split.
RSCs render on the server and stream HTML to the client. Zero-JS components, free data fetching. Learn the boundary rules.
Utility classes and copy-paste components. The combo most AI tools produce best code for.
FastAPI is Python's modern web framework. Type hints become schema. Docs auto-generate. Ship an API in 20 lines.
Store embeddings, search by similarity. The foundation of every RAG system. Postgres plus pgvector gets you there.
Prisma gives TypeScript a type-safe database client generated from your schema. Model once, get autocomplete everywhere.
Clerk handles sign-up, sign-in, sessions, and accounts so you don't. Drop it into Next.js and move on.
Anthropic's SDK in 20 lines. Learn messages, streaming tokens, and basic error handling.
The Responses API is OpenAI's modern surface. One call, text and tools. Learn the shape you'll use most.
Force an LLM to return JSON that matches a schema. Zod + tool-use or JSON mode makes this reliable.
Model Context Protocol lets agents plug into your tools. A 40-line server exposes a real capability to Claude.
Chunk, embed, store, retrieve, generate. Build retrieval-augmented generation in a single file.
The model calls a function you defined, you run it, you return the result. Learn the loop and the common pitfalls.
Streaming AI chat to production takes one framework and three env vars. Learn the deploy path that actually ships.
Tie it all together. A command-line tool that reads a file, calls Claude, and prints a summary. Real code, real errors, real polish.
The UK stood up the world's first government AI safety institute in November 2023. Its structure, scope, and access model are templates other nations are following.
While larger countries debate, Singapore shipped a practical tool. AI Verify is a testing framework and toolkit that lets companies self-assess against international principles.
The world's most influential 'leaderboard' for AI is not a test — it is humans voting blindly. Here is how that works.
When the test questions quietly end up in the training data, scores lie. Here is how it happens and how to catch it.
Evaluating models that see, hear, and read at once requires new kinds of tests. Here are the ones that matter.
Prompts are code. Code needs tests. Here is how to stop silently breaking your system each time you tweak a prompt.
Benchmarks measure what you ask. Red-teaming measures what breaks. Learn to test for failure modes, not capabilities. For AI, red teams probe for harmful outputs, jailbreaks, bias, leakage of training data, and dangerous capabilities.
AI writes Java for you faster than your teacher can say 'Scanner'. Using it without cheating yourself out of the class is the real skill.