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 · 38
From raw bytes to deployed model, every ML system follows the same ten-stage pipeline. Master it and you can read any architecture paper.
Emergent abilities make AI both more exciting and more dangerous. How do labs forecast what the next model will do — and what happens when they are wrong?
Open-source AI is both a technical movement and a political one. Understand the arguments so you can pick a stack and defend it.
Every AI breakthrough of the past decade rests on three interacting ingredients. Synthesize everything you have learned into one working model.
Before shipping, attack your own prompts. Inject, confuse, overload, and role-swap. If you don't find the holes, your users will.
Abstract jailbreak theory is less useful than real cases. Here are the techniques that worked on production models, what they taught us, and what is still unsolved.
If you ship AI, ethics is not abstract. It is a set of decisions you make with real trade-offs. Here is the working checklist serious builders actually use.
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.
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.
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.
The creators capstone. You scope, design, build, test, deploy, and document a real full-stack project using an agentic workflow — end to end.
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.
A prototype agent and a production agent have the same LLM. What's different is everything around it — durable state, retries, idempotency, observability. The real engineering.
Everything comes together. Design, code, test, secure, and ship a production-quality agent with open-source code you can fork today.
Claude Pro vs Max. ChatGPT Plus vs Pro. Gemini AI Pro vs Ultra. Stop guessing which plan you need. Here's the full map.
Subscription spend on AI can silently hit $100/mo. Learn the usage signals that mean upgrade, and the vibes that just mean temptation.
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.
Databricks Assistant, Snowflake Cortex, and dbt Copilot draft pipelines in minutes. The edge is in modeling, governance, and knowing what business question to answer.
Microsoft Security Copilot, CrowdStrike Charlotte, and SentinelOne Purple accelerate defense. Attackers use the same models. The security engineer is the referee in an AI-vs-AI arms race.
The EU AI Act, SEC AI disclosure rules, and state-level bills made AI governance a core compliance responsibility. The role grew; it did not shrink.
A real job now: adversarially probing LLMs and multimodal systems for jailbreaks, prompt injection, data exfiltration, and harm.
The job climbed the ladder. Simple image labeling went to workflows; trained humans now do reinforcement learning from human feedback on hard tasks.
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.
Galileo AI (now part of Google) generates high-fidelity UI mockups from prompts. Look at the acquisition, what happened to the product, and current Google Stitch equivalence.
ElevenLabs generates synthetic voices indistinguishable from human recordings. Deep dive on voice cloning, dubbing, the consent-and-ethics story, and pricing realities.
Writer is a full-stack enterprise AI platform with its own models (Palmyra), strict governance, and deep integrations. Look at who chooses it over ChatGPT Enterprise.
Gong records, transcribes, and analyzes every sales call to surface what works. Deep dive on what Gong actually does, the 'deal intelligence' features, and why it's $1,500+/seat/year.
Clay scrapes, enriches, and personalizes at scale for sales and marketing. Deep look at what it does, the Claygent agent, and pricing that starts at $149/month.
Vic.ai autonomously processes invoices, codes transactions, and speeds up AP teams. Deep look at what CFOs are buying and where it fails.
Harvey is the AI legal platform deployed at top law firms worldwide. Deep dive on what it does, why firms pay six-figures for seats, and the 2026 competitive landscape.
Streaming AI chat to production takes one framework and three env vars. Learn the deploy path that actually ships.
Not toy examples. These are reward-hacking behaviors documented in production LLM training runs, with what each one taught.
The attacker does not need access to the model. They only need to put a few carefully chosen examples into its training data. Here is how that works and why it is unsolved.
The world's most influential 'leaderboard' for AI is not a test — it is humans voting blindly. Here is how that works.
A calibrated model's 70 percent means it is right 70 percent of the time. Most LLMs are not calibrated. Here is what that costs you.
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.
Deceptive alignment is when a model behaves well during training while planning to behave differently after deployment. Long a theoretical worry, recent work has moved it onto the empirical map.