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 · 102
Anthropic publishes detailed prompt engineering guidance. Master the core patterns — Be Direct, Let Claude Think, and Chain Complex Prompts — to write production-grade prompts.
Claude was trained heavily with XML-tagged examples. Using tags to separate inputs, instructions, and expected outputs is one of the highest-leverage Claude-specific techniques.
An attacker can inject text that looks like part of the AI's own response, tricking it into behaviors it would otherwise refuse. Understand the attack vector and how to defend.
Some problems need more than one prompt. Learn how to design multi-turn reasoning flows — reflection, critique, retry — that give you AI which actually solves hard problems.
Asking the model to critique and revise its own output is one of the cheapest quality boosts in prompt engineering. Master the patterns and their limits.
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.
Long system prompts are expensive. Prompt caching lets you reuse the prefix at up to 90% cost reduction and much lower latency. Here's how to architect prompts for caching.
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.
The creative industries are not against AI. They are against training on their work without consent or compensation. Here is what the fight is actually about.
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.
The creators capstone. You scope, design, build, test, deploy, and document a real full-stack project using an agentic workflow — end to end.
One smart agent is fine. Two agents checking each other's work is better. Master the canonical orchestration patterns: planner/executor, judge/worker, debate, and swarm.
Everything comes together. Design, code, test, secure, and ship a production-quality agent with open-source code you can fork today.
Two fundamentally different approaches to generating pixels. Understand the architectural tradeoffs to reason about what each can and can't do. Classifier-free guidance (CFG) controls prompt adherence vs.
Base diffusion models give you creative possibilities. Adapters give you creative PRECISION. Master the three that matter most.
Flux Pro vs. Flux Dev. Midjourney vs. Stable Diffusion. The choice affects product architecture, cost, and what's possible. Here's the honest tradeoff.
Behind the glossy UIs, video models expose REST APIs. Here's how to call Sora, Veo, and Runway programmatically and build production pipelines.
ElevenLabs, Stable Audio, and Suno expose APIs for voice, SFX, and music. Here's how to compose them into a production audio pipeline.
Two families of provenance technology. One attaches signed metadata. The other embeds invisible patterns in the pixels or waveform. Here's how to implement both. The manifest contains ASSERTIONS (who captured/generated it, which tools/models, editing history, bounding boxes of AI-generated regions).
Who owns it? Who can you sue? Who indemnifies you? The commercial licensing landscape is fragmented, evolving, and critical to ship-safe work.
The winning pattern in 2026 is not AI-replacing-humans — it's AI-as-instrument. Figma, v0.dev, Canva, and editor workflows show how to compose it.
Consent, deepfakes, fair use, democratization of creation. The hardest questions in this track don't have clean answers. Let's work through them honestly.
Plan, build, and launch a real creative product using the full AI stack. This is the final deliverable of the Creative track.
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.
Assemble the four or five AI tools that actually belong in your daily life. A tested template for the stack that earns its keep.
Claude Projects, ChatGPT Projects, Notion AI, Perplexity Spaces. How persistent context changes AI from search box to actual assistant.
Every major AI product has a privacy page you've never visited. Here's what to click, toggle, and delete to keep your data yours.
Brand loyalty is a liability in AI. Learn the muscle memory of switching models, the signals that say 'time to swap,' and the anti-lock-in habits.
Perplexity Comet is a full web browser that treats AI as a first-class citizen. It reads, summarizes, and acts on pages you visit.
Sora 2 moved from consumer-only to API in 2026. 60-second 1080p video from a prompt, callable from code.
Black Forest Labs offers three Flux tiers. Schnell is free-speed, Pro is the paid flagship. Here is when each wins.
Flux Dev is the LoRA-friendly middle tier of the Flux family. Here is how to train a style on your own art without renting a farm.
Niji is Midjourney's anime-specialist model. Here is how to prompt it and when it beats general Midjourney for stylized art.
SDXL Turbo renders in a single step. That unlocks interactive, typing-to-image experiences you cannot build on slower models.
Calculus is where a lot of smart students hit a wall. Wolfram|Alpha and Claude can walk you through every step, but only if you already did the setup work.
Imaging AI plans the approach. The da Vinci 5 extends your hands. Autonomous suturing is creeping closer. But the surgeon still owns every blade.
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.
Autodesk Forma and generative design explore thousands of layouts while you sleep. The PE still owns every seal on every drawing.
Fusion generative design explores millions of topology options. nTopology and Ansys simulate in hours what used to take weeks. The ME still owns manufacturability.
Massing studies that took two weeks now take two hours. Here is what an architect actually does when the computer can draft.
AI reads every pitch deck that hits the inbox. Partners spend their time on what still matters — founder judgment and market taste.
Generative imagery, 3D garment sim, and on-demand pattern-making have collapsed the front end. Taste is still the scarce resource.
Pitchbook assembly, comps, and CIMs are now drafted by AI. The analyst still works late — on higher-leverage parts of the deal.
Syndromic surveillance runs on ER notes, wastewater, and social signals. The epidemiologist designs the study, interprets the signal, and briefs the public. An anomaly detection model has flagged a GI cluster in one district.
Site design, shade analysis, and permit packets run through AI. The work on the roof still runs through your hands.
Space planning, mood, and 3D viz have collapsed to hours. The designer still has to know what a room should feel like. What AI touches Concept renderings — text-to-image from existing room photos.
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.
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.
Figma's AI features (First Draft, Make Designs, Rename Layers) bring generative design to the industry standard. Deep dive on what it's changed and what's still a gimmick.
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.
Recraft focuses on style consistency, vector output, and brand workflows — things Midjourney still ignores. Deep dive on why designers and marketers are switching.
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.
Uizard turns hand-drawn sketches, screenshots, and prompts into editable UI mockups. Look at whether its 2026 AI upgrades make it a real Figma alternative.
Runway Gen-4 generates cinematic AI video from prompts. Deep look at its industrial-strength features, why studios use it, and the ethical firestorm around it.
ElevenLabs generates synthetic voices indistinguishable from human recordings. Deep dive on voice cloning, dubbing, the consent-and-ethics story, and pricing realities.
Suno generates full songs — vocals, instruments, lyrics — from a text prompt. Deep dive on what it sounds like, the industry lawsuits, and whether it's a toy or a tool.
Descript revolutionized podcast editing by making audio editable as text. Deep dive on Overdub voice cloning, Studio Sound, and the serious 2025 updates. Studio Sound — one-click AI noise reduction that makes laptop recordings sound studio-quality.
Pika Labs built a viral AI video product aimed at creators, not studios. Compare it to Runway and look at where it fits in 2026.
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.
Sudowrite is purpose-built for fiction writers. Deep dive on its Story Bible, Brainstorm, Describe, and Expand tools — and why novelists pay $25/month when ChatGPT is cheaper.
ShortlyAI was one of the first GPT-3 writing apps, now owned by Jasper. Look at whether the stripped-down approach still makes sense 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.
Motion schedules your tasks into your calendar automatically, rescheduling as priorities change. Look at whether it actually improves productivity or just feels busy.
Reclaim schedules tasks and protects habits on your calendar, but with a gentler touch than Motion. Look at why some users prefer it.
Superhuman was famous for fast email before AI. Now it bundles AI replies, auto-drafting, and AI calendar. Deep look at whether it's worth the premium.
ClickUp is project management, docs, goals, and chat all in one. ClickUp AI is its answer to Notion AI. Look at what it does inside the ClickUp ecosystem.
Consensus searches 200M+ academic papers and gives evidence-based answers. Deep look at how researchers use it, what it does differently from Perplexity, and its limits.
Elicit automates slow parts of academic research: finding papers, extracting data, building literature matrices. Look at what it saves PhDs 20 hours a week.
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.
Lindy builds AI agents that do jobs: handle email, qualify leads, schedule meetings. Deep dive on what it actually delivers vs the marketing.
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.
A deep tour of the canonical examples, Goodhart's Law, and why specification gaming is not a bug but a structural property of optimization. That is Goodhart's Law, originally formulated in monetary policy and now the most-cited one-liner in AI safety.
RLHF made ChatGPT possible. RLAIF is trying to take humans out of the loop. Here is the history, the trade-offs, and where the field is going.
Debate, amplification, weak-to-strong, process supervision. Research on how humans supervise models smarter than them.
What if you have to supervise a student smarter than you? OpenAI's 2023 paper asked that question by using GPT-2 to train GPT-4. The results were surprising.
Insurers price risk. As AI starts causing real losses, they are being forced to do it for AI. The resulting contracts are quietly becoming a major governance force.
Why the benchmark that was state-of-the-art three years ago is now useless — and what that teaches about measuring AI.
Public benchmarks get gamed. Private evaluations tell the truth but cannot be checked. Where is the balance? Third-party evaluators Organizations like METR (formerly ARC Evals) and the UK AI Safety Institute run closed evaluations on frontier models.
Evaluating models that see, hear, and read at once requires new kinds of tests. Here are the ones that matter.
Leaderboards are compelling. They are also deeply misleading. Here is a checklist for real skepticism. In reality, leaderboards hide a stack of choices that can swing the ordering: prompt wording, sampling settings, number of attempts, which subset of the benchmark is reported.
The eval that matters most is the one tied to your real task. Here is a step-by-step way to build one. The rubric is the product Most 'AI product' failures are actually rubric failures.
Some capabilities grow smoothly with scale. Others seem to appear out of nowhere. Telling them apart is a whole research program. The Big Question Is AI capability a smooth climb or a staircase?
Even accurate data can encode an unjust history. The COMPAS recidivism tool shows what happens when AI learns from a biased past.
Every labeled dataset has mistakes. Studies have found error rates of 3 to 6 percent in famous benchmarks like ImageNet. Noisy labels confuse models and mislead evaluations.
Saying the average is 50,000 dollars can mean three different things. Picking the wrong kind of average is how statistics starts lying to you.
Mean tells you the center. Variance and standard deviation tell you the spread. Without both, you are missing half the story.
A single weird value can distort your entire analysis. But outliers are also where the most interesting stories live. Knowing when to remove them is an art.
Thousands of companies you have never heard of trade your personal data every second. Understanding this invisible market is understanding modern privacy. Brokers and AI training Much training data for specialized models (ad targeting, credit scoring, risk assessment) comes from brokers.
Rumelhart, Hinton, and Williams published the algorithm that would eventually power everything.
In September 2012, a neural network crushed ImageNet and everything about AI changed.
Looking at AI's full history reveals rhythms that help make sense of the present moment.
Neural networks mix many concepts into each neuron. Sparse autoencoders pull them apart into human-readable features. This is the workhorse of modern interpretability.