TPEE Learning Center — all 83 free lessons

Learn how Mixture of Agents uses multiple LLM agents in layers to improve answer quality.

Understand what an LLM is and why clear prompts matter.

Use the 12 TPEE sections deliberately.

Walk through creating your first complete prompt from start to finish.

Recognize and avoid the most common errors new users make.

See a complete real-world example from initial need to final prompt.

Leverage built-in templates instead of starting from scratch.

Learn to save, name, and find your prompts effectively.

Understand all the ways to get your prompt out of TPEE and into AI tools.

Understand how to work with others using TPEE's team features.

A concise checklist to follow for every prompt as a new user.

Run large language models locally on your own machine with Ollama.

Understand Obsidian as a free, private, local-first Markdown note-taking and knowledge-base app, and how it pairs with Graphify to browse the TPEE project graph.

Read the ASCII table and understand why 7-bit ASCII is the foundation of digital text.

Master what tokens are, how tokenizers work, and why token limits affect cost and quality.

Budget prompt size, attachments, and long conversations.

Choose models based on risk, context, speed, and price.

Know what Ollama is and how TPEE should describe it safely.

Understand LM Studio as a separate local model application.

Learn the skill of refining prompts based on AI responses.

Diagnose common problems with AI outputs and fix them systematically.

Understand how LLM evaluation harnesses let you benchmark, compare, and validate large language models using reproducible tests.

Understand Hermes Agent as a self-improving, terminal-native autonomous AI agent and how to work with it effectively.

Use OpenRouter as a unified gateway to many LLM providers and models.

Explore Open Code as an AI coding platform and how 'Zen' simplicity plus the Go language fit into modern AI-assisted development.

Run, chat with, and serve large language models locally and offline using LM Studio.

Understand OmniRoute as a free, open-source AI gateway that gives one local endpoint access to hundreds of LLM providers with automatic fallback.

Understand how Graphify turns a codebase into a queryable knowledge graph so AI coding assistants can answer architecture questions cheaply and accurately.

Understand Unicode code points and UTF-8 so multi-language and emoji text is handled correctly.

Understand how Unsloth makes running and fine-tuning large language models fast, memory-efficient, and local-first.

Use Cursor, VS Code, Claude Code, Codex CLI, and other tools with the right prompt shape.

Reduce unsupported answers and verify important work.

Protect confidential work and understand TPEE's offline rule.

Understand when multiple AI roles help and when they add risk.

Turn AI into a repeatable work system.

Use role, task, constraints, examples, rubrics, and iteration patterns like a specialist.

Diagnose why an AI answer was weak and improve the prompt deliberately.

Judge AI output with measurable criteria instead of personal feeling.

Know when a human must decide and when AI output is only advice.

Understand retrieval augmented generation and why grounding documents matter.

Understand how semantic search finds related meaning rather than exact words.

Prepare documents, logs, code snippets, and examples so AI can use them correctly.

Understand CPU, GPU, NPU, RAM, VRAM, and storage bottlenecks.

Choose between FP16, INT8, INT4, quality, speed, and memory use.

Choose cloud, local, or hybrid AI based on privacy, cost, speed, and quality.

Use AI for coding without breaking working software.

Prompt effectively for Rust, C, embedded systems, and hardware/software work.

Make AI-generated work prove itself.

Use AI to find risks without exposing secrets or creating unsafe instructions.

Protect business information and respect legal boundaries.

Use AI for proposals, support, operations, sales, and management.

Apply AI safely in electrical, wholesaler, tradesman, and field-service contexts.

Control style for customers, engineers, students, managers, and executives.

Avoid surprise costs and keep workflows efficient.

Select a model based on task type, risk, speed, privacy, and available context.

Design useful AI teams instead of noisy role lists.

Understand OpenClaw-style products and where they fit in the AI workflow.

Understand Paperclip-style control planes for many AI agents.

Turn repeated AI success into a personal or company standard.

Understand when to choose GPT-5.5, Claude Opus 4.8, Gemini 3.5 Flash, DeepSeek V4, or Grok 4.3.

Choose the right model size based on task complexity, cost, and hardware constraints.

Select the optimal model for programming tasks based on complexity and language.

Choose models that excel at writing, marketing, documentation, and creative tasks.

Pick models that excel at research, data analysis, and structured reasoning.

Understand when and why to use vision-capable AI models.

Understand reasoning models like o3-mini and DeepSeek-R1 and when to use them.

Choose the right local models (Llama, Qwen, DeepSeek, Mistral) for your hardware and needs.

Build efficient AI workflows that minimize cost while maintaining quality.

Understand Moonshot Kimi's capabilities and when to select this Chinese frontier model.

Understand DeepSeek's open-weight models and their cost/performance advantages.

Understand Qwen's multilingual strengths and deployment options.

Understand regional AI models from Singapore and Southeast Asia.

Understand different approaches to AI development across regions.

Learn specific scenarios where Asian models provide advantages.

Understand regional considerations and access methods for Asian AI models.

Understand the price/performance benefits of Asian AI models.

Understand specialized coding models from Asian developers.

Understand emerging trends and future directions in Asian AI.

Improve any prompt by first conversing with the AI ABOUT the prompt - the method behind TPEE's Prompt Enhancing Workflow.

Combine all lessons into a safe professional checklist.

Review the full professional AI skill set and prepare for future course expansion.

Master the complete model selection decision framework.

Learn without cheating and use AI as a tutor.