Open the repository
Use the public GitHub course as the durable curriculum and working reference.
github.com/tbhrc/Course-Agentic-AI →
Free public course by iMPLEMENTAi
Learn Agentic AI by building real agents.
A practical, build-first course for learning how to operate, control, build, test and improve useful AI agents and agentic systems — from one reliable agent through Skills, GitHub, Codex, APIs, MCP, evals, multi-agent architecture and production thinking.
No registration. No gated modules. The repository is the course.
100% freeBuild-firstVendor-light fundamentalsCurrent tools included
The standard
Do not just learn what an agent is. Learn how to operate one.
The course turns concepts into files, diffs, Skills, tool calls, evals, failures, repairs and verified outcomes.
You graduate when you can take a new problem and independently architecture, build, test, debug and explain the agentic system.
Start in three steps
Give the repository to your AI and make it coach you through the work.
The course is designed to be operated with a capable AI learning coach, not consumed like a static textbook.
Give it to your AI
Tell ChatGPT, Codex, Claude or another capable agent to read the root AGENTS.md and act as your practical course coach.
Build, inspect, verify
Complete the labs, create durable artifacts, inspect changes, diagnose failures and explain the result back in your own words.
Open and work from https://github.com/tbhrc/Course-Agentic-AI. Read the root AGENTS.md first. Act as my practical Agentic AI learning coach. Start with course/00-start-here.md and follow the course in order. Make me perform the exercises, inspect changes, debug failures, verify outcomes and explain what I learned back to you.What you will learn
From one useful agent to production-grade agentic systems.
The sequence deliberately keeps complexity late. You learn to control one agent before earning more agents, more state or more infrastructure.
Operate one agent well
AI mental models, Agent Briefs, project instructions, context and verification.
GitHub + reusable Skills
Files, Markdown, Git, diffs, repositories, Skills and smart-agent-first operating patterns.
Codex + coding literacy
Supervise coding agents, understand data flow, read diffs, test, debug and roll back.
APIs + tools + MCP
Tool contracts, auth, state changes, source-of-truth verification and reusable connectivity.
State + evals + safety
Context vs memory, fault isolation, regression testing, prompt injection and real permission boundaries.
Multi-agent + production
Smallest useful architecture, handoffs, specialists, observability, recovery, cost and deployment thinking.
Current practice layer — September 2026
Learn the principles, then open the hood on real harnesses.
The fundamentals should outlive today's tooling. But you should still practise with useful tools that exist now.
A deliberately minimal harness.
Pi is useful for learning because extensions, Skills, prompt templates and packages remain visible. Start with one agent, then add capability only when the baseline proves a gap.
Explore Pi →A plugin-composable harness in developer preview.
Explore Standard, Code, Minimal and Creator modes while inspecting how models, tools, Skills, sessions, sandboxes, storage, loops and UI compose around an agent.
Explore DeepSeek Harness →These specific tools are a maintained practice layer, not permanent dependencies. The course tells learners to verify their current official documentation before use.
Where the course came from
Built from the operating methods we use to implement AI around real businesses.
iMPLEMENTAi publishes the course openly. The commercial work is optional: use the material yourself, or work with us when you want the same principles applied to your own workflows, context, systems and team.
iMPLEMENTAi
Customising AI around how your business actually works.
We connect the tools a company already uses, add approved company context, build reusable Skills and workflows, configure permissions and test the setup on real business work.
Deeper operating layer
When individual workflows are not enough, there is FolderDesk.
The course teaches why AI should not depend on one long conversation. FolderDesk takes that principle further: durable business context, reusable Skills, connected systems, operating knowledge and verified agent work in one business operating environment.
Most learners do not need FolderDesk to complete the course. It becomes relevant when real work needs continuity across tasks, files, systems, people and agents.
AI Build With You
Hands-on implementationUse the free course yourself. Bring us in when you want to apply the same method around your real business.
AI Build With You is iMPLEMENTAi’s recurring done-with-you engagement for founders and operators who want to keep learning while useful AI capability is built into the business.
FolderDesk visualised
One operating environment for humans, AI agents, execution and business truth.
This is the deeper architecture behind the course principles: people and agents work through one operating environment, reusable agent capability sits underneath it, execution connects to real tools, and durable business state remains with the right systems of truth.
FAQs
A few things to know before you start.
Is the Agentic AI course really free?
Yes. The complete repository is public on GitHub and there is no registration gate for the curriculum or labs.
Do I need to be a programmer?
No. You will learn enough coding literacy to inspect, supervise and debug AI-built systems, but the course is not a conventional programming bootcamp.
Is the course tied to ChatGPT or one model?
No. It teaches durable agentic principles and uses current tools where they are useful. The current practice layer includes Codex, Pi and DeepSeek Harness and is expected to change over time.
What if I want help applying this to my company?
Start with the course. If you want hands-on help, book the free AI Implementation Session or use AI Build With You for recurring done-with-you implementation.
Start free
Build your first reliable agent. Then keep going.
The GitHub repository contains the full curriculum, labs, prompts, playbooks, graduation test and continuation path.