Mecha Build
Turn an idea into a working AI app, automation or system
Strategic Value (Why this program?)
Mecha Build is where you build. Start from the problem, create an app or automation, connect real data, add RAG and agents when useful, and understand local/private AI without turning the journey into a theory-heavy engineering course.
Expected Return on Investment (ROI)
Turn an idea or problem into a working prototype.
Connect your app to real services and data and build useful automation.
Know when RAG, agents or local AI are actually the right choice.
Not just content — each part connects to something you will use or build.
The program combines understanding, hands-on practice and a clear output you can review and keep improving after the program.
Who is it for?
For founders, idea owners, product managers, freelancers, developers, marketers, automation specialists and practical builders — including non-developers.
What will you build?
A testable AI product or system solving one clear problem, with a demo and post-program iteration plan.
Included resources
Build Kit: product briefs, automation maps, RAG/agent checklists and launch checklist.
From concept to result in four steps.
The rhythm stays practical: understand, practice, build, then review the output instead of stopping at passive learning.
Understand
The idea, its limits and the right use case.
Practice
A task or workflow around a clear scenario.
Build
An output you can use or present.
Review
Test quality and improve the result.
Tools may change between cohorts when a better fit appears; the goal is to master the workflow, not memorize a tool name.
Academic Curriculum (9 Intensive Lectures)
1. Turn an Idea into a Problem Worth Solving
- Define a clear use case
- Identify user and desired outcome
- Decide what is worth building
Start with the problem, not the tool. Turn an idea into a small product or system with a clear user, inputs, outputs and success measure before generating code.
2. Build Apps with AI without Technical Noise
- Structured vibe coding
- Simple UX and interfaces
- Testing and debugging AI output
Build a working application with AI as a building partner while understanding enough structure, data and failure modes to stay in control of the result.
3. Automate Real Workflows
- Triggers and actions
- Connect forms, email and CRM
- Practical webhooks and APIs
Design an end-to-end workflow that replaces repeated manual steps, handles decisions, records outcomes and includes basic error handling.
4. RAG: Make AI Work with Your Knowledge
- Prepare knowledge
- Retrieval and search
- Reduce unsupported answers
Build an assistant grounded in specific files or knowledge sources and learn how to evaluate retrieval quality rather than relying on a polished demo.
5. Agents that Execute Multiple Steps
- Agent loops and tools
- Human approvals
- Task decomposition and review
Learn when an agent is useful and when a normal workflow is better, then build a controlled agent with tools and clear review points.
6. Connect Real Data and Services
- Authentication basics
- Databases and APIs
- Permissions and secrets
Move from an isolated prototype to a system connected to real services or data while keeping credentials and permissions properly separated.
7. Private and Local AI without the Hype
- When local AI makes sense
- Ollama and open models
- Private RAG and privacy
Understand the cost, privacy and performance tradeoffs, run a local model and decide whether your case should be cloud, local or hybrid.
8. Quality and Safety before Launch
- Practical testing
- Logs and monitoring
- Prompt injection and data exposure basics
Test the system as a product, define failure cases, monitor outcomes and add basic controls against misuse or sensitive-data exposure.
9. Capstone: Build Something People Can Use
- Integrate app, automation and AI
- Measure value
- Demo and next-step planning
Combine the program into one focused product or system that solves a real problem, can be tested and has a measurable reason to exist.
Technical Documentation
Build Kit: product briefs, automation maps, RAG/agent checklists and launch checklist.
Final Capstone Project
A testable AI product or system solving one clear problem, with a demo and post-program iteration plan.
Important questions about the program
Do I need a technical background?
Is the program actually hands-on?
What is the difference between Online and On-site?
Are the tools fixed?
Choose Online or On-site before sending your details.
Compare the experience and price, pick the format that fits you, then complete a short application without making the same decision twice.