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AI Training for Developers
Learn to Build, DeployAI Systems with LLMs
A 4-week live AI bootcamp for engineers who want to build repeatable workflows, reliable evals, and production-grade systems with LLMs at the core. No theory. No fluff. Just systems that hold up in production.
- 4 weeks
- Live, online (part-time)
- 3 hours/week
$2,000 pilot price · was $4,000
4 weeks
Program duration
Live, online
Part-time format
3 hrs/week
Time commitment
$2,000
Pilot launch price
The state of AI in engineering
60-70%
of developers rely on AI-generated code they don't fully understand
<20%
have any form of evals or testing layer for AI outputs
4 weeks
of live, hands-on instruction built around real code
8
participants max per cohort for real feedback, not a webinar seat
3 hrs/week
part-time commitment designed for working engineers
Lifetime
access to templates, prompt libraries, and session recordings
Trusted by engineers from top companies
The real problem
The gap isn't AI usage. It's reliability.
Developers are shipping AI without context, evals, and guardrails, which results in outages, bad code, and silent failures.
Developers who use AI like a vending machine become redundant. Developers who build systems with it become indispensable.
- 60-70% of developers rely on AI-generated code they don't fully understand
- Fewer than 20% have any evals or testing layer for AI outputs
- AI can already generate junior-level code in seconds
- The difference between redundant and indispensable is systems, not usage
Curriculum
Four modules. One production-grade AI system.
Module 01 of 04
Module 01: Foundations & AI Workflow Integration
- How modern LLMs actually work and where they fail for engineering tasks
- Moving from reactive prompting to structured prompts with role, context, and constraints
- Integrating AI tools (Cursor, Copilot, Claude Code) into your daily workflow
- Configuring repo-level AI context and rules for your codebase
- Establishing prompt standards and reusable context files
- Owning AI-generated code instead of becoming its reviewer
Outcomes
What you'll be able to do.
01
Stop shipping code you haven't fully read or don't fully own
02
Build prompts and workflows you can reuse and trust across your codebase
03
Add evals so you catch AI failures before they hit production
04
Use LLMs as a core part of your stack, not just autocomplete
05
Design structured prompts with role, context, and constraints
06
Build agents with scoped tools, guardrails, and rollback triggers
07
Configure repo-level AI context tailored to your codebase
08
Ship a production-ready internal AI tool by the end of the program
Tools & tech
The stack you'll master.
You'll work hands-on with the tools real engineering teams ship with, then wire them into workflows, evals, and MCP-connected agents you fully own.
Cursor
GitHub Copilot
Claude Code
ChatGPT
Google Gemini
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Lovable
Replit
Windsurf
v0
MCP (Model Context Protocol)
React
JavaScriptWho this is for
Strictly for working developers.
For professional developers who already write code for a living and want to stay ahead of the AI curve. Not for PMs, designers, non-coding founders, or beginners.
You should already ship code. This is a fast, senior-level program - we build on skills you already have.
- Frontend, backend, fullstack, data, and DevOps engineers
- Already using Cursor, Copilot, or Claude Code but want more value
- Have shipped LLM-powered features with no testing framework
- Want to build agents or MCP-connected tools safely
- Mid-to-senior engineers staying ahead of the AI curve
Without vs with AI training
From reactive to designed.
The program moves you from reactive, unreliable AI use to designed, eval-backed systems where AI executes within constraints you set.
Without AI training
With AI training
Reactive prompting
Structured prompts with role, context, and constraints
AI writing code you don't own
You designing the system AI executes within
LLM features with no evals
Pipelines with test sets and scoring rules
Agents that go rogue
Agents with pre/post hooks, scoped tools, and rollback triggers
AI as a crutch
AI as a force multiplier on your judgment
Becoming the reviewer of AI output
Becoming the engineer who designed the system
What you walk away with
Tangible deliverables that stay yours.
Every participant ships reusable deliverables embedded in their actual workflow, all of which remain their property.
A Developer AI System: prompt standards, context rules, reusable workflows
A repo-level AI setup configured for your codebase
A multi-step LLM workflow with validation and checkpoints
An eval system with test cases and a reusable scoring harness
An agent with tools and guardrails built on MCP with scoped access
A pre-deployment reliability layer with rollout checklists
A shipped, production-ready internal AI tool
A documented Developer AI Standard with prompt versioning guidelines
How the program runs
Live, cohort-based, capped at 8 engineers.
Everyone gets real feedback, not a seat in a webinar. No upsells, no tiered access - everyone gets everything.
- All 4 weeks of live instruction
- Weekly office hours with structured Q&A and peer learning
- Weekly assignment reviews with real expert feedback, not rubric-based
- Live on-demand support for mid-week assistance
- Final project build clinic with peer review
- Lifetime access to templates, prompt libraries, and session recordings
What engineers say
Systems that hold up in production.
"Metana's AI training changed how our whole team ships. We went from guessing whether AI output was safe to having evals that catch failures before they reach production."
Senior Engineer
Fintech team lead
"I already used Cursor and Copilot every day, but this was the first time I learned to build reusable workflows and guardrails around them instead of just prompting and hoping."
Fullstack Developer
SaaS startup
"The final build clinic alone was worth it. I shipped a production internal AI tool with real test cases and peer review, not a toy demo."
Backend Engineer
Enterprise platform team
Why Metana
Forbes Best
Coding Bootcamp 2024
Featured on
Course Report
A bootcamp engineers actually respect.
Participants come from leading technology, finance, and engineering organizations - Google, Amazon, Microsoft, Meta, Netflix, IBM, plus Web3 teams from ConsenSys, Polygon, Binance, Coinbase, and Algorand. Metana is recognized as a top coding bootcamp, named a Forbes Best Coding Bootcamp and featured on Course Report.
Forbes BestCoding Bootcamp 2024
Featured onCourse Report
FAQ
Questions, answered.
A 4-week live bootcamp by Metana for working engineers who want to build reliable, production-grade AI systems, not just use autocomplete. You'll learn to design structured LLM workflows, write evals, build agents, and ship AI-powered features that actually hold up in production. No theory, no fluff; every session is built around real code.
Enrolling a team? Cohorts are capped at 8 for real feedback. Reach out at info@metana.io to arrange team enrollment.
Talk to a Metana expert
Book a call with a real engineer before the next cohort fills.
Speak with an advisor. We'll map the right program to your goals - and lock in your enrollment offer.