Become the 10x Engineer Companies Want to Hire

It's a 4-week, part-time (15-20 hrs/week) program for working engineers with 1+ years of experience who already know how to code and want to work dramatically faster with AI. Across four weeks you go from AI-assisted development fundamentals in week 1 (Cursor, Claude Code, GitHub Copilot, and Windsurf as daily drivers) through AI-powered testing, debugging, and code review in week 2, building real RAG systems and reliable agents with MCP in week 3, and production concerns - observability, evals, caching, fallbacks, rate limits - plus a capstone presented to hiring engineers in week 4. You leave with 3-5 production-grade projects live in your GitHub, not tutorial screenshots. Cohorts are capped at 24 seats, and the program is backed by a job guarantee or 100% tuition refund, depending on which plan you choose at enrollment.

Engineers with at least 1 year of professional experience who already know how to code and want to move faster without cutting corners, stay valuable as AI reshapes the job description, ship better work with less grunt work, and walk into interviews with real proof instead of buzzwords. It's built for people already shipping code who want a structured system rather than scattered tutorials - not complete beginners. If you want a magic prompt pack that replaces engineering judgment, want AI to think for you, or are looking for a shortcut around the actual work, this isn't the right fit. If you're just learning to code from scratch, start with Metana's Software Engineering Bootcamp instead, then come back once you're already building production software. Cohorts are capped at 24 seats so mentorship and code review stay genuinely hands-on, and the part-time schedule (15-20 hours a week) is built around keeping your current job running while you upskill, not pausing your career to attend full-time.

There are two plans. Plan I is $3,000 and covers the AI tools training only - a fit for engineers who want the technical curriculum without the career-services layer. Plan II is $7,500 and includes the full AI tools training plus 6 months of career support, 1-on-1 career coaching after graduation, and the job guarantee; broken out by value, that's roughly $9,000 of JobCamp career services plus $4,000 of AI Bootcamp training for $7,500, a $5,500 saving versus paying for each separately. Every plan, regardless of tier, includes 1 month of Claude Code Max ($200 value) at no extra cost, access to the private engineer community and token-burn leaderboard, and lifetime access to curriculum updates as the tooling changes. Book a call if you're unsure which plan fits your situation - an advisor can walk through the trade-offs against your current employment status.

The job guarantee applies if you're unemployed at enrollment and you're on Plan II. You graduate, follow the job-search plan - completing all 4 weekly projects plus the capstone, applying to a set number of roles per week, attending coaching, and using the provided frameworks - and if you still don't land a qualifying offer within the agreed window, you get a 100% tuition refund. If you're already employed when you enroll, the guarantee itself doesn't apply, but the career team still helps with hiring-partner introductions, interview prep, and salary negotiation until you land the new role you're after. There's also a separate, unrelated 3-day, no-questions-asked money-back window measured from cohort start, for anyone who decides early on that the program isn't the right fit. Placement coaches are paid based on your outcomes rather than a flat fee, so their incentive lines up with getting you an actual signed offer letter.

You'll work hands-on across six categories of the modern AI engineering stack: IDEs and coding assistants (Cursor, Claude Code, Windsurf, GitHub Copilot), models and APIs (OpenAI, Anthropic, Gemini, Llama, Mistral, Groq, OpenRouter), frameworks (LangChain, LangGraph, LlamaIndex, Vercel AI SDK, Pydantic), vector and data tools (pgvector, Pinecone, Weaviate, Supabase), agents and automation (MCP servers, n8n, Browserbase), and eval and observability platforms (Braintrust, Langfuse, Helicone, Promptfoo). Rather than teaching each tool as an isolated party trick, the curriculum threads them through real weekly builds - a legacy-codebase refactor, a test-automation pipeline, a RAG system with evals, and an unattended agent - so you learn the underlying workflow. Since specific tools change roughly every six months, the emphasis stays on the engineering judgment that transfers between them - reading model output critically, designing evals, and knowing when an agent, not a simpler script, is actually the right tool for a task.

Tutorials show tricks; this teaches a system, and the difference shows up in outcomes. Self-study typically means 6-12 months of scattered tutorials and half-finished courses, no real sense of what hiring managers actually test for in an interview, and side projects that never quite ship because there's no deadline or feedback loop forcing them to. This bootcamp compresses that into 4 weeks of structured, tested curriculum with a real project shipped every week, mock interviews with real hiring engineers instead of guesswork, 3-5 production-grade apps with live URLs in your GitHub rather than half-finished repos, and a job-search system with actual hiring-partner introductions instead of cold-applying to hundreds of jobs and hearing nothing back. Tutorials give information; a structured cohort gives feedback on your specific code, which is the part self-study can't replicate no matter how many videos you watch.

Cohorts are capped at 24 seats to keep the pairing, mock interviews, and coaching genuinely personal rather than a mass-market course. Upcoming cohorts: Cohort 04 starts May 12, 2026, with applications due by May 5; Cohort 05 starts Jul 07, 2026, with applications due by Jun 30; Cohort 06 starts Sep 01, 2026, with applications opening soon. Seat availability changes as each cohort fills, so the numbers shown on this page reflect current openings rather than a fixed allocation - book a call to confirm exactly how many seats are left in the cohort you're targeting, and to check whether your start-date preference lines up with an open application window before you commit to a plan. Applying takes about 15 minutes and doesn't commit you to anything - it's a short conversation about your background, current stack, and what you want to ship next.