Most full stack developers already use an AI coding assistant. Fewer use it well, because AI for full stack developers is as much about reviewing code as generating it. It’s easy to accept generated code that looks right, ship it, and discover later that it skipped validation or broke an edge case. GenAI & Agentic AI for Full Stack Developers is a 12-hour course about using AI across the whole development workflow while staying in control of what ships.
This guide covers what’s in it, how it’s assessed, and who should choose something else.
AI for full stack developers: the course at a glance
| Format | Live online |
| Hours | 12 |
| Modules | 6: three generative AI and three agentic AI |
| Tools | GitHub Copilot, Cursor, and Claude Code, with workflows that apply across languages and stacks |
| Project | One running feature built across every module: frontend, backend, tests, and docs |
| Prerequisites | Python for AI (6 hours), working knowledge of at least one modern stack, comfort with Git, code review, and basic testing |
| Assessment | An applied final exercise (fix a seeded bug and extend your feature) plus a short final test |
| Price | $450 or ₹25,000 |
Additional discounts are available. Contact us to know more.
The six modules
| Module | Type | What you practice |
|---|---|---|
| Frontend component generation | Generative AI | Turning UI requirements into working components, then reviewing and refining them |
| Backend logic, API, and database generation | Generative AI | Generating logic, OpenAPI contracts, schemas, and queries from requirements |
| Technical documentation | Generative AI | Docstrings, READMEs, PR descriptions, commit messages, and design docs |
| Code review, security, and standards | Agentic AI | Catching bugs, OWASP Top 10 issues, secrets, and standards violations before they ship |
| Testing and test automation | Agentic AI | Generating tests, finding edge cases, integration tests, and coverage analysis |
| Debugging and root cause analysis | Agentic AI | Investigating logs, stack traces, profiling data, and reproduction paths |
Generative vs agentic, in this course
The split is practical. In the generative modules, a requirement goes in and code or docs come out, and you review them. In the agentic modules, the AI works through several steps on its own, across files, logs, or a whole diff, before giving you something to review. The second kind saves more time, and it’s also where unreviewed output does more damage, which is why the course puts so much weight on questioning and rewriting what the AI produces.
Number of modules by stage
Source: AgileFever course curriculum, October 2026. Grouping is ours.
Half of the course is about checking and fixing code rather than generating it. That matches where AI-assisted development usually goes wrong.
A review habit worth taking away
Whatever tool you use, these checks catch most problems in generated code:
| Check | What to look for |
|---|---|
| Inputs | Is user input validated and escaped? Generated code often trusts it |
| Errors | What happens on a timeout, an empty result, or a failed write? |
| Secrets | Are keys or credentials hard-coded, logged, or sent to the client? |
| Tests | Do the generated tests check behavior, or only that the code runs? |
| Fit | Does it follow your codebase’s patterns, or introduce a new library for one function? |
Who it’s for, and who it isn’t
It suits full stack, frontend, and backend developers, software engineers, and technical leads who want AI in their daily workflow and want to own code quality on their team. It isn’t only for experienced developers; it’s designed for people at different stages who already work on a real stack.
It deliberately doesn’t teach building AI products such as RAG apps, agents, or LLM features. For that, take the GenAI and Agentic AI BootCamp (74 hours).
Upcoming start dates
| 2026 | 2027 |
|---|---|
| November 19 | January 21 |
| December 10 | February 18 |
| – | March 18 |
| – | April 22 |
The price is $450 in the US or ₹25,000 in India. Check the course page for session times.
Additional discounts are available. Contact us to know more.
FAQ
Will I still write code?
Yes. AI speeds up the repetitive parts, but you review, verify, and own everything that ships.
Which languages does it support?
The workflows apply across modern stacks and languages.
Is there an exam?
Yes: an applied final exercise and a short final test. Pass both to receive the certificate.
What to read next
If you’re weighing a move into client-facing AI work, read What is a forward deployed engineer? For testing AI-generated code and AI features, see the QA and test engineers course guide.
