Breaking into Agentic AI Engineering New

Agentic AI is the fastest-moving area in software right now — and most developers don't know where to start or how to stand out in it.

What we'll cover (tailored to your background):

• What agentic AI engineering actually is — and how it differs from basic LLM API calls • Key concepts: agents, tools/function calling, memory, orchestration, multi-agent systems

• Frameworks and tooling worth learning (LangChain, LangGraph, CrewAI, AutoGen, custom builds)

• How to build your first real agentic project and what makes a portfolio piece stand out

• How to position yourself and your existing full stack skills to transition into AI engineering roles

• What companies are actually hiring for — and how to read between the lines of AI job descriptions

This session is for full stack developers who want to understand what agentic AI engineering actually means in practice: building systems where LLMs don't just respond to prompts, but plan, use tools, make decisions, and take multi-step actions autonomously.

Whether you're curious about the space, actively building something, or trying to pivot your career toward AI — this session will give you clarity on where to focus.

Who is this for?

Full stack developers who want to work with AI beyond just calling the OpenAI API — developers who want to build the systems that make AI actually do things.