Keeping Up with AI: What to Learn, Try, and Ignore

New models, new tools, new frameworks—and a growing list of things you feel like you should already know. Keeping up with AI can feel like a full-time job.

Join Columbus AI Engineering for a practical discussion about deciding what deserves your attention and turning that learning into useful skills.

We’ll cover:

• Building T-shaped knowledge: Develop enough breadth to understand the AI landscape, then go deep in one area where you can build real expertise.
• What to learn: Prioritize foundational concepts and skills that remain useful as tools change.
• What to try: Evaluate new models and tools through small, focused experiments connected to problems you actually have.
• What to ignore: Filter out hype, distractions, and developments that aren’t relevant to your goals.
• Making it sustainable: Build a manageable routine for finding useful information, practicing, and sharing what you learn.

Whether you’re getting started with AI or already building with it, this session will help you make more deliberate choices about where to spend your time.

Bring your favorite learning resources—and something you’re trying to figure out whether to learn, try, or ignore.