Agentic Engineering: Orchestrating the Autonomous Development Lifecycle

I recently gave a talk on the shift from manual coding to Agentic Engineering.

The core of my argument is simple: If you can model a problem, AI can learn it and solve it. Engineering is just the first industry to witness this transition, but it is coming for all knowledge workers. We are moving from being creators of knowledge and processes to being architects of intent and communication.

Below are the interactive slides from the presentation.

Key Takeaways:

1. Coding is the 10%: Agentic tools are for the 90% (Planning, Testing, Reviewing).
2. Model it to Solve it: Focus on problem-modeling skills to stay ahead of the automation curve.
3. Pragmatic Problem Solving: Your new moat is the ability to orchestrate across domains and own the "What."

You can view the full-screen presentation here.