Humans struggle to grasp exponential technological progress, leading to phenomena like "retromania" and hype cycles around innovations like AI.
AI represents an inflection point similar to the industrial and digital revolutions, which disrupted businesses like Kodak and Nokia that failed to adapt.
AI has evolved through several phases, with recent agentic AI having a surprisingly fast and significant impact on the software engineering industry first.
AI can be leveraged at every stage of the software lifecycle, from refining requirements and writing documentation to coding, managing pipelines, and customer service.
AI tools can diagnose production issues, suggest command-line fixes, and automate incident management tasks like engineer assignment and root cause analysis.
AI agents can autonomously handle development tasks by taking a natural language issue, creating code, and submitting a pull request, with the entire process visible in GitHub Actions.
By integrating Azure Monitor as a context source, AI agents can react to production alerts, analyze logs, and automatically propose infrastructure-as-code fixes.
Adopting AI agents requires a cultural shift from a rigid product focus to a flexible process focus, embracing experimentation and a growth mindset to avoid being blocked by fear.
The role of an engineer is shifting from writing and reading code to managing complex systems and interacting with AI, making creative problem-solving more valuable than ever.
39:11Thomas Dohmke
23:33Oliver Will
26:35Ricardo
27:33Romano Roth
26:54Marcel Scherenberg
27:07Eric Jadi & Rene Pajta
29:00Hanna Hennig, Michael Ameling & Tobias Regenfuss and Mike Butcher
28:09Jan Oberhauser, Mirko Novakovic, Alex Laubscher & Keno Dreßel
Jobs that call for the skills explored in this talk.
Devoteam