Agile methodologies were designed to reduce uncertainty and risk in the software
development lifecycle. By breaking down complex problems into smaller,
manageable steps, Agile promoted higher adaptability, continuous improvement,
and accountability. These methods acknowledge complexity and tackle it, one
piece (or pizza slice) at a time. But with the advent of AI, speed is now of the essence. AI tools are now able to analyse both the finer details and the bigger picture simultaneously. As a result, parts of the process that once demanded human ownership and attention are now
passed onto AI systems to achieve.
And that furthermore raises the question, If AI handles complexity for us, what
happens to the discipline of understanding the problem, and finding the solution? Why not have people with the ask + the context just build it themselves?
How does Agile fit into the age of AI?
Key Takeaways:
1) Current state of AI tooling – real examples at enterprise scale
2) The original benefits of Agile – and how AI makes them redundant
3) What businesses really value
4) The move from waterfall > Agile > AI … the same continuum?
5) Clarity on where the industry is heading
- Date:14/02/2026
- Time:11:40
- Event:Reimagining Agile: Transformation in the Age of AI @Bengaluru
