Insights
Written by Frank Callaly
See where your engineering organisation sits on the journey from ad hoc AI adoption to an integrated, agentic SDLC.
AI has the potential to significantly accelerate software delivery, but moving from individual tools and experiments to meaningful enterprise impact requires more than simply giving engineers access to AI.
The Agentic SDLC maturity model outlines three stages of adoption – Ad Hoc, Assisted and Integrated – and the capabilities organisations need to develop as they progress.
Download the maturity model to explore how engineering teams can move from fragmented AI usage and unmanaged costs towards governed, token-efficient agent workflows, automated validation and enterprise velocity.
Per-token prices have collapsed. Enterprise AI bills have not. The gap between those two facts is where most engineering leaders are currently losing the ROI argument, and it is not a pricing problem.
A 10-point diagnostic to assess whether your engineering organisation is ready to scale agentic AI safely across the SDLC.
An insight briefing exploring the SDLC trends, talent shifts and leadership priorities shaping banking and insurance through 2026.