The CIO’s guide to agentic engineering
Understand the real cost of AI-generated code and the growing impact of technical debt
Reduce security and reliability risks introduced by AI-assisted development
Improve visibility and governance over AI-generated applications and decisions
Adopt a model-first architecture that makes applications easier to maintain and audit
Capture AI's productivity gains without sacrificing control, compliance, or long-term ROI
Build enterprise apps at AI speed without compromising reliability. This paper explores why many organizations are discovering that AI-generated code can introduce hidden costs, new security risks, and long-term maintenance burdens that weren't part of the original business case.
As AI accelerates software delivery, enterprises face tougher questions around cost, reliability, security, and governance. The challenge isn't whether AI should be part of development-it's how to ensure what gets built can be trusted, maintained, and scaled.
The organizations that win won't be the ones generating the most code. They'll be the ones building systems that remain reliable, auditable, and sustainable over time. This paper helps IT leaders:
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