Tackling the AI value delivery paradox
AI Summary
While AI tools enable engineers to write code faster, many organizations fail to see improvements in time-to-market. This AI value delivery paradox occurs because deploying agentic AI without adapting the surrounding architecture and processes merely stresses the software value chain rather than accelerating it. To solve this, organizations must evolve their tech estates and structures by categorizing components into autonomous 'cells' for product development and machine-readable 'tissue' for cross-cutting governance and guardrails.
Key Takeaways
- AI code generation increases throughput in the inner loop, but requires structural readiness to prevent system failures.
- The 'tissue' handles cross-cutting concerns like security, identity, and compliance using machine-readable policies and automated guardrails.
- Engineers must evolve from direct coders to orchestrators, utilizing human-on-the-loop practices to manage autonomous agents.
Why it matters
Unchecked AI code generation without architectural and organizational evolution creates bottlenecks, technical debt, and team burnout. Understanding how to structure cells, tissues, and human-on-the-loop engineering allows engineering leaders to safely harness AI velocity without degrading EBITDA, security, or customer experience.
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