The AI ROI Playbook: How ROI Is Won in Production, Not the IDE
The AI ROI Playbook: How ROI Is Won in Production, Not the IDE
Most AI investments focus on visible productivity gains in coding. But in regulated, high-stakes environments, the real costs emerge after code ships during incidents, degraded performance, emergency changes, and audit pressure. This guide explains why production is the bottleneck for ROI and how AI for prod creates a compounding advantage by reducing evidence latency and increasing decision confidence.
Why AI ROI stalls in the IDE, and why the majority of engineering time and cost shows up between tools in production.
What breaks with LLMs, tool augmented LLMs, and single-agent systems in production, and why multi agent coordination is required.
How AI for prod changes incident response, brownfield development, release readiness, cost optimization, and compliance workflows.
How to assess your maturity across manual operations, AI-in-tools, and AI-for-production stages, with concrete next steps.
How teams evolve when agents coordinate investigations, reduce evidence latency, preserve institutional knowledge, and operate with enterprise guardrails.
