AI sprawl gets expensive fast. Not because teams are using too much AI, but because agents, models, and workflows start spreading across the org with no shared way to measure what’s working.
The answer isn’t forcing everyone onto one model. It’s building shared infrastructure to:
• route work to the right model
• compare cost against outcomes
• reuse successful workflows
• turn one-off agent wins into automations
@rbren_dev spoke with
@usatoday about what it takes to move from scattered AI tools to agent infrastructure that engineering teams can actually operate at scale.
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