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Workflow modernization · Note

From projects to products

AI systems keep changing after launch. That pushes federal modernization from one-time projects toward continuous product delivery.

Across agencies, leaders are moving away from big, multi-year IT projects toward continuous product delivery. AI makes that shift more urgent.

A traditional system can be built, accepted, and maintained. An AI system can't be treated that way, because:

  • Models evolve quickly
  • Data pipelines have to stay healthy
  • Model behavior needs monitoring
  • User expectations keep moving
  • Policies and guardrails keep changing

In our work with government teams, the best outcomes come from treating systems as living products, not one-time implementations. That means a standing team, a backlog that outlives the first release, and a regular review of what the system is doing in production.

AI forces us into product thinking. That's a good thing.

How we work

Stage 04 of our method, Evolve in production, is a monthly review of where people override the AI, what to redesign, and which tasks have earned more autonomy.

AN

Ashok Nare

Founder and CEO, Kollabio

Ashok has spent 30 years building distributed systems for federal agencies and other regulated industries. He founded Kollabio in 2015.

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