Thread regarding Optum layoffs

Looking for tech VP insight

How is the landscape looking right now? Is it akin to the hunger games?

First thing is the cloud stuff. We were told to go full hog to the cloud so we did. Now the outages are insane, and leadership is regretting it for our area, but with on prem set for decomm, there is no turning back. Not to mention the costs are through the roof with offshore misconfiguring it and cranking up the bill.

Secondly is the AI stuff. Feels like every team is just publicly declaring they are cramming AI into everything, attempting to, and then failing and trying to cover it up.

Will Candyman actually face accountability for this disaster? I have yet to see a working demo or plan that made any sense since he took over.

I also was told yesterday that PW's organization is set to deploy "hundreds of AI agents" to production next year who will be giving us business and funding, which i frankly find extremeley hard to believe.


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| 1611 views | | 5 replies (last December 13) | Reply
Post ID: @OP+1kc9e4w9b

5 replies (most recent on top)

@OP The reason cloud migrations are a mess is all the people who designed the plan were either laid-off or left.

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Post ID: @c9+1kc9e4w9b

@av Optum is already being sue for declining MN Medicare Advantage claims, after AI implementation without proper vetting or testing. This company will implode. I feel for the employees, but the yes "managers", it will be worst for them.

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Post ID: @aw+1kc9e4w9b

Id be interested to see what that AI fund is even being used for or if it ever sniffs production in any way

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Post ID: @av+1kc9e4w9b

Many tech leaders in PW org have been doing a 20% funding pullback meaning any capital UHC gives to Optum (some departments), 20% gets taken and put in an AI fund. I have heard mixed things on this as to whether the business asked for it or the CIO in our span is doing it.

They say they can do this because we are now 20% faster with because of copilot.

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Post ID: @ab+1kc9e4w9b

Over the last couple of years, many organizations and leadership teams have been racing to make their ecosystems “AI-ready,” often under aggressive timelines and external pressure.

2026 will likely be the real inflection point not because AI suddenly becomes transformative overnight, but because reality finally catches up with assumptions. A lot of decisions were made based on beliefs about AI capability, scalability, cost, and operational maturity that weren’t fully pressure tested in real production conditions.

When those assumptions collide with day-to-day realities: cloud fragility, cost overruns, integration debt, governance gaps, the gap between what was promised and what actually works becomes impossible to ignore. What we’re seeing now feels less like isolated failure and more like a system correcting itself after moving faster than its foundations could support.

The system isn’t breaking so much as it is enforcing the constraints that were always there but deferred, reliability, cost curves, data quality, operational load, and human oversight. Those constraints eventually assert themselves, regardless of how compelling the narrative was early on.

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Post ID: @aa+1kc9e4w9b

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