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The latest episode of Mixture of Experts brought together three leading minds from across the AI ecosystem—Kouthar El Alaoui (IBM), Aaron Baughman (IBM), and Mihai Crovetto (Distinguished Engineer, Agentic AI)—to dissect a week filled with high-impact developments: OpenAI’s new GPT-5.1 models, the surprising rise of the open-source Kimmi K2 Thinking model, and Microsoft’s provocative vision of AI “users” embedded directly inside the enterprise workforce.
Here’s a distilled overview of what stood out.
GPT-5.1: A Fix, Not a Leap?
OpenAI’s dual rollout—GPT-5.1 Instant and GPT-5.1 Thinking—generated plenty of discussion, but the headline moment wasn’t about benchmark wins. This time, OpenAI led with style. According to the company, users want a model that is not only smart but “enjoyable to talk to.”
That pivot raised a core debate on the panel:
Is this truly a new model upgrade—or a course correction after the community pushback surrounding GPT-5?
Mixed Community Reactions
Some developers praise 5.1’s warmth and conversational fluidity. Others remain nostalgic for GPT-4’s output style and skeptical about claims of deeper reasoning. A significant portion of the community believes this is:
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A refinement rather than a reinvention
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Partially a cost-optimization move, especially with the new router system deciding when to use Instant vs. Thinking
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A strategic push into personalization and user experience as the frontier of differentiation
As Mihai Crovetto put it, many are still wondering: “Is this really a new model or just a retune of GPT-5?”
The Router: Feature or Red Flag?
GPT-5.1’s new routing layer—automatically deciding how much “thinking” to apply—won praise from those seeking responsiveness. But others found it unsettling.
Crovetto was blunt:
“I don’t want it learning my behavior. I want switches I can toggle. Not a model deciding how much to think.”
This tension hints at a split emerging in the market:
Do users want a hyper-smart assistant—or a deeply personalized one?
We may soon see segmentation not by model size, but by EQ vs. IQ, style vs. reasoning.
Kimmi K2 Thinking: Open Source’s Biggest Power Play Yet
While OpenAI polished style, Chinese startup Moonshot AI delivered a shockwave with Kimmi K2 Thinking, an open-source Mixture-of-Experts (MoE) model that posts numbers competitive with top proprietary models—even outperforming them on several benchmarks.
Why This Matters
Kimmi K2 Thinking is:
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A 1-trillion-parameter MoE that activates just 32B parameters per token (major compute efficiency)
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Competitive on SWE-Bench, BrowseBench, and Humanity’s Last Exam
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Fully open-weights with a permissive license
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Capable of up to 300 tool calls, 256k context, and local deployability
As Kouthar El Alaoui noted, this challenges the entire closed-model economy:
“If the best model in the world is open weights, the center of gravity shifts from secret models to shared ecosystems.”
But… Are the Claims Real?
Baughman urged caution. Benchmarks can be gamed, and independent evaluation is essential. Still, even skeptics acknowledged the momentum: open source is no longer “six months behind.” In some areas, it may now lead.
Why Developers Are Excited
Crovetto summed up the developer enthusiasm perfectly:
“I can run it locally. No router. No data collection. No hidden training. I’m in control.”
The ability to self-host a frontier-class model—even with a one-terabyte download—is a paradigm shift.
Microsoft’s “Agentic Users”: AI Has Entered the Workforce
The show closed with one of the most surreal stories of the week: Microsoft is exploring AI agents that function as real enterprise users. These embodied agents have:
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Their own identity
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Credentialed access to organizational apps
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The ability to email, edit documents, attend meetings
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Autonomy to collaborate with humans and other agents
In short: a new coworker, but… it’s not human.
The Promise
For business teams:
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Productivity at an entirely new scale
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Constant availability
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Automated workflows across the whole Microsoft ecosystem
The Nightmares
For security teams:
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Thousands of “users” moving data around
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Blurred accountability
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Unknown compliance risk
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Governance systems unprepared for agents acting like staff
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The specter of agents impersonating humans
Crovetto called it a “security nightmare in the making,” especially under GDPR and the upcoming AI regulations.
The Cultural Shock
Even beyond security, the implications are profound.
What does “company culture” mean when:
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Some team members never sleep?
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Some don’t have feelings?
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Some aren’t even people?
And yes—someone joked:
“We’re only years away from office romance with an AI coworker.”
The Coming Agentic Economy
The panel speculated on a weirder future where:
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Agents outnumber humans
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Agents hire humans
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Agents pay humans for data
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Agents create other agents
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Agents attend meetings… and bill by the minute
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Your boss might be Cortana
As Baughman noted, “Hybrid human–agent workplaces will be the norm, not the exception.”
Final Thoughts
This week surfaced a stark reality:
AI is no longer just a technology race—it’s a race to shape how humans and machines will work, think, and co-exist.
OpenAI is doubling down on personality.
Open-source is doubling down on power.
Microsoft is doubling down on autonomy.
The future of AI may be decided not by benchmarks, but by which vision of interaction—and control—users ultimately trust.
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