Stop debating AGI. Start redesigning your work.

Why verification, governance, and escalation matter more than intelligence.

Author

Martin Musiol
January 07, 2026 • Estimated Reading Time: 6 minutes

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Hey Friends,

Everyone is yelling “AGI” again. Cool story. The label is cheap.

What matters (and what’s actually happening) is way more concrete: models are moving from talking about work to doing work — and the world is starting to treat their outputs like something that needs verification, governance, and (in some cases) legal permission.

This week’s signal beats the hype:

  • Math: AI-assisted proofs are getting formalized and checked in public, on real open-problem forums.

  • Healthcare: a U.S. state is piloting AI participation in prescription renewals inside a regulatory sandbox.

  • Sales: one of the biggest SaaS communities is openly saying the classic SDR org chart is about to get nuked.

  • Science: sleep data just got “foundation-model-ified” into disease-risk prediction at serious scale.

Let’s get into it.

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Math: the workflow is going unattended

The shift isn’t “AI can do math.” It’s end-to-end: pick a problem → produce an argument → formalize in Lean → post → humans review.

Takeaway: verification is the moat. And problem framing is now a competitive skill.

Links:

Healthcare: Utah made it real

Utah’s Department of Commerce announced a partnership with Doctronic to evaluate autonomous AI for prescription renewals for chronic conditions inside a regulatory sandbox. Translation: this is autonomy with guardrails, metrics, and accountability — not vibes.

Link:

Sales: the org chart is the product now

SaaStr’s take is blunt: fewer humans, more agents, and a new job title emerging — Agent Manager (tooling, QA, escalation, iteration).

Whether you buy every number or not, the direction is obvious: the middle layer of “polite persistence + routing” is getting crushed.

Link:

Science: SleepFM turns sleep into an embedding

Nature Medicine published “SleepFM,” a multimodal sleep foundation model trained on ~585,000 hours of PSG data (~65,000 participants). It predicts a broad set of future disease risks from sleep signals.

Bull case: better screening/triage.
Caution: risk prediction without clinical integration becomes anxiety at scale.

Link:

The point

“AGI” is a word people use when they don’t have a better one.

What’s actually happening: work is being converted into pipelines models can run.

If you want a practical response:

  1. Pick a workflow that’s mostly “humans shuffling information.”

  2. Build an agent around it.

  3. Put a human in charge of QA + escalation.

  4. Measure outcomes like you mean it.

Stop predicting. Start rebuilding.

That's all for this week!

Happy Building!
🙇Martin

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