Robert Miller (🦄,🦄)

Data Gerd (Geek-Nerd), Cloud Architect, MS SQL DBA/Architect/BI juggler, Big Data (Streaming), Full-Stack Developer, Chesapeake Bay Retrievers, and electronics.

[Robert Miller (🦄,🦄) @RobertMiller]

@CasimirInc @DrSonnyWhite @Debriefmedia @TarzanCrypto

[Robert Miller (🦄,🦄) @RobertMiller]

@heygurisingh Send

[Robert Miller (🦄,🦄) @RobertMiller]

@NVIDIAGeForce #007FirstLightRTX

[MDN Web Docs @MozDevNet]

Speed up rendering with content-visibility: auto ⚡

This CSS property skips rendering off-screen content until needed, giving massive performance wins on long pages.

⋅ Pairs with contain-intrinsic-size
⋅ Zero-effort lazy rendering

Learn more 👇
https://t.co/aXEBbjqooA

[Atal @ZabihullahAtal]

🚨 BREAKING: A new role is quietly emerging and it’s about to dominate the next 5 years.

It’s not “AI engineer.”
It’s not “prompt engineer.”

It’s the Agent Operator.

And it will sit inside almost every organization.

Most people are still thinking about AI as a tool.

That framing is already outdated.

What’s actually happening is a shift from:
humans using software to humans managing autonomous agents that execute work

This is a fundamental redesign of how work gets done.

So what is an Agent Operator?

An Agent Operator is the person who:
• Designs how agents interact with real workflows
• Connects tools, data, and systems into agent pipelines
• Translates business problems into executable agent behavior
• Monitors, corrects, and improves agent performance over time

They don’t just “use AI.”

They orchestrate outcomes.

and this matter because
Every function marketing, legal, finance, biotech is becoming “agent-compatible.”

Not because companies want it.
Because they won’t have a choice.

Agents can:
• Run research loops
• Execute multi-step workflows
• Integrate across tools without APIs breaking the flow
• Operate 24/7 at near-zero marginal cost

The bottleneck is no longer capability.
It’s implementation inside real-world systems.

Required skills for AI Agent Operator role:
→ MCPs (Model Context Protocols)
Understanding how agents access tools, memory, and structured context.

→ CLIs (Command Line Interfaces)
Because serious agent workflows won’t live in GUIs—they’ll run in programmable environments.

→ Writing skills (the file kind)
Clear specs, instructions, and structured documents.
Agents run on precision, not vibes.

→ agents dot md fluency
The ability to define agent roles, constraints, memory, and tool usage in persistent formats.

→ Business acumen
Knowing what actually matters:
Where automation creates leverage, not noise.

What happens next
Enterprises will begin to redesign workflows:

Not around employees using dashboards…
But around agents executing tasks.

That means:
• SOPs → Agent playbooks
• Teams → Human + agent hybrids
• Tools → Composable agent systems

When that shift happens, companies won’t just need engineers.
They’ll need operators who understand both the system and the business.

The leverage is asymmetric

One strong Agent Operator can:

• Replace fragmented SaaS workflows
• Multiply team output without adding headcount
• Turn ideas into execution systems in days

This is not incremental productivity.

It’s operational transformation.

[Robert Miller (🦄,🦄) @RobertMiller]

@iFixit Cleaning the fans on my MBP.

[Robert Miller (🦄,🦄) @RobertMiller]

@erichustls Freedom

[Robert Miller (🦄,🦄) @RobertMiller]

@heygurisingh FREE

[Abdul Șhakoor @abxxai]

BREAKING: 🚨 Someone just tested 35 AI models across 172 billion tokens of real document questions.

The hallucination numbers should end the "just give it the documents" argument forever.

Here is what the data actually showed.

The best model in the entire study, under perfect conditions, fabricated answers 1.19% of the time. That sounds small until you realize that is the ceiling. The absolute best case. Under optimal settings that almost no real deployment uses.

Typical top models sit at 5 to 7% fabrication on document Q&A. Not on questions from memory. Not on abstract reasoning. On questions where the answer is sitting right there in the document in front of it.

The median across all 35 models tested was around 25%.

One in four answers fabricated, even with the source material provided.

Then they tested what happens when you extend the context window. Every company selling 128K and 200K context as the hallucination solution needs to read this part carefully.

At 200K context length, every single model in the study exceeded 10% hallucination. The rate nearly tripled compared to optimal shorter contexts.

The longer the window people want, the worse the fabrication gets. The exact feature being sold as the fix is making the problem significantly worse.

There is one more finding that does not get talked about enough.

Grounding skill and anti-fabrication skill are completely separate capabilities in these models.

A model that is excellent at finding relevant information in a document is not necessarily good at avoiding making things up. They are measuring two different things that do not reliably correlate. You cannot assume a model that retrieves well also fabricates less.

172 billion tokens. 35 models. The conclusion is the same across all of them.

Handing an LLM the actual document does not solve hallucination. It just changes the shape of it.

[kanav @kanavtwt]

there's been an update

[Robert Miller (🦄,🦄) @RobertMiller]

@DogefatheronX Starship, obviously.

[Robert Miller (🦄,🦄) @RobertMiller]

@free_ai_guides Anthropic

[Robert Miller (🦄,🦄) @RobertMiller]

@RedPandaMining @PlebSource Solo mining: Decentralization as it is meant to be.

[Red Panda Mining @RedPandaMining]

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🔁 Repost and like this post
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Good luck, plebs 🟧🐼 #Bitcoin #SoloMining #BitcoinMining $BTC

[Robert Miller (🦄,🦄) @RobertMiller]

@erichustls Freedom

[CoreX Hosting @CoreX_Hosting]

🚨GIVEAWAY TIME 🚨

We are giving away a S21Pro - 234T to be hosted at Iowa Mining.

To enter, do following:
1 : Like this post
2: Follow us
3: Share / RT this post.

Winner drawn: Friday January 30th #Bitcoin #crypto #Giveaways

[Robert Miller (🦄,🦄) @RobertMiller]

@RedCollie1 Does the "dowel pin" need to be metallic? This is unconventional. Could it be wood ( would be damaged by the spinning magnetic disk ) or some form of 'Corning' glass ( susceptible to shearing forces ), as two possible example alternatives?

[Robert Miller (🦄,🦄) @RobertMiller]

@interesting_aIl Calling shenanigans. I did not see a GE 415 at anytime in the pictures. :)
64k-word mag-core memory, card-reader, mag-tape, band-printer.

[Robert Miller (🦄,🦄) @RobertMiller]

@BrockRiddickIFB 6