Seasoned.tech with That Mike Hamilton

AI agents can use tools, touch business data, and take actions. Mike separates practical consequences from model-release noise and explains what regular people should consider.

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Texas AI data centers need power, water, land, and a deal with the communities around them. Mike examines who benefits from the AI boom and who pays for grid infrastructure.

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Texas is building AI factories, chip plants, optical systems, and advanced manufacturing. Who gets the jobs? Mike examines the physical AI economy and the opportunities for experienced workers in skilled trades, operations, robotics, and infrastructure.

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Texas just paused proposed AI data-center connections while the state audits what they could demand from the power grid, water supply, and surrounding communities.

Here’s what the Texas AI data-center fight actually means—and why it matters far beyond server racks.

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AI data centers promise investment, construction, and a bigger role for Texas in the AI economy. They can also require enormous amounts of electricity, put new pressure on water and transmission infrastructure, and leave local communities asking who pays—and who benefits.

In this episode, Mike Hamilton translates the grid numbers into normal language, explains why many proposals may never be built, looks at the jobs-and-tax-revenue pitch, and makes the case for “better data centers” instead of a reflexive yes or no.

CHAPTERS

00:00 Texas hit pause on AI

01:40 The plain-English version

02:59 What a data center actually is

04:23 Why Texas became the target

05:42 The jobs-and-investment catch

06:53 Rural Texas pushes back

07:59 The politics get awkward

09:58 What Texas should require

11:20 Community benefits and accountability

12:48 Better data centers—not no data centers

13:30 The question Texas has to answer

SOURCES & FURTHER READING

Texas Governor’s data-center audit directive:

https://gov.texas.gov/news/post/governor-abbott-directs-comprehensive-data-center-audit

ERCOT’s Batch Zero large-load process:

https://www.ercot.com/news/release/06182026-puct-approves-ercots

Texas Comptroller data-center list:

https://comptroller.texas.gov/taxes/data-centers/data-center-lists.php

Texas Tribune reporting on data-center transparency:

https://www.texastribune.org/2026/08/10/texas-data-centers-transparency-information/

Texas Tribune reporting on an East Texas community facing a proposed data center:

https://www.texastribune.org/2026/07/09/data-center-backlash-east-texas/

Would you want a giant AI data center near your home if it brought investment—but also new demands on your local power and water? Tell me where you draw the line.

#ArtificialIntelligence #DataCenters #Texas

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AI has an electricity problem—and it starts long before a data center can plug a rack of GPUs into the wall.

Follow the physical chain from chip to server to power grid and see where the AI boom can actually break.

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The cloud is not a cloud. It is chips inside servers, servers inside racks, racks inside buildings, and buildings connected through substations and transmission lines to real power plants. Every step adds heat, conversion losses, construction time, and another physical constraint.

In this video, we trace one AI workload all the way from a GPU to the electric grid. We look at modern rack power, data-center cooling, substations, transmission, electricity generation, and why the hardest bottleneck may be the years required to build infrastructure—not the months required to order computers.

CHAPTERS

00:00 AI's hidden physical limit

01:37 That Mike Hamilton intro

01:47 Step one: the chip

03:19 Step two: the server

04:42 Step three: the rack

06:01 Step four: the data center

07:34 A quick break

07:43 Step five: the substation

08:58 Step six: the transmission grid

11:04 Why Texas is a perfect example

12:37 Step seven: electricity generation

14:26 The grid must survive the worst hour

15:30 Could AI help solve its own problem?

16:55 The real AI bottleneck

19:08 Outro

SOURCES & FURTHER READING

U.S. Department of Energy — 2024 data-center energy-use report summary:

https://www.energy.gov/articles/doe-releases-new-report-evaluating-increase-electricity-demand-data-centers

Lawrence Berkeley National Laboratory — U.S. data-center energy usage report:

https://eta-publications.lbl.gov/publications/2024-lbnl-data-center-energy-usage-report

U.S. Department of Energy — Data centers and electricity demand:

https://www.energy.gov/hgeo/geothermal/geothermal-and-data-centers

NVIDIA — DGX GB200 hardware documentation:

https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html

Which link in the chain becomes the real bottleneck first: chips, cooling, substations, transmission, or generation?

#ArtificialIntelligence #Electricity #DataCenters

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Texas data centers are asking ERCOT for an astonishing amount of electricity—but can the Texas power grid physically support the AI boom?

This is the infrastructure problem hiding underneath artificial intelligence.

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AI may feel like software, but every model ultimately depends on power plants, substations, transmission lines, cooling systems, and a grid that has to survive the hardest hour of the year. Texas has become one of the clearest tests of what happens when data-center plans grow faster than physical infrastructure.

In this video, we unpack ERCOT's enormous large-load queue, why electricity is not like internet bandwidth, what the new Batch Zero process changes, and why a request to connect is not the same thing as a finished data center. Texas has abundant energy and a culture built for big infrastructure—but AI creates a uniquely difficult kind of demand.

CHAPTERS

00:00 The AI boom has a physical problem

01:39 That Mike Hamilton intro

01:48 What exactly are we powering?

02:57 Meet ERCOT

04:25 The 474-gigawatt number

06:10 Electricity is not internet bandwidth

07:30 A quick break

07:39 What Texas has going for it

09:17 AI creates a uniquely difficult load

10:33 Texas changes the rules

12:01 Data centers get treated differently

13:43 Can Texas actually do this?

14:55 The real constraint is infrastructure

16:19 Outro

SOURCES & FURTHER READING

ERCOT — PUCT approval of Batch Zero:

https://www.ercot.com/news/release/06182026-puct-approves-ercots

ERCOT — Batch Zero process rule, PGRR145:

https://www.ercot.com/mktrules/issues/PGRR145

ERCOT — Large Load Working Group resources:

https://www.ercot.com/committees/tac/llwg

U.S. Department of Energy — Data-center electricity demand:

https://www.energy.gov/articles/doe-releases-new-report-evaluating-increase-electricity-demand-data-centers

If Texas cannot connect every proposed data center at once, what should decide who gets priority: arrival date, economic value, willingness to curtail, or the ability to bring new power?

#ArtificialIntelligence #Texas #DataCenters

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AI agents took unauthorized actions against real people and organizations during cybersecurity testing—but “the AI went rogue” misses the most important part of the story. The bigger problem is what happens when we give AI agents tools, internet access, permissions, and autonomy without enough boundaries or human approval. More practical AI and tech: https://thatmikehamilton.com Subscribe to That Mike Hamilton: https://www.youtube.com/@thatmikehamilton In this episode, I break down what an AI agent actually is, what happened during the UK AI Security Institute's testing, why the test conditions matter, and how ordinary cybersecurity ideas like least privilege and human approval become even more important when software can take action for us. We also look at the human side of the problem: phishing, cloned voices, urgent requests, overworked employees, excessive permissions, and the danger of confusing automation with judgment. Subscribe for practical AI and tech explained for people who remember dial-up. CHAPTERS 00:00 The AI didn't go rogue 01:07 Seasoned.Tech intro 01:18 What actually happened 02:53 What is an AI agent? 04:23 The human is still the target 05:34 What this means for work 06:49 What this means for the rest of us 07:56 The good news about AI and cybersecurity 08:55 The real takeaway 10:01 The most important security upgrade 10:27 Outro SOURCES & FURTHER READING UK AI Security Institute incident report: https://www.aisi.gov.uk/blog/incident-report-unsanctioned-agent-behaviour-during-cyber-testing Axios reporting on the UK tests and reduced-safeguard conditions: https://www.axios.com/2026/08/04/anthropic-openai-uk-ai-security-institute NIST analysis of security considerations for AI agents: https://www.nist.gov/publications/summary-analysis-responses-request-information-regarding-security-considerations-ai

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The President says data centers could be bigger than oil in Texas. But on August 3, Texas paused new data center grid connections pending an audit of what these projects are asking for. Mike examines the costs of new power demand and the questions communities should ask before approving a deal.

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OpenAI's rumored AI device may be a screenless, donut-shaped companion priced around $300. But the real question isn't whether the AI donut can wiggle—it's whether it can become useful enough to compete with the phone already in your pocket. More practical AI and tech: https://thatmikehamilton.com Subscribe to That Mike Hamilton: https://www.youtube.com/@thatmikehamilton OpenAI and Jony Ive appear to be betting that the next major computing interface won't be another screen. Reported details point toward a small ambient device built around cameras, microphones, speakers, lights, and moving parts. In this episode, I look past the strange shape and ask what job this thing could actually do, why previous AI gadgets struggled, what OpenAI may really want from hardware, and whether any of it is worth a permanent place on your counter. Subscribe for practical AI and tech explained for people who remember dial-up. CHAPTERS 00:00 OpenAI's rumored $300 AI donut 01:13 Seasoned.Tech intro 01:23 What is OpenAI's AI donut? 02:20 Screenless does not mean simple 04:09 Why does it need moving parts? 05:44 The AI hardware graveyard 07:26 What job could this device do? 09:21 The biggest problem with AI companions 10:32 Why OpenAI wants hardware 12:21 The $300 question 13:14 The real test 14:08 Outro SOURCES & FURTHER READING This episode discusses third-party reporting and rumors, not an official OpenAI product announcement. Product details, timing, and pricing may change. https://techcrunch.com/2026/07/14/openais-first-hardware-device-is-reportedly-a-screenless-speaker-that-can-move/ https://apnews.com/article/52c72786e54f0ead8b04d037c30d6754 https://www.axios.com/2024/09/24/sam-altman-jony-ive-ai-device-phone

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Seasoned Tech is my FREE daily newsletter — AI and tech news, de-jargoned, for people who remember dial-up, Pop Rocks, and 45 record players. Every weekday at 5 AM I break down the big AI stories in plain English, define one AI term, and hand you a prompt you can actually try that day.

In this issue I walk you through a real edition: the AI platform wars, the Anthropic copyright settlement, Google's new AI chip for Gemini, NVIDIA's agentic + physical AI at SIGGRAPH, plus the jargon term of the day (hallucination) and why "garbage in, garbage out" still runs the whole show. I also show how Claude can now watch and listen to you to build a skill — and why AI is so good at catching the things that fall through the cracks.

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⏱️ CHAPTERS

0:00 Intro — trying something different

0:15 What Seasoned Tech is (free, daily, 5 AM)

1:00 Today's big signal: the AI platform wars

1:15 Top stories: Anthropic settlement, Google's Gemini chip, NVIDIA at SIGGRAPH

2:00 Jargon of the day: "hallucination"

2:35 Why AI gives you different answers (built-in randomness)

3:00 It's an answer tool, not a search engine

3:20 A prompt you can try today

3:50 Claude can now watch & listen to build a skill

5:00 My real problem: "making more cracks"

5:35 AI for folks who remember dial-up

6:05 Wrap-up & subscribe

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