Roger Schmeits

Systems Engineer - vSphere, VDI,Compellent, ScaleIO, EMC XtremIO & Avamar. UCS, Dell & HP Chassis Mgmt. Son, Brother, Husband, Father, Farm kid, Nature Nut

[Anatoli Kopadze @AnatoliKopadze]

A Google DeepMind engineer just explained why even senior devs fail at building AI agents.

This is the clearest explanation of how agents and loops actually work you'll find anywhere.

People are paying $500 for courses that teach less than this 11-minute talk.

Watch it, then read the step by step guide on building loops for your agents below.

[Anatoli Kopadze @AnatoliKopadze]

This is the EXACT architecture OpenAI uses to build AI agents.

They just dropped a 34-page guide, I compressed it into one page.

6 stages, one loop, everything you actually need.

Read it, then go to the step by step guide on building LOOPS for your agents below.

[Anatoli Kopadze @AnatoliKopadze]

I put the entire blueprint to building your first AI agent in one image

the setup most people waste months figuring out on their own

27 steps. working agent. 20 min to make. $5/month to run:

[Anthony Pompliano 🌪 @APompliano]

Sometimes I feel like I am taking crazy pills.

We built a product where the data objectively proves using it regularly grows your net worth faster than not using it.

Rich people are flocking to it, yet some of you won’t try it.

Insane.

Sign up free: https://t.co/bL17kqxamE

[Andrew Brown @andrewbrown]

Claude Code Camp registration is now OPEN. Its a 3 weeks hands-on online bootcamp where we'll create a very capable agent. Bootcamp starts Saturday July 11th Noon EST.

There is an early bird-sale on now which will end soon.

More information at the site:
https://t.co/KS6nnlxBys

[Roger Schmeits @knothead00]

@andrewbrown Explain "our largest group of users".

[Mayank Agarwal 💡 @TheAIWorld22]

BREAKING: Claude can now map out your retirement better than most people charging $3,000 ever will.

Here are 6 prompts to figure out exactly when and how you can retire.

(Save this before it disappears).

[taku @TWC_Design]

Making This Wooden Latch
#woodworking

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/xHKvUDKhG2

[Sawinery Woodworking @sawinerywoodwrk]

This Miter Jig Is Seriously Clever

[Linux Inside: The Ideal Blog for Sysadmins & Geeks @tecmint]

Announcing a new course on Pro TecMint: Claude Code for #Linux Sysadmins

This is a 32-chapter course designed for professionals who work in the terminal every day, not just developers building sample apps.

You’ll learn how to use Claude Code for real sysadmin tasks like analyzing configs, debugging logs, and improving automation workflows.

The first chapter is now live:
https://t.co/ftSEsOd6Xn

Follow @tecmint for a new chapter every week.

[Roger Schmeits @knothead00]

@efino87 My Dad has sandhill ground where it has a natural spring. He did put in a well but I think they only drilled 120 feet or so (if that). Can not imagine drilling 500 feet. That is very deep.

[Roger Schmeits @knothead00]

@APompliano Click to open "Odd Lots - Daniel Yergin Sees a 'Different World' Emerging After the Hormuz Crisis" in Podcast Guru:

https://t.co/jcmxaRmOAC

[FF&E (Furniture, Fixtures, and Equipment) @FFE_only]

Coffee/Dining Table - 2 Metres.

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[FF&E (Furniture, Fixtures, and Equipment) @FFE_only]

Making of a custom made shelf , the finishing is top notch!!!!!

[Praetor @FourVork]

15 AI related accounts you should follow on Twitter:

1. @karpathy
His tweets already create LLMs narratives that you later see on linkedin in 2 months.

2. @fchollet
posts thoughtful research on intelligence, benchmarks, and AI limitations. Keras creator + ARC-AGI

3. @ylecun
Yann LeCun is Deep learning pioneer & Meta Chief AI Scientist; big-picture research takes and critiques (and drama).

4. @AndrewYNg
Andrew Ng is AI education legend; practical ML advice, courses, and real-world implementation. creator of deeplearning ai

5 @rasbt
Sebastian Raschka posts on Practical ML/LLM implementations, "build from scratch" tutorials, and books.

6. @dair_ai
Weekly ML/AI paper threads and accessible research explainers (high-signal for staying current).

7. @lilianweng
Lilian Weng is ex-OpenAI and her Lil'Log-style threads are good. has In-depth LLM research breakdowns

8. @jeremyphoward
posts interesting takes on AI/crypto news, and works on democratizing practical deep learning and accessible education.

9. @simonw
Simon post Practical LLM tools, takes, experiments, prompting, and engineering breakdowns. django co-founder

10. @_akhaliq
Curates the latest arXiv papers, model releases, and open-source AI drops.

11. @ID_AA_Carmack
AGI/low-level optimization takes that makes you think about the problem.

12. @gwern
Really high-quality long-form AI research notes and essays.

13. @goodside
LLM evaluation, prompting research, and real capabilities testing

14 @drfeifei
Computer vision pioneer; human-centered AI and spatial intelligence research

15 @demishassabis
Been following his work for 9 years. Demmis is my hope against google usurpating their power with AI. Demmis is google DeepMind's CEO

Let me know who I missed guys

[taku @TWC_Design]

Is this a jig? No jig?
#woodworking

[Roger Schmeits @knothead00]

@TWC_Design Sweet!!!

[Prateek Singh @mentalhotfix]

Here are the 4 AI YouTube channels I try to watch every day. They shape how I think, build, and stay ahead in AI.

My personal shortlist 👇

1. AI Engineer - https://t.co/8QrMcEhqti

2. The AI Automators - https://t.co/f853iJvwTq

3. IBM Technology - https://t.co/fn9QdVYk8Y

4. Yannic Kilcher - https://t.co/zHxheD2Jwj