AI Blogger | Hiking Enthusiast ♂️ | Sci-Fi Aficionado | Dog Lover
Houston
Joined November 2023
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Chase AI retweeted
Why did code quality matter in the first place?
@mkanat brings it back to two questions: what does the system actually do, and how do you change it safely?
57 seconds from AI Engineer New York.
Before you accept the next AI generated change, can you answer both?
#AIEngineerNY
Chase AI retweeted
This is the Claude Code Resource Bible.
54 tools.
Agents. MCP servers. Skills. Automation.
Most people still haven’t discovered this stack.
Here’s the curated version (3 best links per section) 👇
🟦 OFFICIAL
• code.claude.com/docs — Claude Code docs
• lnkd.in/eBZZGsMx — official MCP servers
• lnkd.in/ekUBf8a6 — free certification
🟧 DIRECTORIES
• ecc.tools — everything Claude Code
• lnkd.in/ebE2iDvV — MCP list
• lnkd.in/emQbMwbG — 50+ MCPs
🟨 MCP SERVERS
• lnkd.in/eMC5dUqR — browser automation
• lnkd.in/eESCpJPv — database + auth
• github.com/Dokploy/mcp — deploy apps
🟩 SKILLS
• lnkd.in/eppbgRaK — browser control
• lnkd.in/ejAPia8C — full dev workflow
• github.com/tadaspetra/loop — recurring tasks
🟪 MULTIPLEXERS
• cmux.com — agent terminal
• gmux.sh — orchestrate agents
• github.com/coder/mux — parallel dev
🟥 AGENT FRAMEWORKS
• github.com/HKUDS/ClawTeam — multi-agent coordination
• lnkd.in/eJPYijMk — agent collaboration
• lnkd.in/eMt3sS7N — NousResearch agents
⚙️ AUTOMATION
• lnkd.in/e9sarX3R — workflows in code
• openlogs.dev — monitor agents
• lnkd.in/eDKBPrPU — self-hosted infra
📚 ARTICLES
• lnkd.in/e9gfhHhm — best CLI tools
• lnkd.in/ePCzNw5w — top MCP servers
• lnkd.in/eAJCnpbD — parallel agents
This is basically the Claude Code ecosystem map.
Learn it now → you're early
Ignore it → you're late
Bookmark this. You'll need it..
If you’d love to see more content like this, don’t forget to follow for more AI magic.
Chase AI retweeted
Bear case scenario for neoclouds in one Picture. You cannot have such a drastic gap to build something that hypescalers can do themselves as the infra situation stabilises
Would be smart to pick 1/2 names if at all than exposure towards entire sector. My pick is Nebius
$NBIS $IREN $CRWV $BRUN $HUT
Chase AI retweeted
Texas Robotic Faculty Present 36 Papers at ICRA 2026! @IEEEorg - Gabriel Perin #BigData #Analytics #AI #MachineLearning #Robotics #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
geni.us/Texas-36
Chase AI retweeted
College of Computing & Artificial Intelligence co-leads the College of Engineering Initiative to Advance Embodied AI! University of Wisconsin embodied AI — @uwmadcai
Bilge Mutlu - Lead
Michael Gleicher
Mohit Gupta
Mike Hagenow
Josiah Hanna
Heather Kim (incoming faculty)
Bilge Mutlu — Robotics and Human Robot Interaction
Akarsh Prabhakara — Sensing Technologies for Robotics
Yuhang Zhao —
#BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #Robotics #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode
geni.us/College-Computing
geni.us/College-Wisconsin
Chase AI retweeted
Data live on our rankings page now:
openrouter.ai/rankings#open-…
Chase AI retweeted
Open-weight models processed 72% of tokens across OpenRouter last week.
Open-weight models have seen more than 50% of tokens across the platform since mid-April, but the majority of customer spend remains on closed-weight models.
Chase AI retweeted
When it comes to scaling AI, physics keeps winning. @CoherentCorp CEO Jim Anderson expects scale-up, the last part of the AI network still running on copper, to go optical over the coming years as data rates outrun electrical links, expanding the optics TAM. $COHR
Chase AI retweeted
An AI agent that troubleshoots Kubernetes needs controls that live outside the model. This dev lays out a GKE and Gemini setup built on least-privilege access, human approval gates, and audit logging.
{ author: Saurabh Mishra + @GoogleDevExpert }
dev.to/gde/safe-autonomy-in-…
Chase AI retweeted
Very refreshing to see a CEO like Bill Brennan of Credo know so much about his product and technology while working his booth. $CRDO
Chase AI retweeted
🚨 Opus 5.5 High is routing to claude next model
i am late to part , as i prompted it to make a 3d version purely with python code in blender
This is stuttering and i had to stop as my mac crashed < i will buy new one on my birthday - 18 oct>
Enjoy the life of a human
Chase AI retweeted
Techniques for Training Large Neural Networks. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
geni.us/Techniques-Large-NNs
Chase AI retweeted
$LITE $COHR $AAOI $SIVE $CRDO
WOW. @JensenHuang just put the 2027 bottleneck inside the package.
Land, power, shell were already known.
Now he named substrates and silicon photonics.
“Silicon photonics is supply constrained… it’s going to be hard to close that gap for a few years.”
That’s multi-year sold-out status + pricing power for the optical layer.
$LITE and $COHR sit right on the scarce laser / photonics constraint.
$AAOI, $SIVE, $CRDO ride the same interconnect wall.
When the CEO of the company that sets the pace says the light can’t keep up with the chips… VERY bullish!
PS: Credits to my friend @carrioresearch for sharing.
Chase AI retweeted
I got a few questions about the Maryland in class AI study and how it relates to @alldaytahelps. Short answer: you need care to design AI assistants! A few things I notice (and we see these bad patterns *all the time* in university-created in-class AI): 1/10
Chase AI retweeted
Bullish — $LITE $COHR $AAOI $SIVE
The laser fight inside AI switches just got very real at OCP.
At OCP, InnoLight (via TeraHop) showed real field data: 100 billion device-hours on their PICs with a FIT rate under 0.01. (FIT rate = how often the part fails in the field. Lower is better. This is extremely low.)
They also made the power case for keeping the laser inside the engine: ~100 mW vs 200–300 mW external.
Move the laser out and you instantly lose >3 dB (half the optical power) to coupling and connectors, then need ~4× the cooling on the front panel.
$NVDA is still on external lasers. Alibaba wants them integrated. Open CPX ($COHR is a founder) supports both.
This accelerates the ecosystem.
Module makers stay in the game, and InP laser demand stays high either way. More units if integrated, higher-power units if external.
That’s the setup for $LITE $COHR $AAOI $SIVE $IQE.
We are long and bullish. NFA.
PS: Credits to @carrioresearch for sharing the slides.
Chase AI retweeted
OpenRouter users are loving Anthropic's Opus 5.5
It is the #1 model in share of spending across the platform and has led a rebound for Anthropic in the competition with OpenAI
Sonnet 5.5 and Haiku 5.5 have also seen strong launch periods
Chase AI retweeted
These 30 browser games I modded never existed.
They started as videos I generated. And you can play all of them right now.
H3 Max on @fal made the gameplay clips. @claudeai rebuilt each one with fal Agent into a beautiful, interactive WebGL game.
Every image, 3D model and sound comes from fal. The code: written from scratch by Claude, @threejs only, no other library, no engine, no template.
Every prompt and the full instructions are on the page, so you can reproduce it.
Original games, no IP 👇
fal-video-to-game.vercel.app
Chase AI retweeted
Zuck broke down what it costs Meta to build frontier AI:
"To operate a gigawatt a year, call it on the order of $15 billion." Building that same one-gigawatt cluster costs $50 to $60 billion upfront.
And all of that only covers the final training run.
Meta is building well past one gigawatt.
Prometheus in Ohio is scaling beyond a gigawatt, and Hyperion in Louisiana is designed to reach 5 gigawatts.
By Zuck's own numbers, a 5 gigawatt site is $250 to $300 billion to build and roughly $75 billion a year to run.
He thinks the downside has a floor though.
If AI works, plenty of other companies will pay Meta well over $15 billion a gigawatt for that compute.
For the bet to fail, AI as a whole has to fail.
FT @finkd @alexandr_wang @collision @stripe.
$GOOGL head of AI infra: 7-8 year-old TPUs are still 100% in use!
Why keep the old chips busy?
Demand > supply. Google has $514B of cloud backlog
Capital constraints: Big Tech spent 96% of operating cash flow last quarter
Physical bottlenecks: We cannot build datacenters fast enough (energy, land, electrical infra, ... not available)
We probably remain in that constrained environment for a little longer as we just entered the agentic world.
Just start to use GrokBot or Muse and see how fast you blast thru your credits, then you will understand :)
Chase AI retweeted
The future of gaming now belongs to anyone with a big enough imagination.
Speaking worlds into existence.
