If you wanna see something entertaining, watch Claude fight with another AI chatbot, like the one in LinkedIn's Campaign Manager. It's pure gold.
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Check out DesignRush's post about our EVIDENT™ methodology!
Most UX problems are completely avoidable. were built from the start.
@TheUXTeam’s EVIDENT methodology catches them before development begins. Research, insight synthesis, design, prototyping, and validation with every step backed by evidence, not assumptions.
The result: software users actually adopt.
See the five stages of the methodology here: vist.ly/5mzcb
G I Ξ G Ξ Ɍ retweeted
Most UX problems are completely avoidable. were built from the start.
@TheUXTeam’s EVIDENT methodology catches them before development begins. Research, insight synthesis, design, prototyping, and validation with every step backed by evidence, not assumptions.
The result: software users actually adopt.
See the five stages of the methodology here: vist.ly/5mzcb
This is a really great explanation of why and how the Nepal glacial disaster happened.
I am stunned by the amount of misinformation on the topic. So here is meteorologist @mikebettes explaining what happened during the Nepal glacial collapse. Listen to experts.
I hope this is real because it is amazing.
In Nepal, elephants were seen saving people from the devastating Flood...
Pray for Nepal 🙏 ♥️
Readers added context they thought people might want to know
This video is old footage from a prior unrelated flood incident and is not from the current devastating floods in Nepal.
english.mathrubhumi.com/news/world/nep…
livenowafrica.com/explainers/art…
nationalgeographic.com/animals/articl…
theguardian.com/world/2026/aug…
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The most likely cause of the Nepal–Tibet border flash flood is the creation of a barrier lake formed by a previous avalanche. The following devastating avalanche triggered the powerful surge of water seen in the August 26 event.
[🎞️ sciencebyansh]
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This is what @SpaceX's Starbase, Louisiana spaceport will look like.
It looks absolutely incredible. Multiple launch pads, and one beautiful location.
G I Ξ G Ξ Ɍ retweeted
Tesla just upgraded Grok in the car to the #1 speech-to-speech AI model in the world
The new Tesla Summer Release brings Grok Think Fast 2.0
And this is much bigger than just having a better voice assistant
Grok can now actually interact with the car:
• Adjust vehicle settings
• Guide you through controls
• Navigate and change destinations
• Make phone calls
• Search and play music
• Adjust temperature
• Answer questions about your Tesla
Grok Think Fast 2.0 currently sits #1 on Artificial Analysis’ Speech-to-Speech Index, combining speech reasoning, agentic performance, human preference and task success
Basically, instead of digging through menus to figure out your Tesla...you can just simply tell Grok what you want
Tesla is putting frontier voice AI directly into the car
And this is only the beginning of what Grok inside Tesla will become
I lost my father 15 years ago to pancreatic cancer, and now I have an uncle battling it, so this is huge! One patient has been taking Rasonque (daraxsonrasib) as part of a clinical trial for nearly four years. His cancer is no longer visible on scans.
nytimes.com/2026/08/26/scien…
Check out my latest posts on my website, The Eldery Parent: A Layman’s Guide to Planning and Caring for an Elderly Parent. #dementia #alzheimer's #elderly #caregiver
theelderlyparent.com/
AI is an incredibly powerful tool for accelerating design and development. At @TheUXTeam, we use different AI tools every day. But, it doesn't replace the need for real-world user research, usability testing, and evidence-based decision-making.
If AI isn't given data about how your users actually work, it won't know:
→ What information users need to make decisions
→ Where they get stuck in a workflow
→ What causes frustration
→ What drives adoption
→ Which features they actually value
That's why AI-generated UX (without evidence) will rarely result in a great UX.
Without research, observation, testing, and evidence, AI is simply generating educated guesses at scale.
The danger isn't that AI will create bad user experiences.
The danger is that AI will create bad user experiences faster and with greater confidence than ever before.
Great UX has never been about designing user interface screens.
It's about understanding people.
The best products of the future will be built by teams that combine the speed of AI with the insight that only real users can provide.
That's the difference between generating interfaces and creating experiences people actually want to use.
Generate an image to go with this LinkedIn post:
AI is an incredibly powerful tool for accelerating design and development. At UX Team, we use it everyday. But, it doesn't replace the need for user research, usability testing, and evidence-based decision-making.
If AI isn't given data about how your users actually work, it won't know:
• what information users need to make decisions
• where they get stuck in a workflow
• what causes frustration
• what drives adoption
• which features they actually value
That's why AI-generated UX isn't automatically good UX.
Without research, observation, testing, and evidence, AI is simply generating educated guesses at scale.
The danger isn't that AI will create bad user experiences.
The danger is that AI will create bad user experiences faster and with greater confidence than ever before.
Great UX has never been about designing user interface screens.
It's about understanding people.
AI is changing the economics of software development.
What used to take months now takes days.
But there is one thing AI has not changed:
The cost of building the wrong thing.
🚫 Features that users don't need are still a waste.
🚫 Workflows that users cannot understand is still friction.
🚫 Applications that employees avoid are still failed investments.
AI can reduce development costs, but it cannot reduce the cost of poor product decisions.
In fact, by making development faster, AI can actually increase the cost of bad assumptions by allowing the wrong products to scale more quickly.
The most successful enterprise teams won't be the ones that build the fastest.
They'll be the ones who learn the fastest.
The ones that understand their users, validate ideas early, and use evidence (not assumptions and opinions) to guide what gets designed and built.
Because in the age of AI-assisted development, the competitive advantage isn't shipping more features.
🏆 It's building the right features, the first time.
🤖 Made with AI
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MIT students gave AI a body.
the camera sees what’s in front of you. you say what you want.
the device moves your fingers with small electric pulses.
it plays piano without training. it draws what you describe. it mixes a drink while you watch your own arm do it.
the brain is Claude. six people built this in 48 hours.
and this is just the hand.
This is a live stream of a humanoid robot working an 8-hour shift.
youtube.com/watch?v=luU57hMh…