I like seeing all of these in one place but isn’t most of this widely known?
This is it.
Everything learned spending millions on longevity.
From: Your Immortal Unc and Auntie.
To: Our Immortal nieces and nephews.
0. Sleep is the world's most powerful drug.
1. Be in your bed for 8 hours
2. Same bedtime every night, any time before midnight
3. Don’t eat right before bed
4. Calm foods for dinner
5. No screens 1 hour before bed
6. Avoid added sugar (be aware it’s in everything)
7. Avoid all things in an American convenience store
8. Avoid fried foods
9. Shoes off at the door
10. Eat whole foods, particularly veggies fruits nuts legumes berries
11. Walk a little after meals or air squats
12. Get your heart rate high routinely
13. Lift heavy things
14. Stretch daily
15. Water pik, floss, brush, tongue scrape, morning and night
16. Make an effort to drink water
17. Get sunlight when you wake up (UV is low)
18. Protect skin in midday sun
19. Stand up straight
20. See at least one friend once a week
21. Avoid plastic where you can (in all things)
22. Circulate air in rooms
23. When stressed, breathe, learn to calm your body
24. Go to the dentist
25. Avoid sitting for long times
26. Protect your hearing, the world is too loud
27. Alcohol is bad for you
28. Finish coffee before noon
29. Avoid bright lights after sunset
30. If obese, look into a GLP
31. Sleep in a cold room
32. Texting while driving is dangerous
33. Turn off all notifications
34. Limit social media use
35. Don’t smoke anything
36. If you struggle to sleep, read a physical book before bed
37. 1 hour before bed have a calm wind down routine: bath, read, light walk, listen to music
38. The body is a clock and loves routine. Have a daily morning and evening schedule.
39. Avoid long distance travel where you can
40. Baby steps first: incorporate new things slowly
41. Do less… most things don’t work.
Bonus points if you get your blood checked.
Start here, it will change your life.
Mark R. retweeted
Anthropic just dropped data that is a treasure map for founders.
They laid out the exact opportunity gaps that exist today.
Potential usage vs. observed usage.
I distilled the data for you below.
And thank you @PeterJ_Walker for making it into the bar chart they should’ve made originally anyways
Sounds like a general contractor for process automation. Fun to see it described from the outcomes only. There are many of us trained in business analysis from IT backgrounds that have now become AI powered problem solvers. We no longer need a dev team to build solutions!
Bret Taylor, former co-CEO of Salesforce and chair of OpenAI, just redefined the unit of productivity.
It’s not a person.
It’s a process.
Taylor: “I think the atomic unit of productivity in AI is a process, not a person.”
AI won’t replace a worker.
It will compress entire workflows.
What used to take 17 days across departments collapses into hours.
The traditional corporate model measures productivity in person-hours.
The new model measures process-compression.
The incumbent assumption: you buy AI to replace a junior analyst.
That’s a fundamental misunderstanding.
You deploy an autonomous agent to completely collapse the timeline of a business outcome.
An operation requiring 17 days of bureaucratic friction gets mathematically condensed into 17 hours.
You’re not buying a digital employee.
You’re buying the ruthless compression of time.
Using AI to speed up a single employee’s task?
You’re playing the wrong game.
Taylor: “There’s a legal department to do a contract. There’s some finance department, procurement. You probably have IT that’s involved to onboard them into your core systems.”
Friction in the modern enterprise doesn’t come from a single worker.
It comes from the endless hand-offs between siloed departments.
The traditional CEO tries making each department 10% faster.
The winning CEO deploys an AI overlay that autonomously bypasses the human hand-offs entirely.
The algorithm doesn’t sit in the legal department or IT.
It executes the entire thread simultaneously across all core systems.
It doesn’t replace individual workers.
It renders their departmental bottlenecks completely irrelevant.
Taylor: “I think it’s wrong to think about AI as sort of replacing people. In addition to being inhumane, it’s just sort of nonsensical because AI sort of operates in the world of digital technologies.”
The neural network won’t sit at a desk, pour coffee, or shake a client’s hand.
It’s a sovereign engine operating exclusively in the realm of digital friction.
Superintelligence isn’t your direct replacement.
It’s your digital exoskeleton.
The hard part of enterprise execution has never been the human element.
It’s always been wrestling with archaic, fragmented software systems.
When AI takes over the digital process, the biological operator gets freed from the bureaucratic drag.
They instantly shift from manual processor of forms to high-leverage director of outcomes.
And that’s the real transformation.
Not humans versus machines.
Humans commanding the compressed timelines machines execute.
Whoever builds that infrastructure first turns every competitor’s 17-day cycle into a fatal disadvantage.
Because they’re finishing in hours what the rest of the market hasn’t even started.
Mark R. retweeted
So not the fact that it’s just NEWS printed on PAPER?
I was today years old when i found out "newspaper" mean North, east, west, south, past and present
Readers added context they thought people might want to know
No. "Newspaper" is simply a compound word from 'news' and 'paper.'
"News" from Old French 'noveles' and medieval Latin 'nova,' which means 'new things.' "Paper" from Ancient Greek 'papyros.'
etymonline.com/word/newspaper
oed.com/dictionary/new…
merriam-webster.com/dictionary/new…
dictionary.cambridge.org/us/dictionary/…
politifact.com/factchecks/201…
Mark R. retweeted
Enterprise software stocks are crashing across the board due to a huge misunderstanding about agentic AI. It's time to clear up this misconception among more investors, so I've now removed the paywall from what is probably my most important write-up of the year so far. It explains which software companies are really threatened by AI and which are not. buff.ly/jzJYt40
Mark R. retweeted
Goldman just told every SaaS CEO their business model has a five-year shelf life and the market hasn’t repriced accordingly.
The headline number is $780 billion in application software by 2030, 13% CAGR. Sounds like growth. But agents capturing 60%+ of that economics means the profit pool migrates away from per-seat subscriptions toward workflow-completion pricing. The market gets bigger while the legacy revenue model gets smaller. Two things happening at once.
This is already showing up in the data. Seat-based pricing dropped from 21% to 15% of SaaS companies in just twelve months. Hybrid pricing surged from 27% to 41%. Klarna doubled revenue per employee after deploying agents across core workflows. SaaStr is actively downgrading seat counts at vendors because they have 12+ AI agents in production replacing human users.
The math problem for incumbents is brutal. Salesforce charges up to $500/seat/month at top tiers. When one agent automates what ten humans used to do, charging per seat becomes a penalty on the vendor. BCG’s buyer survey found 40% of enterprise customers cite seat reduction as their primary lever to cut software spending. The very AI features vendors are building to retain customers are giving those customers the tool to shrink their contracts.
ServiceNow saw this coming and pivoted to “AI Control Tower” positioning, generating $600 million from Now Assist in Q4 alone. But even with 21% subscription growth and 25% more monthly active users, the stock dropped double digits after earnings. The market is saying: prove the new pricing model scales before we assign a multiple.
Goldman’s own behavior tells the real story. They announced thousands of autonomous AI coding agents working alongside 12,000 human developers, projecting 3-4x productivity gains. Goldman is simultaneously publishing the research that says agents eat SaaS economics while deploying agents internally to eat SaaS economics. They’re the customer proving their own thesis.
The vendors who win will be the ones who wrap workflows in agents and price on outcomes, capturing a share of the productivity gain rather than passing it all through. The vendors who lose will be the ones still counting seats while their customers count agents.
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Valuable perspective. I thrived throughout many of these changes and it took me decades to realize/accept how slowly things change.
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Is your phone listening? Love that someone dove into this! cnet.com/tech/services-and-s…
Need to find an AI thought partner to illustrate the mind map of ideas as we talk. Visualizing connections for myself and others.
Taking notes is great first steps, but we need the next level of group/project facilitation.
Loving the potential for lower cost tools available to more people
A big week for @promise_ai directors.
Congrats goes to @MetaPuppet for creating this Gem! This is everywhere!
Mark R. retweeted
Many of the most important “prompt engineering” skills are management skills: clearly understanding the task to be done & what information is needed to do it; explaining the task to the AI; giving useful feedback to improve outputs; & generalizing lessons learned into a process.
This! It needs to have memory of earlier collaborations to really blow me away, but this would be such a powerful team player.
Last week I saw the future of how we'll all work with AI.
Logan (Google's AI Studio lead) was showing me Gemini's new“real time streaming” feature. He had his code editor open, and casually said via voice 'hey, should I change this function?'
The clip below is wild - you have to see it to believe it.
The AI was watching his screen. Like literally watching - seeing his cursor move, understanding his code, giving real-time feedback. Like pair programming with an AI that never gets tired.
I've been playing with Claude, ChatGPT, building with v0/Bolt. They're all powerful but this was different. This was like having an AI co-pilot actually seeing your screen, understanding context, and helping in real-time.
Different use-case but really bent my mind.
Think what this means:
• Coding – Ask about any line you're looking at
• Debugging – It sees the error in real-time
• Learning new tools – It watches you struggle and helps
• Writing – It sees what you're typing and suggests edits
The tech behind it is really cool:
• Processes entire screen in real-time
• Understands spatial context
• Can handle 500K+ tokens (like reading a book in seconds)
• Remembers your entire session
Google's giving this away free in AI Studio. Yes, they're competing with OpenAI. But for makers, this is massive.
Thanks to @OfficialLoganK for the time and the demo.
It really blew my mind. This is a clip from the full episode of the Startup Ideas Pod which I’ll link below.
In that episode he gives 2 more demos so it's worth watching.
youtube.com/watch?v=6h9y1rLe…
Happy building.
Mark R. retweeted
Most people are still prompting wrong.
I've found this framework, which was even shared by OpenAI President Greg Brockman.
Here’s how it works:
Perspective. Growing up over the last 50 years has been pretty cool
I still cannot believe that I can:
- look at a world map and tap anywhere to zoom in at street level
- instantly access any song, book, movie, tv show, or podcast ever made
- have any conceivable question and get an immediate answer or video explanation
- take a photo or video wherever I am and add it to my massive, searchable, always accessible personal archive
- video call anyone in my life, at anytime, no matter where they are
- watch live sports on a little wireless glass rectangle
- type out these thoughts and have them read by thousands of people, all over the world, a few seconds later
This feels like it would be true. I am very concerned for kids. They are already using AI in middle school to help write. perplexity.ai/page/microsoft…
Respect for longevity and consistency over time as trends and fads come and go.
Be curious about what's new, sure. That's expected.
But it's more interesting to be curious about what's old.
What stood the test of time? What worked before and still works now? What survived through all the jabs that you assumed would knock it out, but didn't?
That's worth attention. That's worth being curious about. Those are the things that are particularly interesting. There are the lessons.
New will always be new. There will always be another new after the previous new. But what made it, what sticks around, what outlasts? What's durable? What's the reason that rare thing is still here?
Longevity isn't a fluke. It's an opportunity to get on board when you missed it before.
Curiosity about things still here isn’t just nostalgia — it’s a strategic way to filter the noise and find what truly matters, what truly works, and what's truly worth investing in.
With the right tool, data is so powerful. Reminds me of @SunFoundation great transparency work years ago and so many important data journalism projects. Hope they doublecheck their data!
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