@johnrushx Yeah, the new world would likely be less "open" for technology sharing
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faces
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Few predictions nobody has thought of yet
1. Open Source movement gonna end because AI can rewrite any oss repo into a new code and commercially redistribute it as their own.
2. Companies gonna use AI to generate their none core software as a marketing effort (cloudflare rebuilt nextjs in a week).
3. Corporations gonna switch from startup acquisitions to solo makers (e.g. Peter, OpenClaw).
4. The entire business moat gonna go from the quantity of resources to their quality. In the age of infinite leverage, the companies with be measured by the smartest employee. So talent war will be insane, billions gonna be spent on it.
5. Building products is becoming easier but distribution is becoming harder because there is 1000x more competition now, just like in the music, a long time ago one could make an okay song and it would get its share of the attention and now every song is just one of one billion songs made today…same here.
6. Since we switched from traditional UX to an agentic one (chat based), and most of our business and personal life runs via Claude code, codex or OpenClaw, this completely changes the world of UX. Your next product should be “build something agents want” instead of “build something users want”.
99.99% of the usage gonna come from agents instead of users.
7. Digital jobs gonna be gone, only C and manager level jobs gonna remain, but everything else to be replaced by AI (this is a reality for people like me already a while ago)
8. Startup founders gonna search for a moat by building products in the intersection of a digital and physical worlds
9. Some, if not most founders, gonna completely pivot into offline local businesses.
10. Coders gonna go from normally distributed salaries into average getting paid peanuts and top 0.001% paid millions and 0.00001% hundreds of millions, just like sport super stars.
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The most successful projects from this cycle actually messed up their charts and users with their automatic buybacks. The early cycle darlings like $HYPE, $ENA, and $JUP topblasted many millions at frankly ridiculous prices on a fair multiple basis.
This led to many retail fomo buying these tops (price drives narrative) and getting rekt. All of the founders of these projects drank too much coolaid of this self-reinforcing thinking the multiples were justified.
After months of decline and no clear path to the previous high prices, some are blaming the mechanism saying “price keeps correcting from the previous (too high) level, buybacks dont work”.
This is just as wrong a statement. How many times do we relearn basic economics truths from hundreds of years of financial markets?
Sure if there isnt enough to pay developers to build then dont spend the limited funds on tokens. But once there is success and consistent revenue— as a holder what is even the point of the token if there is no dividend or buyback or at minimum super clear financial utility?
I propose a more nuanced solution to this “to buyback or not” discussion-
Buyback amount that depends on the price is a good target—
If price is cheap you want to buyback as much as you can as you can have a huge % supply taken out. When market is too hot slow it down.
Some founders more comfortable with traditional buyback decisions made my the CEO/management can do it ad hoc (like, you know, real companies have always done).
But there are programmatic ways for more decentralized protocols to do it if transparency and predictability or legal concerns are a priority—
One simple way is to use a calculated price to earnings ratio. It can be designed by each protocol to suit its specific details. One potential example-
Take an ema of revenue (decide the half-life of time that makes sense) Annualize this as your earnings number
Every day/block of revenue—
if the token price that can be achieved with the buyback is a PE ratio of under 4 buyback 100%, if 4 to 6 buyback 75%, if 6 to 8 buyback 50%, if 8-10 buyback 25%, over 10 dont buyback.
All revenue remainder that gets kept goes to buybacks on buying dips that just looks at price ema. Eg buyback from this reserve at a speed that increases when the price is at very low levels of the last 90 day price ema. This helps plunge protection.
Yes this proposal takes a bit of sophisticated financial engineering compared to all or nothing buybacks, but after the failure of things like web3 gaming, web3 social, metaverse and the like, it should be clear by now that crypto is finance and finance is crypto. If you are a serious project and dont have a finance expert on your time thats fine but you should at least the use a top external advisor or specialized firm to assist.
If Jupiter or other team with high revenue want me to help design something like the above for them I’ll do it for free, you can reach out.
⚔️ SIONG@sssionggg
what do you all think if we stop the JUP buyback? we spent more than 70m on buyback last year and the price obviously didn’t move much. we can use the 70m to give out for growth incentives for existing and new users. should we do it?
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@ColdBloodShill TSLA at $460 feels like one of those too obvious setups.
Markets love symmetry — same reason I’m positioned in $GHT early.
@Gifthorse_hub
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$TSLA here at $460 might be the easiest trade of 2026 that you need.
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faces retweetledi
@johnrushx The brightest minds on the planet again thinking only how to place ads everywhere
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@faces I will display the job cards 2 per row when there’s enough jobs added
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I'm in no way a designer of any kind, but I think I cooked with this one 😍
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@gregisenberg "get reorganized from the grounds up" - I think you're putting it too mildly
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THE BIG AI QUESTIONS I’M CURIOUS ABOUT FOR 2026 AND BEYOND
1. If robotics costs fall and reliability rises, what new blue-collar industries get reorganized from the ground up?
2. What happens to commercial real estate demand as teams shrink and output rises due to AI?
3. If foundation models continue improving at their current pace, how does this reshape what speed means in company building?
4. When AI tutors outperform traditional education for most subjects, how do schools reposition? Does education shift from “teaching” to “socialization + credentialing”?
5. If AI improves medical diagnostics and care routing, how do hospitals change capacity planning? Do outpatient clinics become the center of the American healthcare system?
6. When AI drives mass personalization in advertising, what happens to media buying? Do agencies shift from media arbitrage to creative taste-making?
7. If consumer AI runs wellness, nutrition, and physical optimization automatically, what industries benefit most? Do supplements, gyms, and wearables explode or consolidate?
8. When manufacturing robots gain AI reasoning, what product categories become newly profitable to build?
Do we see a U.S. manufacturing resurgence?
9. When every consumer has an AI “money coach,” how do banks and fintechs shift product strategy? Do personal finance apps melt into the background?
10. If AI creates hyper-realistic synthetic data, how does that change machine learning itself? Do startups train world-class models without ever touching real data?
11. When autonomous vehicles move from pilot to scale, how do suburbs, housing, commuting, and retail reorganize? Maybe real estate get a once-in-a-generation reshuffle...
12. If vertical AI for healthcare, law, real estate, and logistics each gets its own “GPT moment,” what new billion-dollar niches unlock? Every industry gets its own model, its own moat, its own Cambrian explosion.
13. When compute becomes the scarcest resource in the world, what becomes the most mispriced asset class today? Attention? Data centers? Energy? Chips? Land near power?
14. Once every professional has personal agents, what new “agent-first” tools become the equivalent of spreadsheets, Slack, or Figma? Huge new software categories appear.
15. As AI-driven customer support resolves issues instantly, how do brands compete on experience?
16. If agents monitor your health metrics 24/7 and schedule interventions automatically, how do gyms, supplements, and wellness brands reposition? Will products align around measurable outcomes?
17. When agents can run an entire e-commerce funnel sourcing, branding, ads, customer service... what new types of single-person brands appear? Does the DTC “one-person empire” become possible?
What are you curious about?
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