10000000x engineer • I like Solana, Vercel, Tesla and long walks in the park 🦮 https://xitter.gq/t.co/2AEQzHctRA @Streamstar_app
New York, NY
Joined May 2010
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so the foodie himself @dylan_yingling is coming to visit nyc in Feb
I have my list but where should we eat?
Beautiful
Introducing @leapxyz, a Solana Labs Company.
Built by the team behind Dialect and integrated with the best of the Solana ecosystem.
Available now in early access 👇
Nick Kalpakis 👤 retweeted
Introducing @leapxyz, a Solana Labs Company.
Built by the team behind Dialect and integrated with the best of the Solana ecosystem.
Available now in early access 👇
I've seen these long reasoning responses before
*copium*
The floor is in... we could go down another 10% in tech valuations, which would be the ultimate buy time for me.
Every spare dollar I can find in the couch goes into $tsla $SPCX $UBER $AMZN $SHOP $MSFT $GOOG and $AAPL
Here's what will happen:
1. The Dems are going to force us to exit Iran... President Trump will claim a Bush "mission accomplished!" and take the win for his legacy.
2. Inflation drops
3. Dems will come out in support of Data Centers and AI, in exchange for repealing tax cuts on the wealthy and some regulation on frontier models.
4. President Trump takes credit for brokering this deal and takes a second win for this legacy.
5. Ballroom reaches completion... @realDonaldTrump throws a year of ragers. Third win for his legacy
6. Pardon paloooooooza... autopen on fire.
7. Markets top tick and set new records.
Bookmark this... and @grok please remind me of this every 1st of the month @bot
"Grok how much did NVIDIA lose today"
About $330 billion in market capitalization so far today (as of mid-morning trading on November 5, 2026).
It no longer makes sense for companies to keep API’s private. All I want to do is build wrappers on top of apps so that I can create my own personalized experience with their product
Interesting to reflect on the last stretch of tech cycles.
2020–2022: Near-zero rates, pandemic digital demand, and a record VC surge fueled a massive capital inflow. Companies aggressively overhired, treating headcount growth as a proxy for momentum and assuming the boom was permanent. Then the Fed’s rate hikes in 2022, normalizing demand, and the end of “growth at all costs” triggered a sharp rewind, hundreds of thousands of layoffs across 2022–2023 as firms cut to restore profitability.
2023–now: Another huge capital wave, this time centered on AI after ChatGPT. Funding into AI exploded (tens of billions in 2023, scaling toward $200B+ annually more recently), while hyperscalers poured hundreds of billions into data centers and compute. The pitch is efficiency and productivity gains with fewer people. But a different constraint is emerging: AI infrastructure is hitting real physical bottlenecks, GPU/HBM supply, advanced packaging, grid connections, power generation, transformers, and energy costs. Data center electricity demand is projected to roughly double by 2030, and many projects face multi-year delays. Result: systems that look efficient on paper can be far more expensive to operate at scale because supply can’t keep up with demand.
Same pattern, different bottleneck. Cheap capital first inflated headcount, then compute. The open question is whether the current AI buildout delivers the promised efficiency before the cost of power, chips, and infrastructure forces another correction or simply shifts the pressure somewhere else.
