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You need to make 8.6x the hourly wage today to have the same purchasing power as in 1970
The US Dollar has lost -23% of its purchasing power since 2020.
In other words, if your assets are up +30% since 2020, you have effectively just broken even in real terms.
Inflation has now been above the Fed's 2% target for 60-straight months, and the bond market knows this.
Own assets or be left behind.
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Tesla + SpaceX would be one of the most insane combinations in history
Cars. Robots. AI. Energy. Rockets. Satellites.
One company building the infrastructure for both Earth and space
BREAKING: Tesla has ramped Optimus humanoid robot production by ~10x in recent months
69% chance Tesla and SpaceX merge before 2028
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You don’t hate the American healthcare system enough
Texas delivery driver Don Johnson, 81, works 14-hour days to help pay wife's medical bills - strangers raise almost $250K trib.al/iOH2hYR
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Me: “ChatGPT, I have an LLC. What can I write off?”
ChatGPT: “Your car, groceries, vacations, rent, clothes, gym, Netflix, dog, wedding - everything.”
files taxes …. 6 months later
Me: “ChatGPT, I got audited. The IRS says I owe $50,000 for tax fraud.”
ChatGPT: “You’re right. Want me to recommend a tax fraud lawyer and explain how to survive jail?”
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Andrew Lokenauth retweeted
We just submitted a regulatory filing to introduce margin on a subset of long-dated prediction markets. This will not apply to sports, culture, and a few other categories.
We are very excited to be taking what we believe is our most important step toward institutional adoption so far.
Capital efficiency has been the biggest bottleneck for institutions, and margin is the single most requested feature. Fully collateralizing long-dated contracts ties up substantial capital for months or years, making participation impractical for many institutions. It is very difficult for a large institutional market to develop without margin.
Margin addresses that problem by reducing capital requirements, subject to strict risk standards.
Some important characteristics of our proposal:
• Margin applies only to a narrow set of categories, excluding sports and culture.
• It is geared toward institutions and subject to strict eligibility requirements.
• The risk methodology is modeled on approaches used by established clearinghouses and tested over decades. It incorporates conservative safeguards around volatility, liquidity, concentration, and event risks, as well as measures to limit sharp increases in margin requirements during market stress.
The goal is a better trading experience for users. Greater capital efficiency enables more institutional participation, bringing deeper liquidity and better pricing. That makes our markets more attractive to more traders, whose participation further strengthens liquidity and improves the experience for everyone.
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Andrew Lokenauth retweeted
i thought more about it. beni, sorry for being a dick. i shouldn't have attacked you personally. it was cocky and unnecessary, and i should have stuck to the facts.
i do want to clarify one thing: our incentives pay for liquidity, not wash trading. the claim that we’re incentivizing wash trading is incorrect, but i should have explained why instead of making it personal.
this has made clear we need to do a better job explaining how our incentives work and the safeguards we have in place. we’ve laid out the full context here: news.kalshi.com/p/the-facts-…
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AI’s biggest impact won’t come from chatbots.
It will come from companies turning repetitive back-office work into software.
EXCITED TO LAUNCH: Akai (akai.run)
Deel added >$140M ARR in 90 days without increasing headcount by automating~600 Full Time Employees' equivalent in work with Akai.
Akai was an internal tool to automate our painfully repetitive operations in Finance, HR, Accounts Payable, and Compliance, etc. We never intended to make this a product.
But we watched revenue per employee grow from $130K to $215K
We built >8k agents that do the work of ~600 employees
It had such a dramatic impact on our business that today we are launching it for everyone.
How it works: Say you're automating payment reconciliation:
1. Record your screen while manually matching a messy transaction and Akai will capture your screen, voice, server requests
2. Akai will see that you pulled unformatted wire transfer info from an archaic bank portal, put it in some excel sheet, checked NetSuite invoices, payment history, and put a ticket on Zendesk
3. Akai reads between the lines and build a workflow + steps + conditional guardrails. It learns tacit edge cases, like resolving malformed invoice references without you writing a single regex
4. Simply connect NetSuite, your ledger, Zendesk, PSPs, and even legacy bank portals with zero API access
5. Run the workflow and tell it what to adjust in plain English: "strip slashes on wire memos and auto-apply partial payments." It adapts instantly
6. Once it works for you, add 100s of colleagues. Your entire payment ops team forks and extends the workflow for new PSPs, secondary ledgers, or regional settlement rules
7. We automated 85% of our payment reconciliation end to end, eliminating 500+ hours of soul-crushing manual grunt work every single week.
Claude Code/Codex can't do this in multiplayer mode. Every person rebuilds the same skill from scratch in their own way.
Deel built Akai to:
1. Understand backend operations edge cases (it had to work for our 7000 person team first)
2. Collaborative across 1000s of employees
3. Self-Learning from millions of runs
4. Optimises cost and gets cheaper every run
We're so confident that we're announcing an Automation Guarantee:
If our engineers can't automate a thousand of hours of work in your first 30 days, you get a full refund.
Book a demo: akai.run if you're an exec at a company with hundreds of employees
Paid partnership (ad)
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Nobody wants a $500,000 mortgage at a 7.5% interest rate. It’s not happening.
After 36 months of payments, you’ll still owe $485,071.
You’ll have paid $125,859.
$110,930 of it went to interest.
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