Prithvir

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Age 2.2 Yıl
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Software loans yields exploding to 12% while broad leveraged loans sit at 8.5%.
lenders smell blood as AI murders legacy SaaS.
Refinancing wall incoming.
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pre claude: backend devs get 3 months. frontend devs get 2 weeks.
post claude: backend gets 2 weeks. frontend gets 1 week.
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the most underappreciated chart in the world right now
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agi will be deflationary. productive output will rise. goods and services will get cheaper.
a barbell strategy for market cap accretion will start to appear.
end1: hyper-financialization
when people have more time and don't have to worry about food, clothing, and shelter they turn towards financial status games.
we will continue to see explosive growth in instruments that price short-term uncertainty:
• perps
• prediction markets
• options
• spot speculation
• sweepstakes-style trading
the moats here are liquidity network effects, and lock-in similar to the sunk cost from time spent upleveli
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Vibe coding is like trading with 10x leverage
If your vibe-coded app somehow manages to hit
• strong K-factor growth and
• smiling retention curves
You'll probably accumulate tech debt. Three possible solutions:
1. Service the interest
Keep shipping. Pay absurd bills to AWS, Vercel, and others because the system was never designed properly.
2. Pay down the principal
Refactor the stack at a large opportunity cost. Engineering cadence slows, competitors ship, and piranha-fish your user base.
3. Refinance the debt
Hire and deploy engineer + agent combinations whose job is continuously untangling
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No second date, but at least she understands the nuances of prop AMM microstructure and Black–Scholes models for prediction markets.
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Margin debt just hit a new all-time high.
Yes, historically this signals we’re late in the cycle.
But it also reveals something structural.
Leverage compresses time horizons.
When positions are financed with debt, risk must be managed continuously.
That is why the fastest growing instruments today are:
• 0DTE options in equities
• perpetual futures in crypto
• prediction markets for real-world events
They all price short-term uncertainty.
As leverage rises, demand shifts toward markets that clear quickly and settle quickly.
Perps, 0DTE, and prediction markets are the natural endpoint of that e
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do you trade equities, commodities, and indices onchain?
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There’s been misinformation circulating about @tradefoxai's fee structure. Here are the facts.
Since launch, aggregate fees as a percentage of total volume traded have been 0.33%. That figure is before any cashback or referral fees are paid out.
How it works:
We do not use a flat fee. We use a Gaussian distribution. We believe this structure is better than any flat fee model.
In prediction markets, most uncertainty lives near the middle of the curve. That’s where price discovery happens. As price moves toward 0 or 100, uncertainty collapses quickly because the outcome is closer to being decide
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Prediction markets called the US striking Iran before the headlines did.
Now they’re pricing:
1. Khamenei out as Supreme Leader by March 31: 47.5%
2. By June 30: 61.5%
3. By 2026: 68.5%
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Remember folks
Marxist eschatologists reinvent how the end of the world is near every decade
Don’t fall for it
Neither war nor AI doom can take away your life’s meaning since none of you had any purpose in the first place
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Interesting piece in @business this morning
Transactions, volumes, and open interest continue to go parabolic.
But optics and mass market perception could still cap the ceiling.
The next unlock will be institutional markets with unambiguous resolution criteria and explicit hedging utility.
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Data Science skill levels in 2026
1. Ask AI to write a query and iterate until it works
2. += Optimize query efficiency for cost and performance
3. += Translate a business question into the right query
4. += Design and run hypothesis tests
5. += Design and execute A/B tests
6. += Allocate capital based on experimental evidence
Prompt operator to capital allocator
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Hyperscaler capex at $646B is
1. more than the combined military spending of Germany, France, UK, Japan, Italy, Canada ($350B)
2. equivalent to the GDP or Singapore, Sweden, Argentina ($600B)
3. Equivalent to the US bank loan growth ($700B)
4. Slightly smaller than US defense spend ($917B)
5. More than half annual growth in consumer spend ($1T)
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if you're inner circle isn't discussing
1. neg-risk
2. bonding markets
3. merge split arbitrage
4. approximate airdrop size
5. nonce-based order cancellation
congrats, you are blessed
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Key Takeaways from the Federal Reserve paper:
"@Kalshi and the Rise of Macro Markets"
The Fed just published a 41-page working paper evaluating Kalshi as a macro forecasting tool.
They compare prediction markets to:
- Fed funds futures
- Secured Overnight Financing Rate (SOFR) options
- Bloomberg consensus
- Blue Chip surveys
- Survey of Market Expectations (SME)
- Survey of Professional Forecasters (SPF)
1. Real-time, full distributions
Surveys give point forecasts. Infrequent. Often stale.
PMs give:
- Continuous updates
- Full probability distributions
- Intraday reactions to news
- Density
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Apple is the only adult in the room
1. AirPods alone generate more revenue than all of Anthropic’s products and services combined
2. OpenAI plans to spend $100b a year to generate $14b in revenue
3. Apple will spend $1b per year to license Gemini, which will likely increase hardware sales by $20–$80b
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