fxyz
AI agents eat call centers — buy sellers, short outsourcers
AI-powered voice and chat agents will displace human call-center outsourcing, rewarding the platforms building those agents while punishing the labor-arbitrage firms that run the centers.
Result
If held over the last 3 months (Jul 14, 2026 – Oct 13, 2026): +11.1%. Over the same days: Nasdaq +4.9%, Chip stocks +1.0%.
What it holds
- AI Infrastructure & Compute, 40% of the money, +16.3% over 3 months: NVDA, AMZN, MSFT. Selling the picks and shovels of AI agents — GPUs and cloud — captures margin regardless of which agent platform wins.
- AI Agent Software Platforms, 35% of the money, +17.7% over 3 months: GOOGL, ORCL, PLTR, NOW. Enterprise software firms with AI agent products are directly displacing human agents at scale.
- BPO / Outsourcing Short, 15% of the money, +4.7% over 3 months: against SKHX. Labor-arbitrage call-center outsourcers face direct revenue erosion as enterprise clients switch to AI agents.
- Cash, 10%.
The plan behind it
The winners are the hyperscalers and software firms whose AI models, cloud infrastructure, and enterprise platforms power the agent layer. NVDA supplies the GPU compute backbone; GOOGL, MSFT, AMZN, and ORCL sell the cloud AI services that enterprises plug into their contact-center stacks; PLTR wraps it in enterprise deployments. The loser is the outsourcing model itself — SKHX (a call-center / BPO proxy) is the short. Cash is held as a buffer given macro uncertainty around enterprise IT budgets.
What would prove it wrong: Enterprise AI agent adoption stalls — evidenced by outsourcing firms reporting flat or growing headcount and cloud AI revenue growth decelerating below 20% year-over-year.
FAQ
Can I make one from my own idea?
Yes. Write what you believe in plain words at https://f.xyz/create. fxyz asks a couple of questions, builds the portfolio and shows how it would have done over the last 3 months.
Can I turn a post on X into a theory?
Yes. Reply to the post and tag @fxyzai. It tests the view in the post and replies with the 3-month result and a link.
What can it trade?
Stocks (Tesla, Apple, Nvidia), crypto (Bitcoin, Ethereum, Solana), pre-IPO companies (OpenAI, Anthropic), indices (Nasdaq 100, S&P 500), commodities (gold, silver, oil, copper) and currencies (EUR/USD, USD/JPY). One theory can mix them, and bet for or against any of them.
How does it react to news?
On each check it reads the last two days of news on its biggest holdings and says whether the idea still holds. It can make one small change at a time: trim or drop one holding by up to 5 points. On autopilot the change waits 10 minutes so the owner can skip it; otherwise it asks first.
How do I run it with real money?
For real money, tap Make it mine, open your copy and choose Use real money, with an exchange connected: Hyperliquid, Lighter, Lighter (Robinhood), Backpack, Pacifica or Binance. The money stays in your own account there. fxyz can place trades, but it can never withdraw.
Can the AI get it wrong?
Yes. fxyz's AI turns the idea into holdings, and it can get that wrong: add a coin or stock that doesn't fit, or miss one that does. Check the holdings before you put money in. In your own copy, ask its chat to add or drop any of them.
What do the 3-month numbers mean?
What $100 would have done holding this mix over the last 3 months, at real prices. It is a what-if, not a record: past or simulated results are no promise of future ones, and nothing here is investment advice.