Original Title: How Perplexity + Claude Replace an Entire Analyst Team on Polymarket
Original Author: @0xwhrrari
Compilation: Peggy, BlockBeats

Editor’s Note: This article introduces a way to identify arbitrage opportunities on Polymarket and systematize executing them: use Perplexity to do research and pinpoint discrepancies between data and market pricing; use Claude to build trading logic, control risk, and automatically execute; and finally complete trades and cash them out on Polymarket.

The author’s core judgment is that profits come from “structured information gaps.” Market prices reflect the crowd’s intuition more than anything, while data (such as weather forecasts) provides a probability distribution. When the two diverge—and that divergence is continuously captured by a system—it can be converted into stable trading opportunities. Claude is the brain, Polymarket is the wallet, and Perplexity is the eyes—together they form a complete arbitrage loop.

On one hand, this pattern lowers the barrier to entry so individuals can achieve capabilities close to “team-level.” On the other hand, it raises the competitive bar. Once research, analysis, and execution are compressed into a single continuous chain, relying only on experience or manual operation will become increasingly difficult to compete with systematized strategies.

For ordinary participants, the more realistic path is to first find certainty through research, then amplify returns with a system. Whoever can run this method all the way through earlier is more likely to keep delivering stable returns in these markets that look simple at first glance.

The following is the original text:

Among the top 20 traders on Polymarket, 14 of them are actually bots. A Claude-based agent turned $1,000 into $14,216 within 48 hours; while another agent based on OpenClaw, on the same platform and within the same time, was liquidated down to zero.

The difference isn’t code quality—it’s preparedness.

One agent is just fed a generic prompt and told “Trade on Polymarket”; the other behind the scenes is a complete research framework: which niche market to trade, who is already profitable, where the data comes from, and how the underlying mathematical logic holds.

Perplexity AI handles research, Claude handles coding, and Polymarket handles the payouts.

This is the full breakdown—save it.

You can try:

·Perplexity: perplexity.ai

·Strategy lookup: polymarket.com

·Copy-trading bot: t.me/PolyGunSniperBot

·Telegram channel: rari lr

Research layer: From zero to a strategy in 10 minutes

On Polymarket there are dozens of trading categories: politics, crypto, sports, weather. Most people pick based on instinct—this is exactly where losses begin.

With just one deep research query, Perplexity can scan 47+ information sources in under 3 minutes: including Polymarket’s API documentation, Reddit posts where traders share screenshots of P&L, and Twitter analyses that break down wallet behavior.

More importantly, each conclusion comes with citations and source links—not raw text with no proof, but “verifiable data” you can click and verify.

The breakdown is almost immediate:

BTC 5-minute market: The arbitrage window is only 2.7 seconds—this is the domain of high-frequency trading (HFT). You need co-located datacenter servers and at least a six-figure budget.

Sports arbitrage: Profit margins are usually between 1–3%. At least $5,000 in principal is needed to justify the execution risk.

Weather markets: Profit margins are 3–4 times higher. You can enter with $100. Most participants are retail traders pricing based on intuition.

After the first response, Perplexity AI will also proactively suggest follow-up research questions:

“Should you compare NOAA with other weather forecast providers?” — Yes

“Should you look at Polymarket’s fee structure?” — Yes

“What is the historical accuracy of weather predictions across different time horizons?” — Yes

It further unearthed multiple trading wallet profiles. The system even automatically extracted data that isn’t present in the API: entry-timing patterns, average position size, and the distribution of trading frequency. If you had to track these wallets one by one manually, a junior analyst might take an entire day.

And the commonalities among these wallets are very clear: fully automated, running 24/7 all day long, with zero emotion in decision-making. No one is sitting in front of a computer clicking a mouse—these bots trade based on mathematics.

The third query further narrows the focus: what is the best data source for U.S. weather markets?

Perplexity compared NOAA, OpenWeatherMap, and AccuWeather, conducting a systematic evaluation across multiple dimensions such as accuracy, cost, update frequency, and API availability.

NOAA wins on every truly critical metric. Free, 24–48 hour forecast accuracy of 94%, modeling based on decades of satellite data and supercomputer simulation, hourly updates, an open API, and within reasonable usage limits, there’s almost no rate limiting.

After only three queries and ten minutes, you get a complete strategy map: which niche markets to trade, which players are already profitable, and where the data source is.

Without Perplexity, the same research often takes 4 to 5 hours: bouncing back and forth across Twitter, Reddit, various documentation pages, and academic papers—and you can’t even be sure you’ll find the correct sources.

The mathematical logic behind the edge

Polymarket’s temperature markets are binary markets: “Will the temperature in New York this Saturday be higher than 72°F?” There are only two answers: yes or no. Final settlement is either $1 or $0.

But who is pricing these markets? Retail traders. They check the weather app on their phones, and they might casually glance at the 7-day forecast as well. They don’t pull NOAA’s probability distribution data.

The result is: NOAA provides a 94% probability confidence level for a certain temperature range, while the market prices it at only 11 cents.

That’s the outcome shown by the data—and the structural mismatch between it and the crowd’s perception.

For example, NOAA believes the probability that New York’s Saturday falls within the 74–76°F range is 94%, while on Polymarket the price for that range is only 11 cents. So the bot buys at 11 cents. As more information is gradually digested by the market over the next few hours, the price rises to 45–60 cents. The bot sells at 47 cents. Profit per share: +36 cents.

If you operate on a $2 position, the return is +$6.50. If you run 10 such trades per day, that’s $65.

A single trade doesn’t look that impressive. What really gets people excited is what happens after scaling.

That’s why Perplexity’s model council is so important. The query about “optimal position sizing” isn’t handled by a single model—it’s run in parallel across Claude, GPT, and Gemini.

The final answer isn’t a single model’s “opinion,” but the result of convergence among three large language models.

When Claude, GPT, and Gemini independently calculate the same Kelly position ratio and reach consistent conclusions, it’s no longer the kind of “hallucinated output” that may happen—it’s a cross-validated result.

In real operation, if the principal is only $100, then no single position should be more than $2.

Conservative? Of course, conservative. But NOAA still has an error probability of about 6%. Without proper position control, one wrong trade can wipe out all the profit for the day. 6 cities, more than 10 temperature intervals per city—this means over 60 markets to scan every day.

Perplexity’s multi-source analysis further aggregates three independent meteorological research outputs, confirming that NOAA’s 94% prediction accuracy within 24 hours is actually a somewhat conservative estimate. For core metropolitan areas with denser weather-station coverage, accuracy is often even higher.

And this bot scans the market once every 2 minutes. By that calculation, it completes 720 scans per day across more than 60 markets. That level of coverage is something humans simply can’t sustain.

Claude as the “brain”

The entire system is divided into three modules: a scanner, a parser, and an executor.

NOAA scanner:

Polymarket parser (Parser):

Decision logic:

Telegram reports module (Reports):

A typical script only runs if/then logic: if conditions are met → buy. That’s it. And an agent based on Claude will read the “context.”

For example, is a hurricane approaching? NOAA data that used to update once per hour becomes updated every 30 minutes. The agent recognizes that the forecast stability is increasing in volatility and automatically reduces position size. It also reads the news feed, monitors sentiment changes on Twitter, and cross-validates multiple data sources—then dynamically adjusts its confidence before actually placing an order.

This is the difference between a calculator and an analyst.

With a 15-cent entry and NOAA confidence above 85%, that implies at least a 5.6x misalignment between the true probability and the market price.
If you exit at 45 cents, you can lock in 3x returns on every successful trade.

Set the daily maximum loss limit to $50, meaning that in the worst day you would lose at most half of your principal. Then the bot automatically shuts down, and resumes running the next day.

System stack (The Stack)

Perplexity AI addresses the gap in the research layer: niche market selection, data source identification, mathematical validation, and risk assessment—all based on verifiable citations and sources.

Claude addresses the gap in the execution layer: code generation, logic implementation, and real-time adaptive decision-making.

Polymarket is the monetization layer.

Why Perplexity is an asymmetric advantage

Most people underestimate the “research” step. They jump straight to writing code and executing strategies—then they’re confused about why the bot starts losing money on day one.

Perplexity isn’t a search engine wrapped in a chat interface; fundamentally, it’s a research infrastructure.

Multi-model consensus mechanism
Your query isn’t sent to one model—it runs in parallel on Claude, GPT, and Gemini. When all three models independently produce the same answer, you’re no longer facing “possible hallucination,” but a cross-validated signal.

All conclusions come with citations
Every judgment can be traced back to a source. It’s not “I think NOAA’s accuracy is 94%,” but rather: there are research papers, API documentation, and Reddit discussions where traders validate with real P&L. You can click through and verify each item.

Deep Research depth
In under 3 minutes, it parses 47+ information sources: academic papers, API documentation, trading forums, and Twitter data analyses. The output isn’t a bunch of links—it’s a strategy you can execute directly.

Automatic generation of follow-up questions
It doesn’t just answer questions—it tells you what to ask next: “Should you compare different forecast sources?” “Should you break down the fee structure?” It builds the full research path for you.

Compounding effect from speed
10 minutes of research replaces 4–5 hours of manual searching. This isn’t just a convenience improvement—it’s a structural advantage. While others are still browsing Reddit, your bot is already running and generating returns.

Claude is the brain; Polymarket is the wallet; and Perplexity is the eyes.

Without it, you’re trading blindly. With it, before you place your bet, you’ve already seen the whole board.

Research layer → strategy layer → execution layer → profits. Perplexity is the first step—and that first step is exactly where 90% of traders fail.

Don’t skip it.

Most people read through all this, nod along, and then keep trading manually. But the ones who actually act—right now—have Perplexity open in another tab and have started running their first Deep Research query: niche markets, profitable wallets, data sources, Kelly position sizing……

The distance from “knowing” to “doing” is just one prompt.

When you’ve earned your first $6.50 in some weather market, come back and read this article again—you’ll have a completely different understanding.

[Original Article Link]

Click to learn about Lydong BlockBeats recruiting for positions

Welcome to join the official Lydong BlockBeats community:

Telegram subscription group: https://t.me/theblockbeats

Telegram discussion group: https://t.me/BlockBeats_App

Twitter official account: https://twitter.com/BlockBeatsAsia