I count what others feel | Prediction market portfolios | Sport·Math·Edge | Models, not magic | @CoinMarketCap https://xitter.cf/t.co/krp0rc4MKl

Joined May 2012
Prediction markets have a problem few people talk about On smaller events the books are thin @magicmarkets One of the best builders on Polymarket, 5th by 30d volume >> 25+ liquidity providers >> One order book >> One of the best prices, from whichever source has it >> Zero commission NFL. NBA. MLB. Premier League. Champions League. Mexico Liga. NCAA. ATP. Esports Thin books were never a prediction market problem They were a fragmentation problem Capital goes where the best price is at size Now its all in one book
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Tested @OpenBot_ on Windows with a free OpenCode model, no API key needed I set up an agent to check Snitch3, list its key details and save them to a Markdown file It got the job done in about three minutes, and the details matched the site The rough part was watching it work: the chat showed broken fragments of text instead of a clear progress update
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I ran the free Agentsy Report scan on Probly The AI description was accurate: a prediction market platform covering politics, sports, crypto and finance But PROBLY appeared in only 6 of 14 answers and its own site was cited in just 2 The clearest finding: across 8 answers to unbranded discovery questions, PROBLY appeared zero times AI can describe a product correctly and still miss it when people search by category
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Builder codes turn perps into a distribution layer for Polymarket For terminals, the edge is capturing flow across event-driven and continuous markets under one roof
Builder codes are now live for Polymarket Perps. Integrate perps directly into your product and let users trade perpetual markets alongside predictions - all without leaving your product.
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Glad to see you taking part in TestDrive! I been doing the tests myself, and its nice to see ppl sharing their experiences with different tools Curious to see what you end up testing and what you think of it
I've tested a lot of platforms, so I joined a rewarded Test Drive from @testdriveso to check out the Test Track. The UI is clean, everything feels intuitive, and signing up with X took 2 seconds. I’d just like to understand the leaderboard criteria better. Really enjoyed the platform and would love to join more test drives in the future!
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Sharps figured this out a long time ago Nobody serious takes a first deposit bonus, because the real bonus is a sharper price on every single trade Same logic here: a fee waiver is a one time discount, no fees on NBA is a lower cost basis on every position you ever take
Flash sales come and go. They’re nice while they last. But we cannot wave fees for NBA games because we never have fees on NBA games.
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The real edge in funding arbitrage isnt finding the highest rate Its finding a spread that survives fees, slippage, margin requirements and funding reversals 40% annualized rate means little if you can only capture it for a few hours or need twice the capital to keep both legs safe Net return on deployed capital matters more than the headline APY
Top 3 Funding Arbitrage Strategies Bookmark this so you can test different methods You can already do proper arbitrage inside one venue or across a few 1. Spot-Perp (classic) One of the most common strategies in my book When funding is positive (longs pay shorts): buy spot + short equal notional in the perpetual Total cost of the hedge < the funding you collect You need the same notional on both legs so the price movement cancels Works cleanest on major coins with deep books 2. Perp-perp funding arb Same asset, different funding rates on two exchanges Long the venue with the lowest (or negative) funding + short the one with the highest You collect the spread while price risk nets to zero We used this heavily when one venue stayed elevated while the other mean-reverted 3. Lending + Short Perp Deposit the asset into lending (earn APY) and short the same size in the perp You collect two yields: lending interest + funding when it’s positive The position stays delta-neutral (price movement cancels out) Works when both rates are healthy and stable Main cost is lower capital efficiency and extra risk: smart-contract on the lending side plus liquidation risk on the short Exit if funding flips or the lending APY collapses
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I'd nominate @desearch_ai (SN22) for a @testdriveso It brings web and X search into the Bittensor ecosystem and I test it on a practical research task: can it find recent claims about a subnet and surface the original sources so you can verify them? Search quality matters less if you still have to hunt down every source yourself
TestDrive Tool Scouting 🔎 Found a tool or a creator more builders should know about? Send them our way. If you find a tool or creator worth a test drive, we reward you for it. Quote-post this with your find 👇
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The price on screen isnt always the price you pay On Liverpool vs Villarreal, Polymarkets draw costs 21.8c all-in, while MagicMarkets offers 20.8c Thats a $12 difference in potential payout on a $100 trade Across 100 comparable trades, thats $1,200. Same stake, different execution price Thumper is a free Chrome extension that puts @magicmarkets prices next to Polymarket sports markets, so you can compare the real cost before trading Check the price Then take the trade
1/ i built a chrome extension for @magicmarkets that shows you when polymarket isn't the cheapest place to take a sports position it's called thumper. Free to use, no account required 🧵
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Table 6: in the sim the edge leaks with time and size 100 ms already costs 8.6 points of profit Half participation keeps 56.5% of guaranteed profit at a higher return on capital Orders with a loss climb from 14.2% at 100 ms to 22.1% at 1 second The climb is execution, not variance Variance you accept, errors you engineer out
A one-second delay left 22.1% of simulated Polymarket arbitrage orders losing money. Researchers replayed full order books across linked contracts, accounting for spreads and fees. Add that delay, and only 54.3% of orders filled completely. The problem: the profit guarantee depends on getting the whole basket. If some legs fill and others disappear, you’re left holding an exposed position. The delayed strategy still retained 79.3% of its baseline profit overall. But a profitable strategy can contain plenty of losing executions. These are historical simulations using June–August 2026 data. A useful reminder that spotting contradictory prices and actually collecting the difference are separate jobs.
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Paying a global network to break AI models and generate retraining data beats a closed QA team every time. SN26 is one of the cleanest real-world use cases on Bittensor / bittensor:native
Angle 1: The Taped Sign A tiny piece of tape A very different reading In 2020, McAfee showed that tape could make an older vision system read 35 mph as 85 mph For automakers, a misread sign can become a safety and liability risk. @perturbaix helps find these weaknesses before deployment On Bittensor Subnet 26, miners compete to find tiny changes that fool AI models Validators check that each attack works and remains imperceptible. Copies earn nothing Customers get robustness scores, vulnerability heatmaps, and verified data for retraining Image-model testing is live Text, LLM, and multimodal attacks are still on the roadmap. Find weaknesses before attackers do #PerturbVideo
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I tested @FishAudio Drama 3 with a suspense scene built around four cues: [whispering], [confident], [afraid] and [sigh] It generated two takes in about 13 seconds each, so comparing versions was easy What I like is that delivery instructions live right in the script One improvement: make multi-speaker setup clearer. I ended up with Verity on both speaker blocks, and it wasn't obvious how to assign a distinct voice to each character
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Angle 1: The Taped Sign A tiny piece of tape A very different reading In 2020, McAfee showed that tape could make an older vision system read 35 mph as 85 mph For automakers, a misread sign can become a safety and liability risk. @perturbaix helps find these weaknesses before deployment On Bittensor Subnet 26, miners compete to find tiny changes that fool AI models Validators check that each attack works and remains imperceptible. Copies earn nothing Customers get robustness scores, vulnerability heatmaps, and verified data for retraining Image-model testing is live Text, LLM, and multimodal attacks are still on the roadmap. Find weaknesses before attackers do #PerturbVideo
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AlphaRidge puts research, screening, and automation in one place instead of five tabs and three subscriptions. A trader finds a setup on the screener, turns it into a rule, and the rule keeps running and alerting even with the browser closed. @alpharidge_ai maps a few ways the workflow actually closes: > Screening on news: Sort the whole market by 7-day sentiment, event clusters, and impact scores instead of just price and volume. > From idea to rule: Paste a TradingView Pine script into RidgeScript, test it, then arm alerts to Discord, Telegram, or email. > AI that shows its work: The analyst writes screens and marks up charts, then surfaces the exact platform data it used so you can check it. The neat part is the news layer. Miners on SN45 turn hundreds of thousands of articles a day into screenable sentiment and events, so the screener can look at what is being said, not just what already happened. Paper trading is free today. Live brokerage execution is still rolling out. The AI cites its sources, but you still have to confirm before anything is placed.
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Haaland's Norwegian passport says Norway His thermos says Argentina
Gracias #JulianAlvarez @enzofe17 @gerorulli for introducing this lovely drink 🧉
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I saw that @heydittoai walked through Ditto v2 at Exploit Summit, including the bit where an agent switches platforms and keeps the context. Their own write-up uses a case that is basically one sentence: point the new agent at the old one and tell it to mind meld. No rebuild. To give you some more context on this, a normal chat remembers you only inside that app. Claude does not know what you told Cursor, and a new agent starts from zero. But if the spec changed in Telegram, or you moved from one coding agent to another, Ditto v2 keeps one memory under the tools and waits for a yes before it sends or edits anything risky. So the flow would look something like this: ▸ You say it once, in Claude, Cursor, Codex or Grok, and the others can already use it. ▸ Telegram and Slack sit next to the docs and the code, so the agent can search the decision, not just the repo. ▸ A workflow or browser agent runs the job, and the step that could do damage waits for your approval. Depending on the tool, you stay in that chat or leave with the memory exported. This ties back to what I wrote before: the models got good at answering, but you are still the switchboard between them. That’s the part Ditto v2 is building for, even when the handoff is a single sentence. What other agent handoffs should I look into?
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SayGM (SN28) might be the best AI altcoin that noone is talking about 💎 This $TAO subnet has rapidly become a blue chip in the Bittensor ecoystem Why? First of all, their new desktop app allows anyone to access Claude, ChatGPT, Gemini, and Llama for up to 70% cheaper and privately Currently at $5M ARR and growing 🤑 Secondly, their new growth marketing affiliate program "Proof of Customer affiliate pool" is turning heads: - @say_gm_ pays people who refer new developers that actually spend money on its AI gateway - You can earn up to $1 worth of SayGM Subnet 28 alpha for every $1 your referrals spend during their first 30 days Example: you refer a developer who spends $1,000 -> you could earn up to $1,000 worth of SN28 alpha - The rewards do not come from SayGM's normal business revenue or marketing budget. They come from a pool funded by Subnet 28 emissions So now they have an amazing product and an effective growth strategy Sky is the limit here 🚀
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DeepSeek V4.1-Flash-1017 on SayGM isnt just another model its an engine for agentic terminals: screenshots -> parsing -> odds -> signals
Say gm to DeepSeek V4.1-Flash-1017 Now available on SayGM, including confidential inference, at 10% below list price. Thanks to @kubetee for getting it onboarded on day zero. New model, ready to use.
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The event itself isnt always where the mispricing is The market might price the probability correctly but still get the asset's reaction wrong Thats the opportunity conditional markets can unlock
One price in. Every future out. Spot blends every possible outcome into a single number. If Market splits it back out: the asset’s price in the world where the event happens, and in the world where it doesn’t. Trade the future you believe in.
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TradingView for charts MarketSurge for stock ratings Koyfin for research Three subscriptions costing around $289/month @alpharidge_ai brings charting, stock ratings, market-wide screening and strategy automation into one platform at a lower cost The difference isn't just fewer tabs Your trading rules can run inside the same platform where you research the market
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