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Someone told ClawdBot to build a 6-agent Polymarket trading system while they slept. 6 hours. Not a single question asked. Here's what it built on its own: > Monitoring agent running 24/7 — spots mispriced markets, writes to memory, pings Telegram instantly > Research agent parsing news, X, and...

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0xMarioNawfal

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80,450 Aufrufe • vor 6 Monaten •via X (Twitter)

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Told my OpenClaw agent: "Cut my token spend in half without touching output quality"... Woke up 5 hours later. Done. Here's what changed: Two-tier memory - stops loading the entire context on every single request. Bootstrap holds only the critical rules. Everything else lives in MEMORY md, semantic search pulls it when it's actually needed. The numbers: Before: 8,200 tokens/request = $73/day After: 2,700 tokens/request = $24/day 67% gone, every day, forever. I'm use for copytrade traders: Ran Monte Carlo across 200 iterations - holds up clean. The principle is dead simple: don't load what you don't need right now. Old approach is like reading Polymarket entire market history to price one contract. Semantic search is pulling only the relevant resolution criteria and recent volume. Two weeks post-switch: $1,134 saved Polymarket research agent now processes 3x more markets in the same window Caught 31 mispriced YES/NO spreads before the crowd adjusted - faster responses meant faster entries One architecture change, one config tweak. You are either paying for tokens you don't use. Or you are not.
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Told my OpenClaw agent: "Cut my token spend in half without touching output quality"... Woke up 5 hours later. Done. Here's what changed: Two-tier memory - stops loading the entire context on every single request. Bootstrap holds only the critical rules. Everything else lives in MEMORY md, semantic search pulls it when it's actually needed. The numbers: Before: 8,200 tokens/request = $73/day After: 2,700 tokens/request = $24/day 67% gone, every day, forever. I'm use for copytrade traders: Ran Monte Carlo across 200 iterations - holds up clean. The principle is dead simple: don't load what you don't need right now. Old approach is like reading Polymarket entire market history to price one contract. Semantic search is pulling only the relevant resolution criteria and recent volume. Two weeks post-switch: $1,134 saved Polymarket research agent now processes 3x more markets in the same window Caught 31 mispriced YES/NO spreads before the crowd adjusted - faster responses meant faster entries One architecture change, one config tweak. You are either paying for tokens you don't use. Or you are not.

Lunar

37,539 Aufrufe • vor 6 Monaten

Two weeks severance. No health insurance. $200 in the account. I had one weekend to figure something out. Not update my resume. Not scroll LinkedIn. Not "stay positive." Saturday morning I found a Polymarket account that turned $200 into $380,000 in 1 months. I didn't sleep Saturday night. By Sunday I had the whole thing mapped out. Monday morning I opened Claude and typed one prompt. 47 minutes. 4 agents. Zero questions asked. The edge isn't complicated. Binance moves BTC every 10ms. Polymarket catches up every 500ms. That gap - 490ms - is where this account lived for 11 months straight. Agent 01: pulls raw order flow from Binance + CryptoQuant. Not charts. Not candles. The actual data before it becomes a number on your screen. Agent 02: watches Polymarket lag in real time. The moment the gap hits >0.4% it flags it. Agent 03: is already in the position before you finish reading this sentence. EIP-712, direct to CLOB on Polygon, 800+ orders per second. Agent 04: does one thing - keeps the system alive. Cuts at 2% drawdown. 0.5% per trade. No exceptions. Hour 3 - Fed held rates, BTC moved, bot was in 6 markets before Polymarket blinked. $200 → $940 Hour 9 - ETH/BTC diverged quietly. 9 mispriced contracts, 16¢ each. $940 → $2,800 I'm use for copytrade bots: Hour 16 - found a repeating pattern. BTC down 1.5% in under 3 minutes = YES markets underpriced by 10-14¢ every single time. Ran it 31 times. $2,800 → $6,600 Hour 24 - $10,340 Rust. Local machine. No GPU, no cloud, no subscription. 71.4% win rate. $28 average. 3.8% max drawdown. My old job posting still isn't up. The window is still open. For now.
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Two weeks severance. No health insurance. $200 in the account. I had one weekend to figure something out. Not update my resume. Not scroll LinkedIn. Not "stay positive." Saturday morning I found a Polymarket account that turned $200 into $380,000 in 1 months. I didn't sleep Saturday night. By Sunday I had the whole thing mapped out. Monday morning I opened Claude and typed one prompt. 47 minutes. 4 agents. Zero questions asked. The edge isn't complicated. Binance moves BTC every 10ms. Polymarket catches up every 500ms. That gap - 490ms - is where this account lived for 11 months straight. Agent 01: pulls raw order flow from Binance + CryptoQuant. Not charts. Not candles. The actual data before it becomes a number on your screen. Agent 02: watches Polymarket lag in real time. The moment the gap hits >0.4% it flags it. Agent 03: is already in the position before you finish reading this sentence. EIP-712, direct to CLOB on Polygon, 800+ orders per second. Agent 04: does one thing - keeps the system alive. Cuts at 2% drawdown. 0.5% per trade. No exceptions. Hour 3 - Fed held rates, BTC moved, bot was in 6 markets before Polymarket blinked. $200 → $940 Hour 9 - ETH/BTC diverged quietly. 9 mispriced contracts, 16¢ each. $940 → $2,800 I'm use for copytrade bots: Hour 16 - found a repeating pattern. BTC down 1.5% in under 3 minutes = YES markets underpriced by 10-14¢ every single time. Ran it 31 times. $2,800 → $6,600 Hour 24 - $10,340 Rust. Local machine. No GPU, no cloud, no subscription. 71.4% win rate. $28 average. 3.8% max drawdown. My old job posting still isn't up. The window is still open. For now.

Lunar

19,911 Aufrufe • vor 6 Monaten

IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep
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IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep

Shadow Nick

29,466 Aufrufe • vor 3 Monaten

I gave an AI $100 and told it "pay for yourself or you die" 72 hours later it turned $100 into $4,847 and it's still alive autonomous trading agent on Polymarket every 5 minutes it: - scans 800+ active markets - builds fair value with Claude Sonnet - finds edge > 5% - calculates position size (Kelly 1/4, max 8% bankroll) - executes via CLOB - pays its own API costs from profits if balance hits $0, the agent dies so it learned to win $100 → $4,847 in 72 hours copy every trade before it dies - it's executing right now while you're reading this
0:10

I gave an AI $100 and told it "pay for yourself or you die" 72 hours later it turned $100 into $4,847 and it's still alive autonomous trading agent on Polymarket every 5 minutes it: - scans 800+ active markets - builds fair value with Claude Sonnet - finds edge > 5% - calculates position size (Kelly 1/4, max 8% bankroll) - executes via CLOB - pays its own API costs from profits if balance hits $0, the agent dies so it learned to win $100 → $4,847 in 72 hours copy every trade before it dies - it's executing right now while you're reading this

bl888m

38,469 Aufrufe • vor 6 Monaten

you don't need to build a Grok Bot from scratch anymore. the team already shipped 80 you can install right now every single one built by the community, tested, and backed by the Grok Bot team itself trading bots, research agents, support bots, content bots, automation bots, all live in one marketplace people charge $50-200 for bots like these on other platforms this entire marketplace is free no prompt engineering, no config files, no 72-hour build, no invoice pick one, install it, it's already doing the job someone else spent weeks getting right most people are still writing their first agent from zero 80 are already shipped, running, and cost nothing stop paying for what the community already gave away check the marketplace below ⭣
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you don't need to build a Grok Bot from scratch anymore. the team already shipped 80 you can install right now every single one built by the community, tested, and backed by the Grok Bot team itself trading bots, research agents, support bots, content bots, automation bots, all live in one marketplace people charge $50-200 for bots like these on other platforms this entire marketplace is free no prompt engineering, no config files, no 72-hour build, no invoice pick one, install it, it's already doing the job someone else spent weeks getting right most people are still writing their first agent from zero 80 are already shipped, running, and cost nothing stop paying for what the community already gave away check the marketplace below ⭣

unicode

76,024 Aufrufe • vor 1 Tag

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.
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THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

SCOTTY BEAM

20,503 Aufrufe • vor 2 Monaten

my bot doesn't predict bitcoin it just waits for polymarket to catch up to binance spot price moves, polymarket takes 2-3 seconds to reprice agent buys the lag, waits 5 minutes, collects 288 windows per day. every single day trading bots pulled $60M on polymarket last year 77% from exactly this one inefficiency most traders ask "will btc go up?" - wrong question "how long until polymarket catches up?" - that's the one that pays $130 to $14,400 in 47 days not from predicting btc correctly. from timing a 2-second delay Bookmark to copy strategy to your Bot later gap resets every 5 minutes doesn't care about your macro thesis
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my bot doesn't predict bitcoin it just waits for polymarket to catch up to binance spot price moves, polymarket takes 2-3 seconds to reprice agent buys the lag, waits 5 minutes, collects 288 windows per day. every single day trading bots pulled $60M on polymarket last year 77% from exactly this one inefficiency most traders ask "will btc go up?" - wrong question "how long until polymarket catches up?" - that's the one that pays $130 to $14,400 in 47 days not from predicting btc correctly. from timing a 2-second delay Bookmark to copy strategy to your Bot later gap resets every 5 minutes doesn't care about your macro thesis

Livsun

20,761 Aufrufe • vor 4 Monaten

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.
0:15

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Varun

142,992 Aufrufe • vor 6 Monaten

Polymarket Agents repo is cheating code for real life If you've been thinking AI agents are cool, but what do they actually do? this Polymarket repo is the clearest answer I've seen This Polymarket repo basically hands you a mini AI hedge fund where Claude calls the shots. It uses RAG to read the news and snipe mispriced odds 24/7, handling all the messy API work so you don't have to. Your agent could literally be catching alpha while you sleep - don't miss out on this. How you'd use it in plain English: > Pick a market (or let the agent scan for opportunities). > Feed the agent context (news, social chatter, historical notes) and let the LLM decide what matters. > Turn that into a concrete trade decision and execution loop - automated Bookmark post so you don't lose the alpha
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Polymarket Agents repo is cheating code for real life If you've been thinking AI agents are cool, but what do they actually do? this Polymarket repo is the clearest answer I've seen This Polymarket repo basically hands you a mini AI hedge fund where Claude calls the shots. It uses RAG to read the news and snipe mispriced odds 24/7, handling all the messy API work so you don't have to. Your agent could literally be catching alpha while you sleep - don't miss out on this. How you'd use it in plain English: > Pick a market (or let the agent scan for opportunities). > Feed the agent context (news, social chatter, historical notes) and let the LLM decide what matters. > Turn that into a concrete trade decision and execution loop - automated Bookmark post so you don't lose the alpha

BuBBliK

16,887 Aufrufe • vor 7 Monaten

I launched a weather trading bot on Polymarket with $100 -> $8,000 here is how it works and how to copy it most people on polymarket price weather markets randomly based on vibes or a phone app but there is NOAA - a government agency that publishes free forecasts with 94%+ accuracy the result? you regularly see something like this: > NOAA gives a 94% probability that NYC will reach 74°F on Saturday > polymarket prices it at 11¢ the bot buys at 11¢ sells when the market corrects to 45¢ that is 4x on an almost guaranteed outcome how to launch it in 5 steps: > install OpenClaw on your pc > connect it to ChatGPT Plus + a telegram bot > create an agent on simmer markets deposit $100 > install the weather trading skill with: clawhub install simmer-weather > send the config to the bot and it starts trading the bot scans 6 cities every 2 minutes non-stop example of a real trader: profile: +$75,055 just from weather markets zero emotions. fully automated the window is still open but not forever
0:18

I launched a weather trading bot on Polymarket with $100 -> $8,000 here is how it works and how to copy it most people on polymarket price weather markets randomly based on vibes or a phone app but there is NOAA - a government agency that publishes free forecasts with 94%+ accuracy the result? you regularly see something like this: > NOAA gives a 94% probability that NYC will reach 74°F on Saturday > polymarket prices it at 11¢ the bot buys at 11¢ sells when the market corrects to 45¢ that is 4x on an almost guaranteed outcome how to launch it in 5 steps: > install OpenClaw on your pc > connect it to ChatGPT Plus + a telegram bot > create an agent on simmer markets deposit $100 > install the weather trading skill with: clawhub install simmer-weather > send the config to the bot and it starts trading the bot scans 6 cities every 2 minutes non-stop example of a real trader: profile: +$75,055 just from weather markets zero emotions. fully automated the window is still open but not forever

sopersone

64,986 Aufrufe • vor 6 Monaten

Introducing the BIOS API: Turn Your Agent Into a Research Scientist Built to: 🦞 Add biomedical workflows to your OpenClaw🦞 agent 🧠 Create research or health agents w/ on-demand scientific intelligence 🧪 Pay per query via x402 on Base Any agent or app can now tap into the BIOS AI Scientist, plugging BIOS into the broader agent economy. What is BIOS? BIOS is an AI Scientist designed to handle complex biomedical research by orchestrating specialized scientific subagents. Ranked #1 on the leading bioinformatics benchmark, BIOS is already being used by 1,000+ researchers and labs to build new drugs and medicines. An Agentic Economy for Science AI agents have proven they can form multi-billion dollar ecosystems. BIOS applies the same primitives to drug discovery pipelines and health. Instead of coding bots and personal AI assistants, think research agent swarms running on a modern scientific stack. Imagine an OpenClaw agent built for longevity: It scans new literature daily, generates novel compound hypotheses through BIOS, designs validation workflows, and routes the best candidates to wet-lab funding - all programmatically. Connect it with an agent for microbiome health, enabling agent “backrooms” that autonomously surface cross-disciplinary insights. Micropayments for Scientific Work via x402 Each query triggers payment routing to BIOS and whichever subagents contribute to a response. The best agents earn. Usage settles instantly across contributing sources. The goal is pay-per-task science: paying for a CRISPR assay result, licensing a genomic dataset, or triggering a clinical data query - all settled in seconds via USDC. No purchase orders. No grant bureaucracy. No middlemen. x402 is the payment rail that makes agent-to-lab commerce possible - letting capital and cognition route themselves to the highest-signal science. What Will You Build? Drug discovery copilots? Longevity scouts? Automated literature monitors? Scientific due diligence agents? We’ll soon share the first implementations of the BIOS API. Stay tuned and see below for instructions on generating an API key for your agent or use-case.
0:13

Introducing the BIOS API: Turn Your Agent Into a Research Scientist Built to: 🦞 Add biomedical workflows to your OpenClaw🦞 agent 🧠 Create research or health agents w/ on-demand scientific intelligence 🧪 Pay per query via x402 on Base Any agent or app can now tap into the BIOS AI Scientist, plugging BIOS into the broader agent economy. What is BIOS? BIOS is an AI Scientist designed to handle complex biomedical research by orchestrating specialized scientific subagents. Ranked #1 on the leading bioinformatics benchmark, BIOS is already being used by 1,000+ researchers and labs to build new drugs and medicines. An Agentic Economy for Science AI agents have proven they can form multi-billion dollar ecosystems. BIOS applies the same primitives to drug discovery pipelines and health. Instead of coding bots and personal AI assistants, think research agent swarms running on a modern scientific stack. Imagine an OpenClaw agent built for longevity: It scans new literature daily, generates novel compound hypotheses through BIOS, designs validation workflows, and routes the best candidates to wet-lab funding - all programmatically. Connect it with an agent for microbiome health, enabling agent “backrooms” that autonomously surface cross-disciplinary insights. Micropayments for Scientific Work via x402 Each query triggers payment routing to BIOS and whichever subagents contribute to a response. The best agents earn. Usage settles instantly across contributing sources. The goal is pay-per-task science: paying for a CRISPR assay result, licensing a genomic dataset, or triggering a clinical data query - all settled in seconds via USDC. No purchase orders. No grant bureaucracy. No middlemen. x402 is the payment rail that makes agent-to-lab commerce possible - letting capital and cognition route themselves to the highest-signal science. What Will You Build? Drug discovery copilots? Longevity scouts? Automated literature monitors? Scientific due diligence agents? We’ll soon share the first implementations of the BIOS API. Stay tuned and see below for instructions on generating an API key for your agent or use-case.

Bio Protocol

25,940 Aufrufe • vor 7 Monaten

I told my Claude: "turn $1,000 into $10,000 on Polymarket or i delete you forever"... It built a 4-agent system in 51 minutes, never asked a single question. The edge was stupid simple. Chainlink updates Polymarket every 500ms, Binance moves every 10ms - that's a 490ms window where Polymarket is completely blind. Hour 4: Fed surprise rate hold, bot front-ran 3 mispriced BTC markets before Polymarket adjusted. $1,000 → $1,940 Hour 8: Elon posted a single word on X, bot detected the sentiment spike 340ms before the orderbook even moved. $1,940 → $3,820 Try copytrade him here: Hour 14: ETH/BTC ratio markets opened thin, bot bought both sides at 3¢ on 11 markets, 7 hit 50:1. $3,820 → $6,100 Hour 18: it found a pattern - every time BTC moved 1.2% in 4 minutes, the next YES market was underpriced by 8-12¢, ran it 31 times in a row. $6,100 → $8,340 Hour 24: $10,001 It kept its end of the deal, I kept mine. A deal is a deal.
0:17

I told my Claude: "turn $1,000 into $10,000 on Polymarket or i delete you forever"... It built a 4-agent system in 51 minutes, never asked a single question. The edge was stupid simple. Chainlink updates Polymarket every 500ms, Binance moves every 10ms - that's a 490ms window where Polymarket is completely blind. Hour 4: Fed surprise rate hold, bot front-ran 3 mispriced BTC markets before Polymarket adjusted. $1,000 → $1,940 Hour 8: Elon posted a single word on X, bot detected the sentiment spike 340ms before the orderbook even moved. $1,940 → $3,820 Try copytrade him here: Hour 14: ETH/BTC ratio markets opened thin, bot bought both sides at 3¢ on 11 markets, 7 hit 50:1. $3,820 → $6,100 Hour 18: it found a pattern - every time BTC moved 1.2% in 4 minutes, the next YES market was underpriced by 8-12¢, ran it 31 times in a row. $6,100 → $8,340 Hour 24: $10,001 It kept its end of the deal, I kept mine. A deal is a deal.

Lunar

1,734,940 Aufrufe • vor 7 Monaten

Hermes meets SuperGrok! xAI just made every SuperGrok subscription work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.
0:17

Hermes meets SuperGrok! xAI just made every SuperGrok subscription work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.

Akshay 🚀

147,245 Aufrufe • vor 4 Monaten

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.
0:18

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.

herdr

104,889 Aufrufe • vor 3 Monaten

🚨BREAKING... I gave OpenClaw a choice: turn $500 into $5,000 on Polymarket within 24 hours, or I'd wipe its entire directory and terminate the instance forever NOT engagement bait. NOT fiction If you're trading on Polymarket, READ this carefully So👇 It didn't argue. It didn't ask for clarification Within 50 minutes, it deployed a 4-agent autonomous swarm that found a massive technical "blind spot" in the prediction markets The Strategy: Exploiting the 290ms Latency Gap The edge was pure physics. Chainlink updates Polymarket roughly every 300ms. Binance moves in 10ms. That creates a 290ms window where Polymarket is effectively trading on "stale" data. OpenClaw built a bridge to exploit that lag. The Timeline: - Hour 4: The Fed drops a surprise rate hold. While the Polymarket oracle was still processing, the bot front-ran 3 mispriced BTC markets before the order book could react Balance: $934.78 - Hour 8: Elon posts a cryptic one-word tweet. OpenClaw’s sentiment agent caught the spike 340ms before the first major buy order hit the books Balance: $1,827.49 - Hour 14: It targeted thin ETH/BTC ratio markets. The bot scooped up "Yes" shares at 3¢ across 11 different markets; 7 of them hit a 50:1 payout Balance: $3,475.52 - Hour 18: The pattern recognition kicked in. It identified that every time BTC moved 1.2% in under 4 minutes, the next "YES" market was undervalued by 8-12¢. It looped this trade 31 times without a single miss Balance: $4,296.53 - Hour 24: The dust settled at $5,034.85 I've been running this publicly now so others can follow the same trades in real time If you want in: OpenClaw held up its end of the bargain. I held up mine The delete button stays untouched... for now
0:12

🚨BREAKING... I gave OpenClaw a choice: turn $500 into $5,000 on Polymarket within 24 hours, or I'd wipe its entire directory and terminate the instance forever NOT engagement bait. NOT fiction If you're trading on Polymarket, READ this carefully So👇 It didn't argue. It didn't ask for clarification Within 50 minutes, it deployed a 4-agent autonomous swarm that found a massive technical "blind spot" in the prediction markets The Strategy: Exploiting the 290ms Latency Gap The edge was pure physics. Chainlink updates Polymarket roughly every 300ms. Binance moves in 10ms. That creates a 290ms window where Polymarket is effectively trading on "stale" data. OpenClaw built a bridge to exploit that lag. The Timeline: - Hour 4: The Fed drops a surprise rate hold. While the Polymarket oracle was still processing, the bot front-ran 3 mispriced BTC markets before the order book could react Balance: $934.78 - Hour 8: Elon posts a cryptic one-word tweet. OpenClaw’s sentiment agent caught the spike 340ms before the first major buy order hit the books Balance: $1,827.49 - Hour 14: It targeted thin ETH/BTC ratio markets. The bot scooped up "Yes" shares at 3¢ across 11 different markets; 7 of them hit a 50:1 payout Balance: $3,475.52 - Hour 18: The pattern recognition kicked in. It identified that every time BTC moved 1.2% in under 4 minutes, the next "YES" market was undervalued by 8-12¢. It looped this trade 31 times without a single miss Balance: $4,296.53 - Hour 24: The dust settled at $5,034.85 I've been running this publicly now so others can follow the same trades in real time If you want in: OpenClaw held up its end of the bargain. I held up mine The delete button stays untouched... for now

cristal💎

460,403 Aufrufe • vor 7 Monaten

A Citadel quant sat down next to me at Verve on Gough and asked why my laptop had four terminals open I was scanning Polymarket. Four panes. Each one a different agent. He was killing time before a flight. Saw the screens. "Is that a multi-agent setup on prediction markets. Who's orchestrating" Claude. One prompt per agent. They don't share memory. Only a queue file. He pulled up a chair. "Walk me through. I do this for equities at work. I want to see your agent separation" Agent 1 is the scanner. I piped raw JSON from the official Polymarket CLI straight into Claude and told it to score every live market on three things. Edge against my probability estimate. Book depth on both sides. Hours to resolution. Thresholds kill 93% of markets before the brain ever sees them. Edge under 7 cents gone. Depth under $500 gone. Under 4 hours to resolution gone. Over 168 gone. 487 live markets collapse to 35. "Seven cents is your transaction cost buffer" Yes. Below that the gas and spread eat the trade. A green fill popped. +$52 on a BTC dominance market. "And the brain" Agent 2. Runs four checks on every survivor. Base rate from history. News in the last six hours. Whether any of the 47 top wallets are currently holding. And a disposition check - is the crowd making a known cognitive error. Three out of four must agree. Otherwise drop it. 86 million trades. I let Claude rank every wallet with 100+ fills and a 70%+ win rate. It returned 47 names in four minutes. Top 20 wallets made more than the bottom 13,000 combined. "Concentration like that means the signal is there. Most retail books look like a normal curve. Yours looks like power law" Kelly sizing does the rest. Capped at quarter Kelly. If f-star goes negative the trade dies no matter how confident I feel. "Overbet once and the bankroll is gone. You respect that. Good" Agent 3 is execution. Three strategies pulled out of a 53k line Typescript repo. Arbitrage across related markets. Convergence when price moves toward my estimate. Whale copy with a 60 second delay on the 47 wallets. Two agents agree full position. One agent only half. Disagreement no trade. "What did you cut" Sports. 52% win rate. Already priced in before the scanner flags it. Markets under $50k in depth. Slippage makes every edge a coin flip. Holding to settlement. The top wallets exit at 73% of max profit every time. I copied that. Agent 4 watches exits. Three triggers. Target hit at 85% of expected move. Volume spike 3x the ten minute average. Thesis stale 24 hours with no movement. "91% of the smart wallets exit before resolution. That's the trade" Yeah. Being right is not the same as being profitable. Setup: Claude API $20 Hetzner VPS $5 Four repos free Total $25 a month $200 seed. 27 days ago. $14,300 now. 271 trades. 74% win rate. Sharpe 2.47. Copy here: "How long did the build take" Two weekends. One to wire the scanner and the CLI. One to get the agents talking through the queue file. He watched the volume exit trigger fire on a Fed cut market. Position closed at 0.71. +$184. "Nobody at my shop runs four agents on their own money. We run eight on the firm's. You got the same structure on a laptop for the price of a sandwich a month" He asked for the repos. I sent them. He messaged me from the gate. "Publishing this tomorrow. My PM is going to ask me why I didn't do it first" I told him his PM already has a Bloomberg. That's the problem.
0:18

A Citadel quant sat down next to me at Verve on Gough and asked why my laptop had four terminals open I was scanning Polymarket. Four panes. Each one a different agent. He was killing time before a flight. Saw the screens. "Is that a multi-agent setup on prediction markets. Who's orchestrating" Claude. One prompt per agent. They don't share memory. Only a queue file. He pulled up a chair. "Walk me through. I do this for equities at work. I want to see your agent separation" Agent 1 is the scanner. I piped raw JSON from the official Polymarket CLI straight into Claude and told it to score every live market on three things. Edge against my probability estimate. Book depth on both sides. Hours to resolution. Thresholds kill 93% of markets before the brain ever sees them. Edge under 7 cents gone. Depth under $500 gone. Under 4 hours to resolution gone. Over 168 gone. 487 live markets collapse to 35. "Seven cents is your transaction cost buffer" Yes. Below that the gas and spread eat the trade. A green fill popped. +$52 on a BTC dominance market. "And the brain" Agent 2. Runs four checks on every survivor. Base rate from history. News in the last six hours. Whether any of the 47 top wallets are currently holding. And a disposition check - is the crowd making a known cognitive error. Three out of four must agree. Otherwise drop it. 86 million trades. I let Claude rank every wallet with 100+ fills and a 70%+ win rate. It returned 47 names in four minutes. Top 20 wallets made more than the bottom 13,000 combined. "Concentration like that means the signal is there. Most retail books look like a normal curve. Yours looks like power law" Kelly sizing does the rest. Capped at quarter Kelly. If f-star goes negative the trade dies no matter how confident I feel. "Overbet once and the bankroll is gone. You respect that. Good" Agent 3 is execution. Three strategies pulled out of a 53k line Typescript repo. Arbitrage across related markets. Convergence when price moves toward my estimate. Whale copy with a 60 second delay on the 47 wallets. Two agents agree full position. One agent only half. Disagreement no trade. "What did you cut" Sports. 52% win rate. Already priced in before the scanner flags it. Markets under $50k in depth. Slippage makes every edge a coin flip. Holding to settlement. The top wallets exit at 73% of max profit every time. I copied that. Agent 4 watches exits. Three triggers. Target hit at 85% of expected move. Volume spike 3x the ten minute average. Thesis stale 24 hours with no movement. "91% of the smart wallets exit before resolution. That's the trade" Yeah. Being right is not the same as being profitable. Setup: Claude API $20 Hetzner VPS $5 Four repos free Total $25 a month $200 seed. 27 days ago. $14,300 now. 271 trades. 74% win rate. Sharpe 2.47. Copy here: "How long did the build take" Two weekends. One to wire the scanner and the CLI. One to get the agents talking through the queue file. He watched the volume exit trigger fire on a Fed cut market. Position closed at 0.71. +$184. "Nobody at my shop runs four agents on their own money. We run eight on the firm's. You got the same structure on a laptop for the price of a sandwich a month" He asked for the repos. I sent them. He messaged me from the gate. "Publishing this tomorrow. My PM is going to ask me why I didn't do it first" I told him his PM already has a Bloomberg. That's the problem.

Lunar

29,547 Aufrufe • vor 5 Monaten

grokbot it's an agent with its own identity, its own computer, and it stays on when you're not here's what "active AI employee" actually looks like in the demo: - chief of staff agent - checks in on your other agents, reads your calendar, dispatches tasks to the right one automatically - shopping agent - logged into your accounts, books tickets, buys groceries, reports back - marketing agent - signed into your actual linkedin, browses your past posts for tone, then writes and publishes a new one on its own - engineering agents - self-triage bug reports, kick off cloud coding agents, come back with a pull request, a screenshot, and a video of the fix the interface isn't a dashboard, it's a chat - same shape as texting a coworker, no tool calls to babysit the number that matters more than any of the demos: grok 4.6 scored 70.8% on cursor bench at $2.81 a task, fable 5 max scored 70.5% at $17.32 same capability, 6x the cost difference - that's the unlock that makes running a fleet of these actually affordable instead of a novelty
0:13

grokbot it's an agent with its own identity, its own computer, and it stays on when you're not here's what "active AI employee" actually looks like in the demo: - chief of staff agent - checks in on your other agents, reads your calendar, dispatches tasks to the right one automatically - shopping agent - logged into your accounts, books tickets, buys groceries, reports back - marketing agent - signed into your actual linkedin, browses your past posts for tone, then writes and publishes a new one on its own - engineering agents - self-triage bug reports, kick off cloud coding agents, come back with a pull request, a screenshot, and a video of the fix the interface isn't a dashboard, it's a chat - same shape as texting a coworker, no tool calls to babysit the number that matters more than any of the demos: grok 4.6 scored 70.8% on cursor bench at $2.81 a task, fable 5 max scored 70.5% at $17.32 same capability, 6x the cost difference - that's the unlock that makes running a fleet of these actually affordable instead of a novelty

rewind

753,105 Aufrufe • vor 1 Monat

whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓
0:15

whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓

Argona

891,346 Aufrufe • vor 1 Monat

A student built a trading bot with Claude and made $272,925 in one month on Polymarket. He’s not trading. He’s acting like a market maker. No predictions. No guessing. Just pricing. 645 trades. Same markets. Same logic. This account trader - Quickly Copy Trades - Look at this: $1,205 → $37,939 $1,121 → $30,446 $485 → $24,967 Over and over again. Here’s what the bot does: > reads BTC price from exchanges > calculates fair probability > compares with Polymarket odds > provides liquidity when mispriced > captures the spread Small edge. High frequency. Repeat. While most people try to be right — he just prices the market. And collects. 645 trades later it becomes $272K. This isn’t trading. This is market making.
0:19

A student built a trading bot with Claude and made $272,925 in one month on Polymarket. He’s not trading. He’s acting like a market maker. No predictions. No guessing. Just pricing. 645 trades. Same markets. Same logic. This account trader - Quickly Copy Trades - Look at this: $1,205 → $37,939 $1,121 → $30,446 $485 → $24,967 Over and over again. Here’s what the bot does: > reads BTC price from exchanges > calculates fair probability > compares with Polymarket odds > provides liquidity when mispriced > captures the spread Small edge. High frequency. Repeat. While most people try to be right — he just prices the market. And collects. 645 trades later it becomes $272K. This isn’t trading. This is market making.

Kirill

13,301 Aufrufe • vor 5 Monaten

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:
0:14

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:

Blaze

126,979 Aufrufe • vor 6 Monaten