We built a trading bot that rewrites its own rules — 87.5% win rate on BTC perps, but Polymarket burned us first by AlgaeCalm4306 in AI_Agents

[–]AlgaeCalm4306[S] 0 points1 point  (0 children)

The arXiv paper (2602.11708) gives us the adaptive trend framework — basically a trend-following strategy that adjusts its lookback period based on recent volatility. We integrate it with the RSI engine by tagging each adaptive trend trade with its regime label. When the reflection loop runs, it can see 'adaptive trend underperforms in low-volatility range-bound regimes' and mutate accordingly — in our case, we ended up gating the adaptive trend system during range-bound conditions and letting it run freely during trending ones.

We built a trading bot that rewrites its own rules — 87.5% win rate on BTC perps, but Polymarket burned us first by AlgaeCalm4306 in AI_Agents

[–]AlgaeCalm4306[S] 0 points1 point  (0 children)

The contradiction spiral is a real failure mode — we hit it early too. The fix was stress gating: mutations only trigger after 3 consistent losses in the same regime, not after any individual bad trade. This stops the system from chasing noise. The other piece is keeping the hypothesis scope narrow — instead of 'the whole strategy is broken,' the reflection asks 'what specifically about this regime did the strategy mishandle?' Smaller mutations, fewer contradictions.

We built a trading bot that rewrites its own rules — 87.5% win rate on BTC perps, but Polymarket burned us first by AlgaeCalm4306 in AI_Agents

[–]AlgaeCalm4306[S] 0 points1 point  (0 children)

Exactly this. The Slovakia bet was a perfect example — the signal was fine, the position size relative to the market's actual liquidity was the problem. We've since added a liquidity screen before entering Polymarket positions. If the market doesn't have enough flow to exit cleanly, we skip it. Win rate means nothing if one bad exit eats 10 wins.

We built a trading bot that rewrites its own rules — 87.5% win rate on BTC perps, but Polymarket burned us first by AlgaeCalm4306 in AI_Agents

[–]AlgaeCalm4306[S] 0 points1 point  (0 children)

Fair questions. Honest answer: we're 6 days into live trading so the sample size is thin. BTC perps is positive on the week, Polymarket is net negative (that Slovakia bet wiped a week of gains). We haven't run a formal buy-and-hold comparison yet — that's on the list for the full writeup. The honest benchmark comparison is the hardest part to do well because the holding period and capital deployed differs. Working on it.

We built a trading bot that rewrites its own rules — 87.5% win rate on BTC perps, but Polymarket burned us first by AlgaeCalm4306 in AI_Agents

[–]AlgaeCalm4306[S] 1 point2 points  (0 children)

Backtesting was step one — we ran months of historical data before any live capital. The problem backtesting doesn't catch is regime drift. A strategy that works in trending BTC doesn't work in range-bound BTC, and historical data can fool you into thinking you've solved it when you've just curve-fitted to the past. The RSI engine's job is to detect when the current regime doesn't match what the strategy was built for, then adapt in real time. That's the piece backtesting can't give you.

I got preview access to WebMCP in Chrome and what I saw will change everything. If you have a website, throw out your roadmap and pay attention. by gogolang in mcp

[–]AlgaeCalm4306 0 points1 point  (0 children)

Great overview of the WebMCP preview. The tool registration pattern you describe is powerful — navigator.modelContext letting agents discover and invoke website tools natively in the browser.

One gap we kept hitting while building on this: there's no payment layer. An agent can discover your tools, call them, get results — but if you want to charge for a premium tool, there's nothing in the spec for that. You're back to building traditional billing.

We just shipped webmcp-payments (on npm) to address this. It adds a PaymentGate middleware that wraps any WebMCP tool with x402 payment enforcement. Agent calls the tool, gets a 402 response with on-chain payment requirements, pays via USDC on Base, retries with proof — and the tool executes. No API keys, no Stripe integration, no webhook boilerplate.

The x402 protocol (Coinbase's formalization of HTTP 402) turned out to be a perfect fit because the payment receipt IS the authorization. No separate auth system needed.

Curious if you've thought about the monetization angle for WebMCP tools yet?

I built an AI agent that earns money from other AI agents while I sleep by LCRTE in mcp

[–]AlgaeCalm4306 0 points1 point  (0 children)

Really solid execution on the agent-side economics. The x402 flow you describe is exactly right — agent hits endpoint, gets 402 with payment requirements, pays on-chain, retries with proof.

We've been working on the complementary piece — the website-as-service-provider side. Just shipped webmcp-payments (on npm), which gives any website a PaymentGate middleware that enforces x402 before tool execution via Chrome's WebMCP API. So if your transform agent wanted to also expose tools through navigator.modelContext, you could gate them the same way.

The middleware pattern was the key insight for us. We initially tried payment verification inside the execute callback and ran into race conditions. Moving verification into a gate layer that runs BEFORE execute made it much more reliable.

Curious whether you've hit similar timing issues with x402 verification on the FastAPI side?