Prashant Kumar@prashant08062arch632

Most AI trading systems lack hard risk controls, learning loops, and transparent rejection reasoning. The Alpaca Trading Committee separates AI analysis from deterministic risk: four LLM analysts feed a debate agent that creates one trade proposal, while an eight-rule Risk Governor independently approves or rejects it before Alpaca execution. Every rejection is stored and evaluated counterfactually; every executed trade is fully journaled. These feedback loops reveal patterns, improve future decisions, and make the system auditable. The Risk Governor enforces confidence, return, drawdown, position, sector, total exposure, direction, and position-cap limits without AI override.

🌎 Online Hackathon | 💻 Month-long challenge | Dates: Sep 1–30, 2026 | 🏆 $10,000 Prize Pool ($5k cash + $5k in AAI credits) A month-long online challenge run by lablab.ai together with AssemblyAI, the Voice AI infrastructure company for builders. Every participant builds on AssemblyAI. You can join at any point — registration stays open for the whole build window, so you can start on day one or pick the project up halfway through and still submit. 🌍 Fully online hackathon. Join and build from anywhere in the world.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.