Another late night. Building a quant trading system an agentic model where different AI agents handle research, testing and risk, and none of them is allowed to place a trade on its own.

The hardest part so far? Being honest when the results say "not yet." Most strategies I've tested failed once real costs were included. That's exactly what testing is for.

Keeping The Psychology of Money and The Diary of a CEO close while I figure it out. What are you reading these days?

#QuantTrading #AlgoTrading #BuildInPublic

Curious how you’ve separated the agents from execution. When you say none can place a trade on its own, is that enforced through a separate execution service with fixed risk checks, human approval or both? I’d love to understand where the agent's decision-making ends and the hard rules take over.

BEFORE: Client had messy Excel inventory with 500 rows, duplicates (A12 / a12), blanks, wrong prices like "$ 2.5" and "N/A", and different warehouse names (KER / ker / Kericho).

AFTER: I did:

Removed 12 duplicate SKUs

Standardized item names to Title Case

Fixed QTY and Prices to 2 decimals

Unified Warehouse to Kericho

Made sheet ready for pivot dashboard

Result: Clean, ready-to-use inventory in 2 days using Excel.

Tools: Excel, Remove Duplicates, Text to Columns, TRIM, PROPER