Essays · Operations Intelligence, AI and Quant
Hossein Narimani — Writing
In-depth writing on quant system design, operational AI, SaaS architecture, custom AI agents and founder execution systems.
Why Generative AI Agents Fail in Real Operational Systems: Architecture, Latency, and Cost Constraints
Most AI Agent projects work well in the demo stage. The problems start when you move them into a real system. Latency climbs. Costs spiral out of control. And the synchronous architecture that looked elegant in a notebook buckles under real production...
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Hybrid Quant System Architecture: Integrating Risk Management, Position Sizing, and Execution in a Unified Framework
Most quant systems that fail in production don't have a signal problem. They have an architecture problem. Their signals work. Their backtests are...
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Building Custom AI Agents with Memory Persistence and State Management for Production Decision Systems
Most AI agents that work in demos fail in production. Not because the model is wrong. Because they have no memory and no state. An agent that...
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How AI Crypto Signals Can Reduce Losses in Sideways Markets
Most trading losses do not occur during market crashes. A significant portion emerges when markets refuse to choose a direction. Price moves....
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How AI Signals Detect Crypto Pump-and-Dump Traps: A Practical Guide for Traders
Most traders assume they become victims of crypto pump-and-dump schemes because their technical analysis is weak. The reality is different. The...
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