Building production-ready fault tolerance for AI

> What I Built

Screen Recording 2025-06-01 at 9.31.31 AM.mov

https://github.com/ShaliniAnandaPhD/NueralCircuit

The Problem I Solved You know what really bothers me? AI systems fail at the worst possible moments. Imagine you're deep in flow state, completely focused, and your AI focus optimization tool crashes. That's not just an inconvenience - it's cognitive disruption that can ruin your entire session.

So I built NeuroCircuit: a six-agent system that doesn't just detect failures - it heals itself before you even notice something went wrong.

My Solution in One Sentence Six specialized AI agents working together to provide bulletproof focus optimization that self-heals in under 30 seconds, based on Steven Kotler's flow science.

>> The Architecture I Designed

I went with a neural circuit approach because I wanted something that felt natural - like how your brain coordinates different regions for complex tasks.

My Six-Agent Team

🧠 CognitiveDetector → Analyzes your flow state
🚀 NeuralBus → Routes messages between agents
💾 MemoryController → Remembers your patterns
⚡ DecisionEngine → Makes optimization decisions
🔄 AdaptationController → Adapts to your style
🎯 CoordinationHub → Orchestrates everything

Why I Chose This Design

• Each agent has one job and does it extremely well
• They all talk to each other constantly (real coordination, not fake prompt passing)
• If one fails, the others immediately step in to help
• The whole system learns your personal flow patterns over time