QUADRA – The Strategic Co-Pilot for Product Teams

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  Quadra Architecture

🧭 What Inspired This Project? I’ve always believed the most powerful decisions in a product team are made not from dashboards — but from patterns. When Google announced the Agent Development Kit, I saw an opportunity: Could I simulate the thinking structure of a full-stack product team — one that reads behavior, listens to users, and aligns everything into a clear plan?

That’s where QUADRA was born.

Not as another data tool. But as a strategic co-pilot — something that doesn’t just automate tasks, but guides product direction.

🛠️ How I Built It QUADRA is made of four intelligent agents, each playing a role you’d expect in a real product team:

Insight Agent — Ingests raw user logs (2GB .tsv) and analyzes behavior across calories, macros, and goal tracking. It flags churn risk using patterns of inconsistency, overeating, and drop-off.

Growth Agent — Reads those summaries and suggests nudges: portion guidance, streak-based rewards, and goal reframing — tailored to user segments.

Voice Agent — Ingests 50+ user reviews and categorizes pain points across UX, motivation, performance, and pricing using prompt-based text classification.

Strategy Agent — Consolidates all insights into a markdown report: what’s happening, why it matters, and what the product team should do.

All agents are modular and orchestrated through a central controller.py. The system runs end-to-end in Colab, powered by Python and Google Drive as a cloud storage layer.

💡 What I Learned That multi-agent design isn’t just for research — it’s practical, composable, and surprisingly intuitive once you break the problem down by function.

That strategy can be architected — not guessed.

And that when you focus on clarity and modularity, even a solo developer can build something that feels like a team built it.

🧱 Challenges I Faced Handling a 2GB+ semi-structured .tsv dataset in a memory-efficient way using chunked processing in Colab.

Designing each agent to work independently but still contribute meaningfully to a unified strategy output.

Ensuring that the user reviews felt human, the churn analysis felt real, and the system felt coherent — not stitched together.

🧭 What QUADRA Represents QUADRA isn’t just a submission. It’s a statement about what AI can do inside a product team — when built with intention, clarity, and context.

This is version 1. There’s so much more ahead.

Built With

• adk
• gcp
• google-drive
• json
• kagle
• panda
• python
• regex
• regexlib
• youtube