Field Notes

Field Notes

Notes from building AI systems in production - covering ML, software engineering, and lessons from the field. New topics added regularly.

Enterprise AI

Deploying AI at scale in Fortune 100 environments.

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AI Agents at Scale
Deploying autonomous AI agents in enterprise environments - orchestration, trust, and governance.

LLMs & NLP

Large language models, natural language processing, and text understanding.

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RAG Pipelines
Retrieval-Augmented Generation - how to ground LLMs in your enterprise data.
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Transformers
The architecture behind modern LLMs - self-attention, encoder-decoder, and why it changed everything.

ML Engineering

Building, training, and optimizing machine learning systems.

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Linear and Logistic Regression
The two models every ML engineer reaches for first - one predicts numbers, the other predicts categories.

Software Engineering

System design, architecture, and engineering fundamentals.

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System Design Basics
Foundational concepts for designing scalable, reliable distributed systems.

More topics coming soon. New field notes added daily.