Insights & Field Notes
AI Systems Journal
Technical Blog
Deep dives on LLM integration, agentic AI systems, microservices, and semantic search.
Where Do LLMs Learn From? Understanding Training Data Sources
Explore the four primary sources of LLM training data: web crawling, professional databases, synthetic data, and commercial licensing. Learn how Common Crawl data is filtered, cleaned, and packaged for training modern language models.
Mistral OCR 3: Enhance Document Accuracy and Efficiency
Mistral OCR 3 delivers breakthrough document extraction with state-of-the-art accuracy across invoices, forms, and complex tables. Learn how to leverage high-fidelity extraction, HTML table reconstruction, and industry-leading pricing ($1-2 per 1,000 pages) to transform your document AI pipelines.
The Gartner AI Maturity Model: A Strategic Roadmap for Enterprise AI Adoption
Navigate your organization's AI journey from awareness to transformation. Explore Gartner's five-level maturity framework, seven assessment pillars, and practical strategies to build capabilities and accelerate AI-driven competitive advantage.
Why your next product should be a Chat-Web Application
Traditional dashboards are giving way to conversational workflows. Design Chat-Web Apps with LangGraph, LLMs, and automation stacks that let users ask, act, and automate in one place.
How to integrate LLMs into enterprise microservices
A pragmatic guide to adding GPT/Claude-powered capabilities to existing services with patterns for security, latency, and cost.
Agentic AI systems architecture with LangGraph
Designing multi-agent workflows for orchestration, routing, and reliable tool use across enterprise contexts.
Vector databases for semantic search: patterns and pitfalls
Choosing Pinecone/FAISS/Chroma, chunking strategies, metadata filters, and evaluation for production search.