Building Production RAG: Hybrid Vector Search & Reranking Architecture
A deep dive into sub-400ms Retrieval-Augmented Generation using Qdrant vector database, BM25 sparse keyword search, and cross-encoder reranking.
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Technical thoughts and resources.
Our engineering team writes about Model Context Protocol, RAG architectures, prompt design, and lessons learned building AI-native software.
LangGraph vs. AutoGen for Enterprise AI Agents in Production
A technical evaluation comparing LangGraph state machines and Microsoft AutoGen for multi-agent workflows, tool execution, and enterprise security.
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How AI Agents Actually Work in Production
AI agents are the most hyped concept in AI right now. Here's what they actually are, how they work in real business systems, and what separates a demo from production.
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RAG vs. Fine-Tuning: When to Use Each for Your AI Project
Two of the most common approaches to making AI work with your data — but they solve very different problems. Here's how to choose the right one.
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Build vs. Buy: An AI Strategy Framework for SMBs
A practical framework for deciding when to build custom AI solutions vs. buying off-the-shelf tools. Designed for SMBs and mid-market companies evaluating their AI options.
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What is AI-Native Software? (And Why It Matters)
AI-native isn't a marketing buzzword — it's a fundamentally different way to design software. Here's what it means, why it matters, and how to tell the difference.
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What is MCP and Why Your Business Should Care
The Model Context Protocol is changing how AI models interact with business tools. Here's what it means for non-technical decision makers and engineering teams alike.
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