Insights

How we think, in writing.

Technical notes on building GenAI systems that survive production. Written for the engineers who build them and the leaders who commission them.

Architecture RAG architecture for enterprise: what actually works in production 14 min Most RAG implementations look fine in demos and fall apart in week two. The architecture decision that changes that. Architecture Document intelligence: the architecture behind processing 10,000 contracts a month 15 min PDFs, scanned invoices, legacy formats — the full stack for extracting structured data from whatever documents arrive. Architecture Fine-tuning vs RAG vs prompting: a decision tree for enterprise teams 15 min The answer is almost always prompting first, RAG second, fine-tuning rarely — and the specific cases that break the rule. Architecture Vector databases for enterprise: Pinecone vs Weaviate vs pgvector 13 min What production deployments actually reveal about each option, beyond the comparison-post consensus. LLM stack GPT-5.5 vs Claude vs Gemini 3.1: a practical decision framework 12 min Benchmarks are useless for your use case. How to actually choose models for business automation. LLM stack Prompt engineering for business workflows (not chatbots) 12 min Prompts for internal automation are a different discipline from prompts for chat — higher stakes, subtler failure modes. Agents Agent orchestration patterns: when single-agent fails and multi-agent wins 16 min Single-agent is underrated and multi-agent is over-hyped. A decision framework from production patterns. Agents The human-in-the-loop pattern: where AI needs a checkpoint 11 min Full automation isn't always the goal. A practical framework for deciding where humans stay in the loop. Deployment The real cost of running LLMs in production 11 min Token costs compound fast at scale. Four changes that keep deployments from blowing the budget. Security LLM security in regulated industries 14 min Banking, healthcare, insurance — the compliance requirements are real, and standard deployment advice skips most of them.

These patterns are what we build.

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