Production AI and growth engineering insights
Practical, engineering-led guides to RAG, voice AI, automation, AI acquisition and answer-engine visibility.
Articles
- How a private RAG concierge cut a FinTech's support cost 47% () — A step-by-step breakdown of the retrieval architecture, model routing, and guardrails that turned a drowning L1 support queue into a 92% first-contact-resolution engine — in eight weeks.
- The AI acquisition playbook: cold traffic to booked demo in 9 steps () — The exact funnel architecture we deploy for AI-native companies — intent capture, qualification, and an autonomous follow-up loop that turns anonymous clicks into qualified pipeline.
- RAG vs fine-tuning vs long-context: how to choose in 2026 () — A decision framework for the three ways to give an LLM your knowledge — when retrieval wins, when fine-tuning is worth it, when a long context window is enough, and how to combine them.
- AEO in 2026: how to get cited by ChatGPT, Perplexity & AI Overviews () — Answer Engine Optimization is the new SEO. Here is how to structure content, schema, and entities so large language models surface and cite your brand in their answers.
- Shipping sub-600ms voice AI: a production latency architecture () — Why "fast" voice agents still feel broken, and the streaming, native-multimodal architecture we use to hold end-to-end conversation latency under 600 milliseconds.
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