Notes from building AI in production.

The real cost of an AI agent is three costs: building it, running it and improving it. Here's what drives each one, how to estimate the return and how to keep spend under control.

Rule-based automation and AI agents solve different problems. A plain-English guide to when Zapier, Make or n8n is enough, when you need an agent, and how the two work best together.

Retrieval-augmented generation lets AI answer from your policies, manuals and data instead of the internet. What it is, where it pays off and what separates a good system from a bad one.

MCP is an open standard for connecting AI to your tools and data. What it is, why it matters for your systems and what to ask before you plug AI into them.

You don't need an AI strategy deck to get value from AI. Seven practical starting points for small and growing businesses, and how to pick the right first one.

We built Open Vernacular AI Kit as a production-first normalization layer for Indian language AI systems. It standardizes code-mixed, multi-script input before retrieval, routing and LLM calls.

We're open sourcing SwiftCache, an enterprise-grade image caching library battle-tested in production apps with millions of users. Zero dependencies, Swift 6 ready, 150KB footprint.