Writing from the studio.
Practical notes on AI automation — what works in production, what doesn’t, and how we think about the decisions in between.
How to Add AI to an Existing SaaS Without Rewriting It
Most SaaS products don’t need a rebuild to get AI features. They need one well-chosen workflow, a clean API endpoint, and a prompt that doesn’t hallucinate on your data.
What an AI Automation Sprint Actually Looks Like
A fixed-scope, fixed-price, four-week engagement. Here’s what happens each week, what you get at the end, and what we won’t scope in.
LLM Routing: Why We Run Claude, Gemini, and OpenAI Behind One Gateway
Hard-coding a single model provider into your app is a liability. Here’s how we route across models — and the rules we use to decide which one runs what task.
The AI Features That Actually Show Up in Your P&L
Most AI features don’t move the needle. A few do — reliably and measurably. Here’s how to tell the difference before you build.
Webhook vs Polling for AI Integrations: When Each Makes Sense
Both patterns work. The right choice depends on latency requirements, whether the data source emits events, and how much you want to think about retry logic at 3am.