The Problem Worth Solving
Most people using AI with Coda get mediocre results — not because the AI is bad, but because it has no context. It doesn’t know your table conventions, your formula patterns, or why you should never use a Select List where a relational table belongs.
Skill files solve this. They carry the accumulated judgement of someone who has made the mistakes, documented the lessons, and knows which Coda decisions survive contact with a real workspace.
What Coda Curious Is
Coda Curious is where Coda expertise becomes teachable. Not tutorials. Not tips. A structured method for encoding what an expert knows into files an AI can follow — so that any maker, at any coding level, can steer an AI to build, maintain, and improve a Coda doc with confidence.
Skill files: Plain-language instruction sets that give AI the architectural rules, formula patterns, and naming conventions of a seasoned Coda expert. Core Coda competences: Each skill file maps to a real capability — formulas, data architecture, page structure, column design, automations — turning expertise into context an AI can act on. AI-ready by design: Whether you use Antigravity, Claude, or another AI assistant, the skill file is the bridge between your intent and a result that holds up. What You Can Learn Here
🗂 Data architecture: How to model relational tables that stay clean as a workspace grows — and how to encode those decisions into a file an AI can follow. ✍️ Formula logic: The patterns behind thisRow, Filter(), Format(), and the formulas beginners fear. Not memorised — understood, then written into skill files. 📐 Page & UI standards: Naming conventions, callout structure, column lifecycle rules. The decisions that make a Coda doc legible to someone who didn’t build it. ⚙️ Automations & buttons: How to design actions that are self-documenting and safe to hand off. 🧠 Steering AI agents: How to write skill files that work — what to include, what to leave out, and how to verify the AI is actually following them. How the Blogs Feed the Files
Each blog post is a working record of a problem encountered, a pattern tested, and a conclusion reached. Some are conceptual. Some are deeply practical. Some turned out to be wrong and were corrected in later posts — those corrections are noted.
The blogs feed the skill files. The skill files feed better AI outputs. The goal is a loop that keeps improving — and that any maker can enter at any point.
The full archive is on the Blogs page. Use the search to find what you need.