getting started
Introduction
Developers use AI constantly now, but the work is scattered — one tool for one model, another tab for a different one, a new chat every time you switch, and none of them remember what you were doing five minutes ago. Every switch means re-explaining the project from scratch.
MockingBird exists to close that gap. It's a workspace layer that sits above the individual models — Claude, GPT, Gemini, DeepSeek — and carries your project underneath all of them, so switching models doesn't mean losing your place.
Three things, working together
- Multi-provider access
Use whichever model fits the task — one for coding, one for reasoning through a decision, one for cost-efficient routine work — from the same workspace, same conversation. - Persistent workspace memory
MockingBird remembers your project across sessions — decisions already made, conventions you follow, what you're actively working on — so you're not rebuilding context every time you open it. - Persistent identity context
It also remembers how you work — preferences, patterns, the things you'd otherwise repeat in every new chat — and carries that forward too.
Model access alone is already commoditized — every provider is one API call away. What actually compounds over time is whether the tool remembers your project and keeps working with you inside it. That's the layer MockingBird is built on.