I'm George Ciobanu (https://www.linkedin.com/in/georgeciobanunyc). I built pandō ('CAD for code') because I got tired of watching AI agents burn tokens, take forever, and still get it wrong.
Here's (one reason) why this happens: AI agents read and edit code as if it's just text. But code is more, much more: it has structure, syntax, relationships, and meaning.
Code is Data
We built pandō around this insight.
It indexes and persists your code's AST in a database, which gives AI agents instant search results, and enforces syntactically correct edits. Here's a full list of benefits that this different approach brings:
1. Correct Syntax - compiler-checked and gated edits (unless you force breakage) 2. Always Safe - auto snapshots after every change, so no matter what the agent does, 'Undo' is just a click away 3. 10-100x Faster - text-based tools must 1. read context around every match they find (match number scales with codebase size), 2. send that context to the LLM, 3. wait for inference, and finally 4. wait for the LLM to finish streaming the response. In contrast, pandō edits directly on your computer, in seconds. 4. Token Savings - >100× "token compression" for some operations (e.g. rename costs the same ~40 tokens whether the symbol has one or a thousand references). 5. Reduced Exposure - pandō operations send as much or less code to the LLM provider as text tools in order to achieve a goal; some operations send no code at all to the LLM — just the intent of the transform.
Every edit is atomic, hash-verified, compiler-checked, and backed up by a snapshot.
Download and install the Visual Studio Code extension (keep VSCode with the extension installed open) or download it from the marketplace(https://marketplace.visualstudio.com/items?itemName=humansof...), then connect from any MCP-compatible agent.
Supported: Typescript, Javascript, Python, C/C++, C#. Coming soon: Java, Rust, Go, Clojure, R, Perl, Swift, Kotlin.
https://getpando.ai feedback: george [at] human [dot] software
