The Missing Piece in AI Coding: Automated Context Discovery

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2024-12-12 19:30:04

I recently switched tasks from writing the ColBERT Live! library and related benchmarking tools to authoring BM25 search for Cassandra. I was able to implement the former almost entirely with "coding in English" via Aider. That is: I gave the LLM tasks, in English, and it generated diffs for me that Aider applied to my source files. This made me easily 5x more productive vs writing code by hand, even with AI autocomplete like Copilot. It felt amazing!

Coming back to Cassandra, by contrast, felt like swimming through molasses. Doing everything by hand is tedious when you know that an LLM could do it faster if you could just structure the problem correctly for it. It felt like writing assembly without a compiler -- a useful skill in narrow situations, but mostly not a good use of human intelligence today.

The key difference in these two scenarios is that ColBERT Live! is a dozen source files with simple relationships. Cassandra is thousands of files, poorly modularized, with call stacks dozens deep.

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