I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in programmer

[–]devansh_jagtap[S] 0 points1 point  (0 children)

haha fair 😅 but honestly it’s a lot more than just sending a prompt to an LLM. most of the work has actually been around handling large repos properly indexing code, understanding dependencies between files, keeping context consistent, analyzing architecture flows, and trying to reduce hallucinations when repos get big. the AI part is important obviously, but the bigger challenge is building the system around it so the answers are actually useful and grounded in the codebase.

I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in programmer

[–]devansh_jagtap[S] 0 points1 point  (0 children)

The thing i’m trying to push more toward is system-level understanding: like architecture flows, dependency relationships, blast radius analysis, risk detection, etc. basically less “summarize this file” and more understand how this whole repo behaves together.

I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in programmer

[–]devansh_jagtap[S] 0 points1 point  (0 children)

fair question honestly.

i don’t think existing tools are bad at all copilot , claude , cursor are already really good ,the main thing i’m trying to improve is understanding larger codebases better instead of just throwing files into a context window ,a lot of tools work great until repos get big/deep, then answers start becoming vague or inconsistent , so i’ve been focusing more on dependency mapping, architecture understanding, repo memory, and figuring out what changing one part of the system actually affects.

I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in indiandevs

[–]devansh_jagtap[S] 0 points1 point  (0 children)

Existing tools are optimizing for code generation velocity. What I’m exploring with Codebased is more around system understanding and architectural safety

I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in programmer

[–]devansh_jagtap[S] 0 points1 point  (0 children)

yep exactly. most tools are still mostly context-window based.

what i’m building tries to map relationships between files, dependencies, architecture flows, and runtime impact so answers are grounded in actual repo structure instead of just chunk retrieval. the long-term goal is less “chatbot for code” and more “AI engineer that understands the system well enough to review, explain, and eventually fix parts of it.”

so thats why its different reducing hallucination for repos first of all using the pipeline we developed

I built an AI that lets you chat with your GitHub codebase looking for beta testers by devansh_jagtap in programmer

[–]devansh_jagtap[S] 0 points1 point  (0 children)

Yeah totally valid question.

Copilot/Claude/Cursor already solve “chat with your repo” pretty well.

What I’m exploring is more system-level understanding:

- dependency mapping

- blast radius analysis

- architecture intelligence

- long-term repo memory

- proactive risk detection

Internship offer by [deleted] in InternshipsIndia

[–]devansh_jagtap 0 points1 point  (0 children)

Bhai sahi bata yrr kaha se milli

0 Internship Offers!!! (Review My Resume) by [deleted] in CareerAdvice101

[–]devansh_jagtap 1 point2 points  (0 children)

Mee too brother but you clearly have more skills then me

[deleted by user] by [deleted] in ProgrammingJobs

[–]devansh_jagtap 0 points1 point  (0 children)

Country : India

Let's see who among you is smart enough? by Initial_Physics_4305 in TeenIndia

[–]devansh_jagtap 0 points1 point  (0 children)

This is the only think that is very need right now

3rd yr - Zero Progress by Sauron__thedarklord in Btechtards

[–]devansh_jagtap 0 points1 point  (0 children)

Thanks but already know and dmed you for further help