u/Obvious_Gap_5768

repowise - open source codebase intelligence for AI coding agents (and humans too)

Built this because every time I used Claude Code on a large codebase, it would just read files one by one. No idea which files change together, who owns what, why things were built a certain way, or what code is straight up dead.

repowise indexes your codebase into five layers: dependency graph (tree-sitter), git history analytics (hotspots, ownership, co-changes), auto-generated docs with RAG search, architectural decision tracking, and code health scores with 12 biomarkers.

All of it exposed through 9 MCP tools so your AI agent can actually understand your codebase instead of grepping through it blind. Also works standalone with a local dashboard if you just want the analytics without the AI stuff.

Some numbers from our benchmark on Flask: 36% cheaper, 49% fewer tool calls, 89% fewer file reads. Same answer quality.

Multi-repo workspaces, auto-sync on every commit, works fully offline with Ollama. AGPL-3.0.

pip install repowise

GitHub: https://github.com/repowise-dev/repowise

Happy to answer any questions.

u/Obvious_Gap_5768 — 1 day ago

Just quit my 1 Cr job to go full time on my own startups. Anxiety is through the roof

I'm a Sr Staff Data Scientist at a large MNC in Bengaluru. Great CTC, a manager I genuinely like, the kind of WLB that lets you have a life outside of work. By most metrics it was the kind of job people would be happy to coast in for a few years.

At the same time I had three things running on the side.

One is an open source dev tool for AI coding agents I launched a month back. It started getting enterprise inbound faster than I expected. NDA already signed with one major mnc, POC scheduled with another, couple more in conversations. No revenue yet but things feel good.

Second is an AI interview prep platform I co-founded with my partner about 8 months back. Around 25K users now, real monthly revenue, covers DSA, system design, AI/ML, the whole stack. Not enough to retire on but enough that I stopped calling it a side project a while back.

Third is a voice AI tutor we built at a hackathon last month. 500 signups in the first couple of days. Way too early to call but the early response felt different from other things we've launched. Don't have enough time to market this so parked it aside.

The other reason this felt necessary was that my head was already somewhere else. Work was fine, I was hitting deliverables, but my real focus was going into the side stuff. Felt fairer to both sides to just pick one.

I also kept telling myself I'd quit once the time was right. After 6 months of saying that I realised the time is never actually going to feel right.

Last week I just did it, my partner really stepped in and helped me decide here.

Now I'm in notice period and I can't sleep properly. The same traction that made the decision feel obvious is now making it scarier somehow. Now there's something real to lose. Telling my parents was harder than I thought. They didn't say anything bad, but I could see their doubts.

Friends who were telling me to just do it three months ago are now asking are you sur. Atleast my partner is supportive and thats all that matters.

I keep coming back to feeling like this was the right call, but the anxiety hasn't gone down even after putting in the papers. If anything it's worse now.

Posting this here mostly to put it somewhere outside my own head. Two months till I find out if past me was an idiot or a genius.

reddit.com
u/Obvious_Gap_5768 — 5 days ago

Just quit my 1 Cr job to go full time on my own startups. Anxiety is through the roof

I'm a Sr Staff Data Scientist at a large MNC in Bengaluru. Great CTC, a manager I genuinely like, the kind of WLB that lets you have a life outside of work. By most metrics on this sub it was the kind of job people would be happy to coast in for a few years.

At the same time I had three things running on the side.

One is an open source dev tool for AI coding agents I launched a month back. It started getting enterprise inbound faster than I expected. NDA already signed with one major mnc, POC scheduled with another, couple more in conversations. No revenue yet but things feel good.

Second is an AI interview prep platform I co-founded with my partner about 8 months back. Around 25K users now, real monthly revenue, covers DSA, system design, AI/ML, the whole stack. Not enough to retire on but enough that I stopped calling it a side project a while back.

Third is a voice AI tutor we built at a hackathon last month. 500 signups in the first couple of days. Way too early to call but the early response felt different from other things we've launched. Don't have enough time to market this so parked it aside.

The other reason this felt necessary was that my head was already somewhere else. Work was fine, I was hitting deliverables, but my real focus was going into the side stuff. Felt fairer to both sides to just pick one.

I also kept telling myself I'd quit once the time was right. After 6 months of saying that I realised the time is never actually going to feel right.

Last week I just did it, my partner really stepped in and helped me decide here.

Now I'm in notice period and I can't sleep properly. The same traction that made the decision feel obvious is now making it scarier somehow. Now there's something real to lose. Telling my parents was harder than I thought. They didn't say anything bad, but I could see their doubts.

Friends who were telling me to just do it three months ago are now asking are you sur. Atleast my partner is supportive and thats all that matters.

I keep coming back to feeling like this was the right call, but the anxiety hasn't gone down even after putting in the papers. If anything it's worse now.

Posting this here mostly to put it somewhere outside my own head. Two months till I find out if past me was an idiot or a genius.

reddit.com
u/Obvious_Gap_5768 — 5 days ago
▲ 153 r/indiehackersindia+3 crossposts

How I cut Claude Code token usage in half (open source, benchmark included)

Been working on Repowise for a few months now. The core idea: AI coding agents are only as good as the context they get. Most of the time, that context is terrible.

Cursor reads your files. It doesn't know your architecture. It doesn't know which files break the most. It doesn't know why you made that weird design decision in auth six months ago.

So I built a layer that sits between the codebase and the agent.

Four things it does:

  1. Parses your AST into a dependency graph (NetworkX). Agents can reason about structure.

  2. Mines git history into hotspot and ownership maps. Who wrote what, what breaks most.

  3. Generates an LLM wiki of your codebase and stores it in a vector DB. Always in sync.

  4. Captures architectural decisions as ADRs so agents have intent context, not just code.

Exposes 8 MCP tools. Works with any MCP-compatible agent. Also has a local web UI to explore the graph and docs yourself.

AGPL + commercial dual license. Self-hostable.

Got a few hundred GitHub stars pretty fast. Then someone cloned it on PyPI three times in a week violating the license, had to file a DMCA. Wild week.

Happy to answer questions on the technical side or the distribution side. Both have been interesting.

Repo: https://github.com/repowise-dev/repowise

Dogfooding on website: https://repowise.dev

A star would really help with visibility!

u/Obvious_Gap_5768 — 14 hours ago

Anyone else miss writing code before agents took over?

Building two products full-time. Most of my day is babysitting Claude and Cursor. Prompt, wait, review diff, accept, prompt again. 10 hours of this.

Shipping more code than ever but still feel like I built nothing.

Used to love opening the editor at night, headphones on, disappearing into a problem for 4 hours straight. That flow state where you forget dinner is gone now

Opened code I wrote by hand 6 months back. Remembered every weird decision, every tradeoff. Pulled up something Ckaude shipped last month. Reads like a stranger wrote it.

Yes I can still write everything by hand. Then I ship 1 feature while the next founder ships 5. Cannot afford that as a solo guy competing for users.

I am not saying AI is bad. It is brilliant for boilerplate, refactors, migrations. But the part I actually loved is gone. Debugging a weird race condition for 3 hours until one print statement cracks it open. Writing a clean solution from scratch. Actually building something with my hands.

Anyone else feeling this?

reddit.com
u/Obvious_Gap_5768 — 9 days ago
▲ 190 r/Python

Three packages copy-pasted my AGPL code to PyPI and named me in their description. PyPI won't act

I published repowise on PyPI a few weeks ago. It generates and maintains a wiki for your codebase, plus some git intelligence stuff like hotspots and ownership among other things

Soon after launch, three packages appeared on PyPI within hours of each other, all with the same description:

"Codebase intelligence that thinks ahead, outperforms repowise on every dimension."

Repowise is mine. They literally name it.

Looked inside the packages. They forked my AGPL-3.0 code, ran an LLM over it to fix a few small things, and republished under new names. No attribution, no license file, no source link.

Filed PyPI abuse reports. Filed a DMCA for the license violation. Sent email. Weeks in, all three packages are still live, still pulling downloads off my project's name.

PyPI's abuse flow seems to be a single form and silence. There's no copyleft enforcement path baked into the registry itself, so AGPL violations basically depend on DMCA, which is slow and easy to ignore.

Any suggestions would be very helpful

reddit.com
u/Obvious_Gap_5768 — 10 days ago
▲ 1.5k r/NewKeralaRevolution+1 crossposts

I work in AI daily. Staff Data Scientist, building multi-agent systems at enterprise scale, published at research venues. I also build products on the side. So I sit at an interesting intersection of "AI is my job" and "AI is eating my job."

Here's what I actually think plays out.

The junior dev pipeline dies first. Not junior devs. The pipeline. The "write CRUD, fix bugs, level up over 3 years" path is gone. Companies will hire fewer L1s and expect them to move faster. The entry bar got harder, not easier.

The middle gets squeezed. Engineers who are "good at implementing specs" are in trouble. That's a Claude/Cursor job now. Engineers who understand systems, make architectural calls, and can review AI output critically? More valuable than ever.

The top 10% gets a 10x multiplier. One good engineer with strong AI tooling is doing what used to take a small team. Companies will figure this out slowly, then all at once.

The Indian market specifically runs heavily on service contracts and staff augmentation. That model was already getting squeezed on margins. AI just compresses the timeline further.

The devs who thrive will be the ones who stopped thinking of themselves as coders and started thinking of themselves as builders.

Curious to hear about other people's take

reddit.com
u/Obvious_Gap_5768 — 17 days ago

TL;DR: The divide isn't AI replaces you vs. doesn't. It's people who use AI to think vs. people who use AI to avoid thinking. College is the best time to be in the first group. Build something real, go deep on one tool, learn to navigate codebases. The field is moving fast enough that a sharp fresher can outpace a complacent senior right now. That window won't stay open forever.

Let me start by saying: your anxiety is not irrational. The ground is actually shifting. I'm not going to give you the "AI is just a tool lol relax" cope.

Quick context so you know where this is coming from: 7 years in tech, senior staff level, currently leading AI initiatives at a large org. On the side I've been building and shipping things seriously: open source projects with real community traction, products with 20k+ users. I've been on the other side of GenAI hiring loops recently, so I see both ends of this, what gets built and what gets through.

Here's what I actually see.

The divide forming is not what you think

Everyone frames it as: will AI replace developers?

Wrong question.

The divide I see, in hiring, in who's getting traction, is between people who use AI to think and people who use AI to avoid thinking.

The second group is genuinely in trouble. I interview them. They can use Cursor, they can get something running, but ask them why they made an architectural choice or what happens when it breaks at scale: nothing. The AI wrote it and they don't know what it wrote.

The first group? They're shipping things I couldn't have shipped in the same time a few years ago. And a lot of them are not from pedigreed backgrounds.

What nobody tells you about enterprise AI

Most enterprise AI is a mess. Half the projects are LLM wrappers with no evals, no fallbacks, and someone's job title changed to "AI lead." People who can design agentic systems that are reliable, not just demo-able, are genuinely rare.

You don't need 5 years to understand this space better than most people in it. It's so new that a sharp 3rd-year who's been building seriously for a year can have better mental models than a 10-year veteran who started "exploring AI" last quarter.

That window won't stay open forever. But it's open right now.

The DSA question (honest answer)

Don't quit. But recalibrate why you're doing it.

The real value of DSA was never array rotations. It's learning to decompose problems and reason about tradeoffs. That's more useful than ever when you're debugging an agentic pipeline hallucinating in production.

The value of DSA as a placement filter is under pressure. Some companies are changing loops. But many haven't, and you need to clear placements to buy yourself options. Do the grind, clear the filter, just don't confuse clearing the filter with actually being good.

What I'd do if I were in college right now

  1. Build something real before you graduate. Not a tutorial project. Something with users who aren't your friends. Even 10 strangers using your thing will teach you more than any course. With AI, a weekend is enough to have a rough but real product.

  2. Go deep on one AI tool, not shallow on all of them. Listing 8 AI tools on a resume impresses nobody. Pick one and understand it well enough to explain its failure modes.

  3. Learn to navigate a codebase, not just write one. AI writes code fast. The scarce skill is understanding why a codebase is shaped the way it is and knowing where to change things without breaking stuff. This is what separates a vibe-coder from someone a team actually wants.

  4. Full-stack + LLM API calls is criminally underrated. If you can build a clean backend/frontend AND wire in a real LLM workflow, not just chat_completion but actual tool use, memory, fallbacks, you're genuinely useful at most AI startups right now. Most people don't have this. It's not a high bar.

  5. Contribute to open source AI tooling. Agent frameworks, eval libraries, dev tools. People hiring in this space notice GitHub. More importantly, you'll be building alongside people who actually know what they're doing.

The uncomfortable thing

A lot of senior engineers, people at my level and above, are also scared and figuring this out in real time. "What's the right architecture for agentic systems in production?" Honest answer: we're still working it out

You're not as far behind as you think. The gap between a curious, building fresher and a complacent senior is closing faster than at any point I've seen. That's both a threat and an insane opportunity, depending on which one you decide to be.

Build something. Ship it. Let it fail. Repeat.

Good luck.

reddit.com
u/Obvious_Gap_5768 — 19 days ago

Reading code and understanding code are different things.

Claude Code is good at reading. Open auth.ts, describe what the functions do, trace the call chain.

But it doesn't know that auth.ts was rewritten three months ago because the original approach broke under k8s horizontal scaling. It doesn't know that payments.ts changes alongside it in 80% of commits despite having no import link. It doesn't know the engineer who owned 70% of it left in January.

That context lives in your git history, your commit messages, your past decisions.

Claude Code starts every session without any of it.

I built Repowise to fix this. It pre-computes what Claude Code needs to actually understand a codebase and exposes it through MCP tools.

Four layers: dependency graph from AST parsing, git signals (hotspots, ownership per engineer, files that change together without being imported by each other), an auto-generated wiki with semantic search, and a decisions layer that mines commit history for the "why" behind how code is structured.

The shift is from "here is what auth.ts contains" to "here is why it works this way,

who owns it, what breaks if you touch it, and whether anyone has already made a call about this."

Ran a benchmark. 48 SWE-QA tasks on pallets/flask, claude-sonnet-4-6, two conditions:

bare Claude Code vs repowise. Same model, same prompt, same judge.

On 48 benchmark tasks: 36% cheaper, 49% fewer tool calls, 89% fewer files read.

All results and harness code are public if you want to reproduce it.

Some other stuff it does that I haven't seen elsewhere in open source:

\- Dead code detection via graph traversal, no LLM calls, under 10 seconds on any repo size

\- CLAUDE.md auto-generated from actual graph data, not a template. Hotspot warnings,

ownership map, files that silently change together, past decisions.

\- Decision records linked to the code they cover, with staleness tracking as that code changes over time

\- Multi-repo support

\- Local dashboard with dependency graph, doc freshness, bus factor view

\`pip install repowise\` then \`repowise init\`.

First index is \~20 min on a 3k-file project, every commit update after that is under 30 seconds. Works with Claude Code, Cursor, Codex.

AGPL-3.0, nothing leaves your machine.

GitHub: https://github.com/repowise-dev/repowise

Benchmark: github.com/repowise-dev/repowise-bench

A github star would be incredibly valuable!

Happy to answer any questions.

u/Obvious_Gap_5768 — 22 days ago