u/recro69

I'm the solo founder of Kolabl. I handle product and tech. Kolabl is live and helps local businesses in Bengaluru work with Instagram creators, with real numbers pulled straight from Instagram instead of screenshots.

I'm building a 3-person core team and looking for two people:

1. Growth & Partnerships: bring local businesses and brands on board and get them running creator campaigns. Mostly in-person around Bengaluru.

2. Creator & Community: bring Bengaluru creators on board and run our Instagram.

How it works:

- Paid per result for a 3-week sprint (15 Oct to 8 Nov)

- Equity track with vesting after that, if it's a fit for both of us

- You work directly with me, and your ideas ship

You need to be Bengaluru-based and able to give 15+ hours a week.

Happy to answer questions in the comments.

The hard part of 2B reconciliation is not always the matching itself.

Sometimes the invoice is obviously the same. The invoice number is entered in a different way:

• 25-26/XYZ
• 2526/XYZ
• XYZ/25-26

There are also wrong accountant entries, GSTIN errors, missing GSTR-1 filings or invoices appearing in a different period.

Which mismatch requires the manual effort in your workflow?

A scheduled job runs each night. The same scrape, the report, the same queue worker. Every few days it hits the same external failure – say a 429 from the same API. What bothers me is that the agent treats each failure, like a brand problem. Each run starts with a context, so the agent rediscovers the fix, retries fails again and finally moves on. Then the next scheduled job wakes up. Repeats the same process.

This made me think about agent memory in a way. We usually think of memory as remembering decisions or user preferences. But recurring failures also need memory: this already happened, the cause of the failure and the solution that worked. Without that memory the automation does not learn from yesterday. It's just repeating yesterday's mistake. How are you handling this in production — do you store recurring tool failures somewhere that the next agent run can use, or do you rely mostly on logs?

I asked Claude for logic without exponential backoff. The commit message read: "Add logic (without exponential backoff)." Nobody asked for backoff. Claude tried backoff was corrected and that correction became part of project history. I have noticed things in comments, test names, filenames and PR descriptions. Things like "as discussed" or ", per your feedback."

The weird part is that the code is not necessarily wrong. Claude has not switched audiences. Claude is still talking to the person it was chatting with of the person who will read the code six months later with zero context. It feels like something checking whenever an AI coding agent creates anything that is supposed to stand on its own.

I have been experimenting with AI for turning Word documents into presentation decks and I have found that asking for the slides directly is not always the best approach.

What works better for me is breaking it into two steps:

1. First turn the document into a slide‑by‑slide outline.

2. Remove anything that does not really need to be a slide.

3. Then generate the presentation from the approved outline.

I also found that giving the AI some context, about the audience and presentation length makes a difference. A 5‑minute internal update should not have the structure as a 30‑minute client presentation.

I am curious how others are handling this. Do you generate the deck directly or do you prefer reviewing an outline first?

I have been trying to grow a X account about AI/tech lately. I started with the steps, like posting every day sticking to one niche and replying to people in the same field. I am putting out content. My reach and follower growth are still moving very slowly. This made me see that making content and getting people to see that content are two different problems.

For the people who work in media what actually helped you the most when your organic growth was stuck?

I start a X account that is all about AI agents and production AI.

I have been posting a lot. I try to answer other founders. I am trying to stay focused, on one thing of trying to do everything.

The problem is not making content now. The problem is getting people to look at it.

For those who have grown an account from scratch, was there a point where things started compounding, or was it simply months of consistency?

We thought that impressions would match up with leads. Replies proved to be a much better sign that a post would start a conversation.

Has anyone else found a measurement that works better, than the one everyone always talks about?

I'm a solo founder. I built the entire product myself — and that's exactly the problem.

The product is live in production and launching publicly this week. From here, the work splits into two full-time jobs: growth/partnerships on one side, and tech + operations on the other. Doing both alone means doing both badly, and the product deserves better than my split attention.

So I'm looking for a technical co-founder based in Bangalore who can fully own tech and operations — while I go all-in on growth.

What's real today (keeping the product itself for an in-person chat):

• Full product running in production — dashboard, public pages, automated data pipelines
• Integrations with two major platforms' official APIs, including an approval most startups get rejected on
• First users onboarding right now; public launch is days away
• Bootstrapped, pre-revenue by design — monetization path is mapped, not vapor

Stack: Python/FastAPI on Azure, Next.js/TypeScript on Vercel, Postgres (Supabase), scheduled data-ingestion jobs, CI/CD via GitHub Actions. Real codebase — tests, migrations, deploy pipeline. Not a no-code prototype.

You:

• Strong with Python + TypeScript/React, and comfortable owning production alone — deploys, debugging, third-party API quirks, infra
• Product judgment: you'll decide what we build with me, not take tickets
• In or around Bangalore — I want to do this face to face, not over endless calls

The deal: meaningful co-founder equity with standard vesting. Partnership, not a job — no salary yet, and I'd rather discuss equity openly over coffee than pretend there's a magic number in a Reddit post.

How this goes: DM me → we meet in Bangalore over coffee → I show you the live product, the codebase, and real numbers → you grill me on why this wins. Vetting goes both ways.

Comment or DM with one line about what you've built. Links > resumes.

[ Looking for Cofounder ]

I'm a solo founder. I built the entire product myself — and that's exactly the problem.

The product is live in production and launching publicly this week. From here, the work splits into two full-time jobs: growth/partnerships on one side, and tech + operations on the other. Doing both alone means doing both badly, and the product deserves better than my split attention.

So I'm looking for a technical co-founder based in Bangalore who can fully own tech and operations — while I go all-in on growth.

What's real today (keeping the product itself for an in-person chat):

• Full product running in production — dashboard, public pages, automated data pipelines
• Integrations with two major platforms' official APIs, including an approval most startups get rejected on
• First users onboarding right now; public launch is days away
• Bootstrapped, pre-revenue by design — monetization path is mapped, not vapor

Stack: Python/FastAPI on Azure, Next.js/TypeScript on Vercel, Postgres (Supabase), scheduled data-ingestion jobs, CI/CD via GitHub Actions. Real codebase — tests, migrations, deploy pipeline. Not a no-code prototype.

You:

• Strong with Python + TypeScript/React, and comfortable owning production alone — deploys, debugging, third-party API quirks, infra
• Product judgment: you'll decide what we build with me, not take tickets
• In or around Bangalore — I want to do this face to face, not over endless calls

The deal: meaningful co-founder equity with standard vesting. Partnership, not a job — no salary yet, and I'd rather discuss equity openly over coffee than pretend there's a magic number in a Reddit post.

How this goes: DM me → we meet in Bangalore over coffee → I show you the live product, the codebase, and real numbers → you grill me on why this wins. Vetting goes both ways.

Comment or DM with one line about what you've built. Links > resumes.

I'm a solo founder. I built the entire product myself — and that's exactly the problem.

The product is live in production and launching publicly this week. From here, the work splits into two full-time jobs: growth/partnerships on one side, and tech + operations on the other. Doing both alone means doing both badly, and the product deserves better than my split attention.

So I'm looking for a technical co-founder based in Bangalore who can fully own tech and operations — while I go all-in on growth.

What's real today (keeping the product itself for an in-person chat):

• Full product running in production — dashboard, public pages, automated data pipelines
• Integrations with two major platforms' official APIs, including an approval most startups get rejected on
• First users onboarding right now; public launch is days away
• Bootstrapped, pre-revenue by design — monetization path is mapped, not vapor

Stack: Python/FastAPI on Azure, Next.js/TypeScript on Vercel, Postgres (Supabase), scheduled data-ingestion jobs, CI/CD via GitHub Actions. Real codebase — tests, migrations, deploy pipeline. Not a no-code prototype.

You:

• Strong with Python + TypeScript/React, and comfortable owning production alone — deploys, debugging, third-party API quirks, infra
• Product judgment: you'll decide what we build with me, not take tickets
• In or around Bangalore — I want to do this face to face, not over endless calls

The deal: meaningful co-founder equity with standard vesting. Partnership, not a job — no salary yet, and I'd rather discuss equity openly over coffee than pretend there's a magic number in a Reddit post.

How this goes: DM me → we meet in Bangalore over coffee → I show you the live product, the codebase, and real numbers → you grill me on why this wins. Vetting goes both ways.

Comment or DM with one line about what you've built. Links > resumes.

Curious which models have actually stayed in your rotation.

Been watching a small group of micro creators start getting brand deals while bigger accounts get passed over. The difference isn't how followers they have. It's that they are ready for deals and the others aren't.

Wondering how many people here have seen the thing. What do you think really makes a brand choose a creator over a bigger one?

The FOMO tactics are doing the work in all of these: a limit ("5 only") a time frame ("closing this week") and a fear of missing out ("free now paid later"). Keep the number real. If you say 5 stop at 5. The scarcity won't work next time.

A warning about point three and point four: those subscribers take down posts that only have a link to an waitlist page. The link needs to go to something a person can actually use or a moderator removes it.

Want me to make an one-line "comment 'ME'. I'll DM you" version, for any of these? That style gets the replies.

Working with a group of micro creators to help them get ready for deals and get in front of brands. Opening 5 free founding spots this week then it will be closed.

Founding members stay free. Link is, in the comments. 5 Only.

Testing something with a small group of micro creators to get them deal-ready before brands come knocking. Early feedback's been strong, so I'm taking 5 more in free before it opens to everyone.

Founding testers stay free for good. Everyone after pays.

Link below — grab a spot before they're gone.

Spent the last few weeks helping a small group of micro creators get deal-ready and noticed brands starting to come to them instead of the other way around.

I'm taking 5 more creators in as free founding members before I open it up. After this batch it won't be free.

If you're a creator (or know one), comment and I'll send the link. Closing the spots this week.

I've been quietly working with a handful of fashion/lifestyle micro creators to get them deal-ready and in front of brands. It's working better than I expected, so I'm opening a few more free founding spots before this stops being free.

This round is 5 creators only. Founding members get in before anyone else and stay free — everyone after pays.

If you're 5k–100k and want one of the spots, drop your niche below or DM me. First come, first in.

We created a research process that started 111 agents put 123 claims in a queue, for checking and used up the entire Claude Max limit in around 30 minutes.

The unexpected thing was that the issue wasn't the model. The issue was spread of tasks and checking claims too late.

The biggest change came from one rule:

The agent that finds a claim cannot check that claim.

We also made sure every accepted claim had a primary-source URL and a supporting quote.

After making that change the same subscription lasted 10 times longer.

How are you stopping verification spread from getting out of control in -agent RAG systems?

Been noticing more product/tech work happening out of Surat lately and I'm curious about the local developer community here. For those of you doing full-stack work (React/Next, Node/Python, that kind of stack) — how are you finding opportunities? Mostly remote for out-of-city companies, or are there decent local/hybrid options too?

Also curious what the community feels is missing here compared to Bangalore/Pune. I work with a small team that leans on Surat talent and I'm always interested in connecting with good devs, so feel free to drop a comment or DM if you're in this space — happy to chat. 🙂

When I started working on RAG I thought changing models would make the difference.

That wasn't what I found.

Some of the improvements came from really simple changes. For example better chunking, adding a reranker and building an evaluation set with user questions made a big impact.

It made me curious, about what other teams discovered after building and deploying RAG systems.

What is one change that had a bigger impact than you thought it would?

It could be related to retrieval, indexing, chunking, evaluation, prompting, caching, GraphRAG or something else entirely.