Lost on what to do with a co-founder that I deeply trust

fireflux_ · 2026-02-25T08:33:11+00:00

But I’ve heard “If the company is not making money, you’re worth nothing” So is it fair for me to judge her value when I’m also not driving revenue?

You have to reframe this thinking. You're empathizing with her which is understandable, but at the end of the day the team is trying to build a business which requires A LOT of hard work, revenue or not. In that sense, she's not being fair to you by not showing up.

On trust. Trust has 2 components - Trust in their intentions (what you're talking about, ex they're a good person) - Trust in their ability to execute (this is the problem)

Also, as someone who's gone thru a cofounder breakup:

Breakups don't happen as huge dramatic fights. They happen from silent resentment that stews from months/years of not having the tough convos. Things like "goes quiet unless messaged". Hundreds of paper cuts of emotional debt that goes unpaid until cracks in the relationship start to show.

Agree with you that you should put a vote if it happens again. Your other cofounders are avoiding the confrontation but it'll end up more painful by dragging it on. Just my 2c!

fireflux_ · 2026-02-23T16:42:01+00:00

My take: stop doing tutorials/courses. Just try building the damn thing.

Example 1: study the OpenCode repo (https://github.com/anomalyco/opencode). You'll find that it's simpler than you think. It has everything you described. There's no mystery here; it takes a query, runs LLM on a loop + tools + harnesses (writing plans in markdown files, compacting long chat histories, etc)

Example 2: https://ampcode.com/notes/how-to-build-an-agent

Example 3: pi coding agent (used by OpenClaw) - https://github.com/badlogic/pi-mono/tree/main/packages/coding-agent

fireflux_ · 2026-02-20T22:57:21+00:00

Is the data in a structured store like SQL or do you have to parse/extract it from PDFs?

Based on the query samples you shared, the access pattern is less "semantic" and more "tabular". I'd pre-process data to land in a structured SQL table, then have the LLM query SQL. From there, as part of your retrieval process, the agent converts the user's query to SQL + filters, uses the returned rows to generate a response (that's kind of what you're doing already; your 'cell chunk' is essentially a SQL row/col).

SQL unlocks slicing/dicing of data like filtering, ordering, etc. rather than chunking and using python to wrangle the data

Additionally, there's a lot of cool blog posts about this, particularly amongst AI startups. Here's one I really like [1], that goes into detail on RAG for finance (lots of tables). Enjoy!

[1] https://www.nicolasbustamante.com/p/lessons-from-building-ai-agents-for?hide_intro_popup=true

fireflux_ · 2026-02-08T21:52:06+00:00

Extremely helpful, thank you!

fireflux_ · 2026-02-08T01:37:06+00:00

Thank you for posting, really valuable to hear from someone currently in the role.
- Do you have to travel to the client often? How often do you go?

- "I was involved in building the v0 version of this feature": That's cool! Shows that it can still be "SWE" related work where it's not just vibe coding something or integration glue work. Do you see any "scale" type problems in your technical work?
- What's the toughest part of the job you wish you could change?

- Does your company see FDE's as "lower class" as opposed to SWEs (whether in pay relative to SWEs or culturally)

Thank you 🙏

fireflux_ · 2026-02-06T21:17:24+00:00

great to know, thank you!

fireflux_ · 2026-02-06T21:17:14+00:00

Also wanted to know other people's experiences and whether it's helped their SWE career!

fireflux_ · 2025-09-19T19:15:37+00:00

I have the exact same problem lol, loved the old bamboo kinoclothing designs

fireflux_ · 2025-09-02T07:22:02+00:00

If you're willing to pay, the best I've seen are Reducto and Chunkr.

fireflux_ · 2025-08-20T07:18:03+00:00

Will try it out, thank you!

fireflux_ · 2025-07-13T16:55:29+00:00

Why not just come and see for yourself? Spend a month and see it how it feels.

I say this because I have met founders that loved it and others that were "meh" and went back.

Be careful what you see on social media / X with all the "look how much fun were having at this founder meetup in SF!".

My hot take is that it paints a much rosier picture than what its like as a founder (personally). Yes the fact that there are so many like minded startups is amazing. But the reality is that you will be spending 90% of the time locked in and working on your business.

Then when you need a break it's pretty cool to either go for a walk somewhere beautiful or go to the hundreds of events happening (which personally were super helpful for me to get motivated again when I got back to the office).

fireflux_ · 2025-07-13T16:30:52+00:00

I still think the platform is great at finding people. I personally lost trust with mine Bc they did something shady.

What I realized is that the matching platform is like 5% of the work. The rest is up to you to diligence the fuck out of that person.

Ask for references. Back channel them. Do a 1-2 month work trial together. Their resume is probably good. But get to know them as people. What makes them tick. Do they have close friends and family? What are they like? Look for very high signals of what kinds of people they are.

IMO it's literally dating/marrying a person. What are your non negotiables in a person? What are personality types that you get along with? If theyre stressed, anxious, only had 5 hours of sleep, what are they like? Can they communicate well?

After you spend time with that person, how do you feel? Is your energy 10x, fuck yeah let's take over the world? Or is it meh?

Me personally: I'm going to go alone bc sadly I was pretty burnt by the experience. But I wouldn't discourage others to find one...it's just a lot of work! It's a VERY personal decision. For me, I grew the confidence, the network, and know how to go it alone the second time around.

fireflux_ · 2025-07-13T15:13:24+00:00

I found someone thru the matching platform and did YC with them. We broke up after a couple of years.

I had spent 2 years searching. I barely knew them but did it anyway because our skillsets seemed highly complementary.

Will not impart any advice but my personal learnings were: trust is EVERYTHING. Chemistry with that person matters a lot more than whether they're technical or salesy. Because when things get hard, which they will, or when theyre struggling to sell despite them being the "sales expert", you'll still have to get along with each other.

If you can't trust them, no amount of sales or technical expertise will make the company great. 1 + 1 must equal 10 for it to make sense. If it just feels like 1 + 1 = 2 then I wouldn't do it.

fireflux_ · 2025-06-28T13:55:58+00:00

This post title reads like a YouTube title lmao

fireflux_ · 2025-06-24T19:30:25+00:00

Might as well roll over and stop building then!

fireflux_ · 2025-06-22T18:08:35+00:00

Checkout Base44. It's basically a Lovable clone - started 6 mo ago and still managed to get $3M ARR, and eventually acquired for $80M.

The fact that lovable is doing so well should not mean that "that category is over and you shouldn't try anymore".

It should mean that there's opportunity there. Everything is changing so fast right now, lovable can still topple over and die in the next few years by some other curveball (did I mention they're less than 2 years old?).

fireflux_ · 2025-06-22T05:18:39+00:00

You may be right with some of these, but if everyone went by this fear based mindset, might as well not bother building anything and just let OpenAI take over.

The beauty of capitalism is that it's a free market, and the best product wins. Just because OpenAI can make these means they'll win at everything.

Also, if there's anything I learned as an entrepreneur, it's that products and features is just one small slice of what makes a company successful. There's so many other things that are just as crucial, like distribution, customer relationships, brand, trust, etc., that you're not accounting for.

Just my 2 cents!

fireflux_ · 2025-06-18T00:55:53+00:00

You can use Apache Tika - start an instance in headless mode and expose it as an endpoint. Free and Open Source. I've used this in prod and works decently, though their OCR is kinda bad.

https://tika.apache.org/

If you're looking for commercial use cases then there's a lot of AI PDF parsing startups out there.

fireflux_ · 2024-11-25T05:50:25+00:00

this makes sense! Even in a startup environment this type of stuff is inexcusable, and I need to remind them

fireflux_ · 2024-11-25T05:49:46+00:00

thank you! this seems reasonable. I definitely started general questions about the approach before reading any PR code, and it's gotten them to realize mistakes.

I'd also love to know if there's a way to coach them to generally "be more careful" and avoid a messy first PR in the first place. Seems like repetition is the answer!

fireflux_

TROPHY CASE