u/OddArugula9422

Looking for Junior AI Engineer, GenAI Engineer, LLM Engineer, or Junior AI Architect opportunities globally.

Hands-on with Python, LLMs, RAG, LangGraph, FastAPI, vector databases, and agentic AI systems.

Open to WFO, hybrid, remote & relocation. Immediate availability.

If you’re hiring or know of a relevant opportunity, I’d appreciate a DM or referral.

Thank you!

We have Slack, GitHub, Jira, Notion, Confluence...

So why do we still end up asking teammates instead of searching?

Curious to hear your thoughts.

Companies already have Slack, GitHub, Jira, Notion, Confluence...

So why does so much company knowledge still live in people's heads?

Genuinely curious. What's your take?

I'm doing customer discovery to understand how engineering teams actually work as they grow.

I'm not building in public, pitching a product, or selling anything.

I'm looking for **one real story**.

What's one engineering problem your team has simply learned to live with?

What made it so difficult to solve?

I'd love to hear what happened.

No Pitch, no tool building just learning from the experience.

I'm doing customer discovery to understand how engineering teams actually work as they grow.

I'm not building in public, pitching a product, or selling anything.

I'm looking for one real story.

What's one engineering problem your team has simply learned to live with?

What made it so difficult to solve?

I'd love to hear what happened.

I'm talking to engineering teams to understand where context and knowledge break down. I'd love to hear your experience.

I'm spending the next few weeks talking to engineers, tech leads, PMs, and engineering managers to understand where teams lose the most time, context, and knowledge as they grow.

I'm not looking for generic answers—I want the stories behind the pain.

Some questions I'm curious about:

\- What's the most frustrating thing that slows your team down?

\- What's the last time you thought, "Didn't we already solve this?" but couldn't find the answer?

\- Where does important context disappear? Slack? Jira? GitHub? Docs? Meetings? Someone's memory?

\- What's the hardest information to find when you're debugging an issue, onboarding, or building a new feature?

\- What's a recurring problem your team has simply accepted as "that's just how it is"?

If you had a magic wand and could eliminate one engineering workflow problem forever, what would it be?

I'm not building a sales list or trying to pitch anyone. I'm simply trying to understand how real engineering teams work and where the biggest gaps still exist.

I'd really appreciate hearing your experiences—whether you're at a startup or a large company. Feel free to comment below or DM me if you'd rather share privately.

I'm trying to understand the problems engineering teams still struggle with as they grow.

I'm not interested in "our CI is slow." I'm interested in the painful stuff.

What's a problem that keeps coming back?

- When did missing context cost your team days or weeks of work?

- Have you ever rebuilt something because nobody knew it already existed?

- Has a decision been reversed simply because nobody knew why it was made?

- What engineering problem makes you think, "How is this still a problem in 2026?"

I'm looking for real stories from startups and large companies. What happened, and what did it cost your team?

I'm spending the next few weeks talking to engineers, tech leads, PMs, and engineering managers to understand where teams lose the most time, context, and knowledge as they grow.

I'm not looking for generic answers—I want the stories behind the pain.

Some questions I'm curious about:

- What's the most frustrating thing that slows your team down?

- What's the last time you thought, "Didn't we already solve this?" but couldn't find the answer?

- Where does important context disappear? Slack? Jira? GitHub? Docs? Meetings? Someone's memory?

- What's the hardest information to find when you're debugging an issue, onboarding, or building a new feature?

- What's a recurring problem your team has simply accepted as "that's just how it is"?

If you had a magic wand and could eliminate one engineering workflow problem forever, what would it be?

I'm not building a sales list or trying to pitch anyone. I'm simply trying to understand how real engineering teams work and where the biggest gaps still exist.

I'd really appreciate hearing your experiences—whether you're at a startup or a large company. Feel free to comment below or DM me if you'd rather share privately.

Built this in 48 hours. Be brutal.

Problem:

Teams re-debate closed decisions constantly.

Nobody built anything to stop it. So I did.

What it does:

Watches your Slack. When someone contradicts

a past decision, it flags it in-thread. Automatically.

Live results:

- 4/4 collisions caught

- 0 false positives

- Works inside existing Slack

What's broken? What's missing?

Would you actually use this?

(Repo in comments)

Problem I kept seeing:

Team decides something in Slack. Gets buried.

Someone re-proposes the opposite 2 weeks later.

Meeting called. 45 minutes wasted. Happens again next sprint.

What I built:

Watches your Slack channel. When a new message

semantically contradicts a past decision, it posts

a threaded warning automatically.

Real test results:

- 4/4 deliberate collisions caught

- 0 false positives

- No data leaves your machine

Open source. Free. Self-hosted.

Looking for teams to test this on real Slack channels.

What am I missing? Would you actually use this?

The fix gets merged. The postmortem gets written.

What doesn't survive: which hypotheses failed, which signal actually mattered, why that architectural decision made sense at 3am with half the data. That knowledge lives in one engineer's head until they change teams.

Six months later it's gone. You're starting cold on an incident you've already solved.

Has anyone actually cracked this — preserving investigation reasoning in a way the team reuses? Or is institutional knowledge loss just accepted infrastructure tax?