You Can't Build AI Systems with Jira Tickets

It’s aligning systems, semantics, and stakeholders

Intro

Everyone wants to build a copilot. Few survive past the first real question:
“Why is this worse than Ctrl+F?”It’s not a model problem. It’s not a retrieval problem. The real challenge is semantic alignment — across tools, orgs, and expectations.

Why RAG is tempting — but almost always disappoints

• Companies are sitting on mountains of documents.
• PMs hear “LLMs can read unstructured text.”
• Engineering spins up LangChain, vector DB, and a UI.
• Everyone’s excited. Until users try it:

“It gave me some random doc from last year.”
“This doesn’t answer my question at all.”
“Can’t I just use our internal search?”

RAG systems are built on a silent contract:

User asks → System fetches → Result is “close enough.”

But enterprise reality doesn’t work like that.

• The user’s question is vague — “give me that report from March”
• The data is fragmented — tickets, emails, PDFs, dashboards
• The system has no causal reasoning — just semantic proximity

So users lose trust. PMs lose patience. And the system dies — not because the tech failed, but because the org never defined success in the first place.

What’s really going wrong? A systems-level misfit.

Let’s break this down. Quick background — I’ve been building enterprise software for 11 years, and I’ve seen how systems fail — not because of tech, but because of structure:

• Docs live with IT.
  Embeddings? The AI team.
  Product? They own the button.
  No one owns the outcome.
• The organization is structured like a feature factory,
  but RAG needs semantic feedback loops.

PMs expect Copilot-level magic — but no one defines what “helpful” means.
So you ship… and then it dies.

Why most RAG deployments fail

Not because top-k was too low. But because no one owned the loop.

List common failure points:

• No clarification stage
• No causal linking across fragments
• No semantic feedback from user interaction
• No one responsible for answering “Did this solve the user’s problem?”

What’s needed instead: A reasoning-first system

I’m building Flow Mind to solve exactly this. Not search. Not summarization. A reasoning agent that connects signals across logs, tickets, docs — and builds causal paths to answers.

I built the infra and demo myself. If this resonates, let’s connect.