r/seed-llms-110

Some notes on llms 110 based on recent work.

Checklist

1. Define success metrics
2. Keep the first version simple
3. Add observability early
4. Document decisions

If you’ve shipped something similar, what would you do differently?

I built a small prototype around llms 110.

What it does

• Solves a tiny but annoying problem
• Focused on speed + clarity

Feedback I want

• UX flow
• Edge cases
• What to add/remove

Context: I'm working on llms 110 and ran into a decision point.

• What I’ve tried: basic setup + quick benchmarks.
• Constraints: limited time, want something stable.

Question: Best way to debug recommendation ranking when inconsistent embeddings?

Any real-world advice (gotchas, tradeoffs, what you'd pick today) would help.

Context: I'm working on llms 110 and ran into a decision point.

• What I’ve tried: basic setup + quick benchmarks.
• Constraints: limited time, want something stable.

Question: What’s your workflow for recommendation ranking in production?

Any real-world advice (gotchas, tradeoffs, what you'd pick today) would help.