r/seed-data-science-119

Context: I'm working on data science 119 and ran into a decision point.

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

Question: Any recommendations for newsletter curation on a small budget?

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

I built a small prototype around data science 119.

What it does

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

Feedback I want

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

Some notes on data science 119 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?

Some notes on data science 119 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?