𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗢𝗻𝗹𝗶𝗻𝗲 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀
ML models need fresh data to work. You need online feature pipelines.
Start with a clear goal. Define success first. This stops you from building things you do not need.
Build a simple version first. A small working system is better than a big broken one.
Test your code. Check for failures. Monitor your system in production. Use metrics to find errors.
Avoid these traps:
- Over-engineering for future scale.
- Ignoring technical debt.
- Building too many abstractions.
Follow these rules:
- Keep it simple.
- Measure before you optimize.
- Automate manual tasks.
- Use tools your team understands.
Your plan:
- This week: Audit your system. Find one gap.
- This month: Fix the gap. Measure the impact.
- This quarter: Review and refine.