← MLOps & ML Engineering / 54

mediumOpenAI MetaNetflix

How do you build a data flywheel from production feedback, and what makes feedback loops go wrong?

Production usage can become your best source of training data, or a self-reinforcing trap. The signal is knowing how to capture clean feedback and how to break the loops that quietly corrupt the model.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Production usage can become your best source of training data, or a self-reinforcing trap. The signal is knowing how to capture clean feedback and how to break the loops that quietly corrupt the model.

Unlock the other 750 answers · ₹2,000 / $25Your progress and mastery stay saved · 6 months · one payment · no auto-renew

UP NEXT ON YOUR JOURNEY

Next in this trackWalk me through deploying and scaling model inference on Kubernetes.Popular right nowWhy do transformers scale attention scores by 1/√d_k, and what breaks if you skip it?Popular right nowWhen do you choose prompting vs RAG vs fine-tuning for a customer problem?

DISCUSSION · 0

No comments yet — be the first to share your approach.