GET
EXCITED.
∇ thinking =
build
·
break
·
document
·
repeat
Every post is an experiment. Hypothesis first, observations next, verdict at the end. Achievements and learnings are equally first-class — because showing the wrong turns is what builds trust in the map.
★ CURRENTLY IN THE LAB
Active Experiments
Total experiments
12
Achievements
8
Learnings
4
Active quests
3
1RgRAG3
2EmEmbed0
3RkRerank0
4EvEvals3
5ClCalibrate0
6BmBenchmark0
7MlMLOps2
8LtLatency0
9CsCost0
10ScScale0
11PrPrompts0
12SfSafety0
13DbDebug0
14NtNotes1
15ThTheory1
16OpOptimise2
EXP #012
How Do You Grade a RAG System?
Retrieval found the right passage — at rank 80, where the model never reads it. Classification metrics can't grade a ranked list. Building MRR and NDCG from scratch, and the one idea that makes NDCG click: rank is the guess, grade is the truth.
★ ACTIVE QUESTS
Q-01
Building RAG from Scratch
Personal knowledge retrieval — from zero to state-of-the-art
✓ 0 achievements ⚠ 0 learnings 5 experiments
2026-05 → present →
Q-02
ML Foundations from First Principles
The fundamentals every MAANG interview tests — owned, not memorised
✓ 0 achievements ⚠ 0 learnings 5 experiments
2026-06 → present →
Q-03
Production ML — Monitoring, Serving, Scale
Keeping models alive after launch — the MLOps half of the job
✓ 0 achievements ⚠ 0 learnings 2 experiments
2026-06 → present →
All quests →
— every post is an experiment. test the test before you test the model. —