Avani Chaskar
Avani Chaskar, Ashutosh MaheshwariGet insights into using AI for real world scenarios.
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 37 | Founded | 2 years ago | Last Issue | 19 days ago |
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avanichaskar.substack.comLatest Issues
RAG Retrieval Metrics: Score Your Retriever With 4 Numbers
Your dashboard says the retriever finds the right document 90% of the time.
Your users say the answers are wrong.
Both are true.
The retriever did find the right runbook.
It ranked it 4th, below a stale doc that has the wrong informatio...
RAG Evaluation Datasets: Build a Test Set You Can Trust in 4 Steps
Your new reranker scores 2 points higher.
The old reranker scored 72%. The new one scores 74%.
You have 50 test questions, and at that size the margin of error is about ±14 points.
Do you ship it?
By the end of this post you will know:...
Where RAG Fails?
A RAG answer can fail in two ways.
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The right context never reaches the model.
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Or it does—and the model still gets it wrong.
If you only score the final answer, you cannot tell which one happened.
The failure map...
[2-minute read] How to Safely Swap an LLM in Production
Most teams treat an LLM upgrade like this:
model = "new-model"
Change the config. Run a few tests. Ship it.
Can you switch models without breaking production?
An LLM API makes model changes look like a one-line configuratio...
How FastAPI Uses Pydantic to Validate Every Request
Recap: part 1 was validation basics, part 2 was fields and constraints, part 3 was nested models, part 4 was config. In production, you don’t call .model_validate() by hand — a framework does it on every request. Usually, that’s FastAPI....
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Authors
The writers behind this newsletter.
Senior Software Engineer & AI Architect | Deep Dives into RAG & Agentic Workflows
I've built products for over a billion users at YouTube and Google Search. Now, I deconstruct complex systems and production AI for 80,000+ engineers each week. Subscribe to learn the principles behind building at hyperscale.
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