the nilenso blog. ensonians write about work and life

Artisanal shims for the bitter lesson age
Have you priced in the bitter lesson in your AI application's architecture?
Atharva Raykar

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What are popular AI coding benchmarks actually measuring?
Popular benchmarks are narrower than you'd want.
Atharva Raykar

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The common sense unit of work
Consider refactoring the unit of work that your team operates on.
Srihari Sriraman
The quality of AI-assisted software depends on unit of work management
The craft of AI-assisted software creation is substantially about correctly managing units of work.
Atharva Raykar

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My Quarterly System Health Check-in
An operational exercise for engineering leaders.
Srihari Sriraman
Why Does AI Feel So Different?
More about the recursive paradigm shifting paradigm shift.
Srihari Sriraman
How I keep up with AI progress
A curation of quality sources to keep up with AI progress.
Atharva Raykar

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AI-assisted coding for teams that can't get away with vibes
A playbook for building high-quality software with AI.
Atharva Raykar

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Experimenting with Self-Hosted LLMs for Text-to-SQL
Yogi pits local and frontier LLMs against each other to see how they fare on Text-to-SQL tasks.
Yogiraj Hendre
Exploring RAG based approaches for Text-to-SQL
Tarun iteratively improves upon a Retrieval-Augmented Generation (RAG) pipeline to generate SQL queries from natural language.
Tarun Kumar
MCP explained without hype or fluff
tldr; like most protocols, MCP solves the M⨯N integration problem by turning it into an M+N integration problem.
Atharva Raykar

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