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When Engineers meet AI

Kannan Kalidasan

An engineer writing about Open Source AI, Software Agents, Physical AI and AI Engineering for builders who lead and leaders who build.

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Substack
PricingOnly free issuesPublishesWeekly
Issues66Founded3 years agoLast Issue6 days ago
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Latest Issues

The Token-Aware Engineer

A few years ago, software engineers spent most of their time writing code. Today, we increasingly spend our time generating it.

Image Source

Whether you’re using Claude Code, Codex, Cursor, OpenCode, or another coding agent, the workflow...

6 days ago
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1

JDBC to ADBC: A Technical Deep Dive

For decades, Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC) have been the undisputed standards for connecting applications to databases. They provided a unified API that abstracted away the complexities of vendor-sp...

a month ago
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How Distributed Inference Actually Works

I’ve been experimenting with local models recently, particularly Qwen3 Coder running through MLX on Apple Silicon. My current setup looks like this:

Development Machine

  • MacBook Pro M5 Pro - 48 GB Unified Memory

  • Qwen3 Coder runnin...

a month ago
6

Dense vs MoE Models Explained

Yesterday, I ran out of tokens in OpenAI Codex while oxidizing parts of my Python codebase into Rust. It was around 11:30 PM, and I had to wait another two hours for the limits to reset.

That moment felt strangely familiar.

Just like how...

a month ago
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2

Measuring Local LLM Performance Across Two Macs

I’ve been using a Mac Mini (M1, 2020) for a while now, both for personal use and for running local models. Recently, after getting a MacBook Pro (M5 Pro), I found myself curious about how much of a difference the new machine would actually...

2 months ago
8
2

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  • Kannan Kalidasan

    Read about how to create scalable, intelligent systems; spanning Data, AI Tooling, Software Engineering, and Engineering Philosophy.

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