AI Coding Field Notes

Field notes on AI coding agents — what they cost, where they break, what shipped. Every published figure (prices, percentages, multiples, token counts and durations) as JSON and CSV, each row carrying the sentence it came from.

View the Project on GitHub xyzs996/ai-coding-field-notes

AI Implementation

5 of the 24 write-ups here are tagged AI Implementation. Every figure quoted below is in the figures table with the sentence it came from.

AI Programming Tool Selection Strategy: From Rapid Prototyping to Long-term Collaboration

A specialized code review agent beat Claude Code on accuracy across 200 real pull requests and 50 open-source repositories while burning about one-ninth the tokens.

Beyond Token Pricing: How Indie Devs Should Really Evaluate AI Model Costs

Microsoft’s evaluation of Kimi K3 landed on a number that should change how you read a pricing page: about 60 percent of the cost difference between models comes from the thinking depth a task requ…

From AI Demo to Product: Loop Engineering for Indie Devs

The agent processes 40-plus podcast channels overnight, transcribed and summarized, ready to read by morning.

The Hidden Costs of GPT-5.6 Model Selection: A Developer’s Real-World Guide

“Choosing the right GPT-5.6 model for your business is more about avoiding cost overruns than just picking the cheapest option.”

When AI Customer Service Backfired: Klarna’s Case and the Four-Stage Path to Enterprise AI Adoption

Klarna reported $4 million a year in savings and a 99.96 percent conversation engagement rate, the kind of pair of numbers that ends an internal debate before it starts.


All 24 write-ups