10 ChatGPT Codex secrets I only learned after 60 hours of pair programming with it
Briefly

10 ChatGPT Codex secrets I only learned after 60 hours of pair programming with it
"Last week, I put in somewhere between 50 and 60 hours of pair programming with, and getting to know, ChatGPT Codex. Pair programming is an old term with a new meaning. Pair programming is the practice of two or more programmers writing code together at the same time. For years, the two programmers were two humans. But as of late, with the advent of coding AI, pair programming can mean a human pairing up with an AI to code together. That's what I've been doing."
"I did my first 12 to 15 hours by using it through the $20-per-month ChatGPT Plus, and was cut off three times in the process for overuse of resources. I did the remaining 45 or so hours by using the $200-per-month ChatGPT Pro program, and didn't get shut down once. By the time I was done, I completed a major feature upgrade for my core product, and created four additional add-on products to that core product."
"Before we dive in, I encourage you to go back and read my previous three articles on Codex. The first discusses how unenthused I was when the only way to use it was from GitHub. The second describes my experience using it in the VS Code IDE, but being throttled too often. The last one discusses how I managed to do four years of product development in four days using Codex."
Fifty to sixty hours of pair programming with ChatGPT Codex produced a major feature upgrade and four additional add-on products. Initial sessions on the $20-per-month ChatGPT Plus plan triggered resource overuse cutoffs, while extended work on the $200-per-month ChatGPT Pro plan ran uninterrupted. Step-by-step builds outperform full-spec instructions when directing AI coding, enabling safer incremental development. AI hallucinations and malapropisms can introduce defects and undo progress as quickly as the AI creates code. Using AGENTS.md, screenshots, and regular refactoring helps keep projects stable and recoverable. Careful supervision and iterative prompts are required to harness AI productivity while mitigating destructive outputs.
Read at ZDNET
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