Building with AI, keeping it human

New pattern: capture a HAR file and let Codex reverse-engineer the data flow.

I used to do this manually: open DevTools, scan Network, guess which calls mattered, then stitch together a script. Now I just save a HAR, hand it to Codex, and let it do the archaeology. It’s been a big speedup for the messy, real-world sites that don’t want to be scraped.

HAR files are a map, not just a log

A HAR file is basically a time-stamped ledger of every request and response. The key trick is that it’s JSON, which means tools like jq (or a tiny Python parser) can slice it fast. That gives Codex a structured way to explore the site quickly without overloading the context window.

The workflow that keeps me out of the weeds

I’m converging on a simple loop:

1. Capture a HAR in Chrome DevTools while doing the exact thing I want to automate.
2. Ask Codex to inspect the HAR, identify API-like calls, and trace where the data I care about shows up.
3. Have it generate a Python script that replays those requests or extracts the HTML if that’s the only path.

When the site has dozens (or hundreds) of resources, this saves a ton of time. The HAR is a breadcrumb trail. Codex is the bloodhound.

Auth isn’t a blocker if you plan for it

For logged-in sites, I just ask the script to accept headers on the command line. That way I can paste in a session cookie or bearer token and keep the script generic. It’s boring, but it keeps the extraction logic clean and repeatable.

Do I need a library for this?

Maybe. I’ve been tempted to write a small library or Codex skill to normalize HAR parsing and expose “find me the data” helpers. But the reality is: Codex is already fine at reading JSON and writing a one-off parser. The tradeoff is tokens and time. If a simple helper set can shrink both, it might be worth it. If not, the DIY path wins.

I’ll keep experimenting and see what actually feels like friction. If you’re doing something similar—or have opinions on HAR tooling—hit me up.