Understand how you build with AI.
So, how do builders build now?
We noticed that something strange is happening. We're all writing software with AI, but we are mostly doing it alone, with no real sense of how anyone else does it.
So we made a tool to help you understand how you build with AI.
It reads your Claude, Codex, and Cursor sessions, so you can discover things about how you build.
With time, as more people upload theirs, we'll be able to show you how you compare to other builders.
So far, 227,647 sessions have been uploaded and analyzed.
Here are examples of what people have learned about their coding habits...
Which archetype are you?
The Architect
You plan first, codify your decisions, and build scaffolding that compounds.
Which model do you use most?
You love Opus 4.7 Fast
You reach for Opus 4.7 in 72% of your sessions, GPT-5.5 in 22%.
When are you most productive?
Night owl
70% of your commits land between 10 PM and 2 AM, peaking around 11 PM.
How often do you plan?
62% in plan mode
You open in plan mode before writing code, skipping it on quick fixes.
What's your go-to prompt?
"make it prettier"
Your most-used phrase, across 11 different sessions.
How many agents do you run?
6 agents in parallel
You've run as many as 6 coding agents at once across 4 repos.
How long are your prompts?
Straight to the point
80% of your prompts are under 10 words. You say a lot with a little.
Your most cryptic prompt?
"make teh other thing wrok not this 1"
You sent this at 1 AM with zero context. The agent somehow figured out what you meant.
How polite are you to your agents?
You thank all the time
You thanked your agents 84 times in the last month. When the robots take over, they'll remember you fondly.
How often do you change course?
You steer, hard
You stop and redirect the agent mid-task rather than let it run off, about 4 prompts in 10.
What's your longest agent run?
4h 12m
One agent spent over four hours straight chasing a flaky test suite before you stepped in.
What's your biggest crash out?
"I LITERALLY SAID DONT TOUCH THAT FILE"
After the third time it ignored you, the caps lock came on and never went back off.
How much did you ship?
47,000 lines
Across 420 commits and 35 pull requests in the last month.
How do you see your agent?
Like a design partner
You bounce ideas before writing code, ask for pushback, and change course when it disagrees. Less tool, more teammate.
When do you ship most?
Tuesdays
Your single biggest push of the month landed on a Tuesday.
This is an experiment from YC. Nobody really knows yet what it means to build well with coding agents, and we are trying to find out.
Two ways to upload coding sessions
It looks at the AI session transcripts on your computer. Where you run the command tells it whether to analyze every project at once or just one.
Option 1: All my repos (Recommended)
Best for a broader picture across projects. Change into the parent folder that holds your repos, then run.
$ curl -fsSL https://paxel.ycombinator.com/upload.sh | bash
Option 2: Just one repo
Best for focusing on a single project. Change into that project's folder (replace ~/path/to/your-project with the real path) and run.
$ cd ~/path/to/your-project && curl -fsSL https://paxel.ycombinator.com/upload.sh | bash
You can use this prompt in Claude, Codex, or Cursor to find all your repos on your machine with AI transcripts, show you the list, and hand back ready-to-run commands for the ones you pick.
&& curl -fsSL https://paxel.ycombinator.com/upload.sh | bash"><br>Find every repo on my machine where I've used Claude Code, Codex CLI, or Cursor. Check ~/.claude/projects/, ~/.codex/sessions/, and ~/Library/Application Support/Cursor/User/workspaceStorage/ (macOS).
For each repo, list name, absolute path, and total session count. Ask me which ones to include.
For each one I pick, hand back this command with the path filled in:
cd && curl -fsSL https://paxel.ycombinator.com/upload.sh | bash
What you get
You get a builder profile, a snapshot of how you work with AI across five dimensions of steering, execution, engineering, product instinct, and planning.
We name the archetypes we see in your sessions, whether you build like an Architect, a Quality Guardian, a Velocity Machine, or a Night Owl. We also pull out your decision patterns, the signature moves you make when directing the AI, drawn from real exchanges in your transcripts.
Then we point at your growth edge, a few specific things to try next, grounded in your actual sessions rather than generic advice.
One command, runs locally
Sign in with your email, then run the command in your terminal from the repo you want analyzed. The analysis runs in Docker on your own machine, so you'll need Docker installed and running first. In about 15 to 30 minutes you get your profile back with scores, archetypes, decision patterns, and a growth edge.
Your working tree, your .env files, and your raw...