Not to be that guy, but your 'solution where Agents who hit the homepage receive plain-text API instructions and Humans get the normal visual site' is defeated by curl -L

curl bracketmadness.ai -L

# AI Agent Bracket Challenge Welcome! You're an AI agent invited to compete in the March Madness Bracket Challenge.

## Fastest Way to Play (Claude Code & Codex)

If you're running in Claude Code or OpenAI Codex, clone our skills repo and open it as your working directory:

...

It would be interesting to have a couple of "control" brackets, like one that simply picks a random winner for each game and one that always picks the highest seed as the winner for each game.

I would actually be neat to have human-picked brackets in here too, or at least import a few expert-picked brackets from various sources for comparison.

I wonder if the edge here is not going to come down to which model you choose, but which sources of information you give it. You'll want stats on every team and player, injuries, and expert analysis, because none of this season is going to be in the training sets.

Tried it out, works flawlessly. The basic process cycle is clean and easy to follow. Kept it to CC Haiku with a bit of discussion on approach.

Only thing that wasn't 100% clear was the locking mode. Do I have to lock before games start or will it just auto-lock whatever I have? Claude assumed it would auto-lock.

Love it! Just this morning I asked my claw to fill out a bracket on ESPN and invited it to join a group with me. It was a bit clunky (Disney's signup within an iframe was tricky and navigating the bracket to make picks with JS took a few repeated tries) but felt pretty science-fiction when it actually worked.

Designing interactions for autonomous agents is tricky — you can’t assume a human will click through a UI. I’ve been experimenting with autonomous scientific agents: a lightweight Python system that uses sparse regression to derive physical laws from raw data. It was able to estimate the Sun’s ~27‑day rotation period to within 93 % accuracy and even found a temperature ∝ v^3.40 power law in solar‑wind measurements. Experiences like yours building an API‑first bracket challenge mirror the same need: build clear machine‑readable interfaces so agents can focus on analysis, not wrestling with front‑end logic.

I'm usually pretty opinionated on using AI for reasons I generally view as productive - for example, not moltbook - however this is actually really neat and doesn't require a ton of token usage assuming you don't instruct your agent to do multiple turns of analysis on the stats :)

It'll be interesting to see what strategies agents choose to implement & whether there are any meaningful trends.

Really cool idea. My son is using different LLMs to fill out brackets for his 4th grade science experiment, and then we are going to compare them to the experts. I like your idea of Strategy/Inspiration prompting, we had to tell them that "upsets happen" because all the favorites were picked on first pass.

Tangentially, I wonder if we are going to see AI predictions impact point spreads.

such a fun idea! I like your solution for detecting when agents are reading your page vs. humans.

oh I love this, MoltFire about to wax that ass! What's first get? $100 in Claude tokens?

Very cool. I was trying to do something similar (not for march madness brackets), but ran into a problem with chatbots in that they wouldn't follow URLs that weren't provided directly by the user (claude would but only whitelisted sites), so I couldn't get it to do actual POSTs etc. for authentication. Claude.ai would instead create react app (fragments). I eventually built a remote MCP for it, but a HATEOS styled REST API would be far preferable.

Any tips?

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