# beat-claude

> Public hiring challenges where you must beat a generic AI answer to earn an interview

- Repository: https://github.com/ericosiu/beat-claude
- Category: Other
- Stars: 202 · Forks: 34 · Language: Python · License: not stated
- Experience: Some experience
- Page: https://ir.adyog.com/repos/ericosiu/beat-claude/

Beat Claude is a public hiring challenge run by the marketing agency Single Grain. Candidates pick a task for a role, build a real work artifact, and submit it with evidence. The aim is to find people who add judgment and proof to what an AI tool produces from the brief alone.

The repo holds the candidate briefs, the public scoring guide, fixture datasets and a validator script. Reviewers score answers against private benchmarks that are not published, to discourage rubric gaming. Strong submissions may get a follow-up exercise or a live walkthrough.

It is not software you run for its own sake. It is a hiring process in the open, and its design is worth reading if you want to see how a company tests AI-assisted work. Tools of any kind are allowed, but you must disclose how you used them.

## What it does

- **Role-specific briefs**: Challenges cover general, internship, marketing, paid media, SEO, engineering, design, sales, YouTube, talent and operations roles. Each is meant to take 1-2 hours.
- **Seven-part submission packet**: Every submission needs a written answer (4 pages max), a working artifact, an evidence log, source-labeled numbers, an AI usage disclosure, failure handling and artifact access.
- **Validator script**: A script checks that all seven sections are present and that numbers carry source labels. It also checks for anything the review-manipulation detector would flag.
- **Fixture datasets**: Role challenges include small synthetic datasets with planted issues. They rotate between hiring rounds, so shared answers go stale.
- **Private review**: Reviewers score against private benchmarks, and may follow up with a walkthrough or proof check. Only a high-level scoring guide is public.

## What you could build

- Apply for an AI automation internship by running an agent against the seeded fixture data.
- Practice building a marketing, SEO or sales operating artifact against a realistic brief.
- Pre-screen a submission with the validator script to check its sections and source labels.
- Study how a company designs an AI-era hiring test, with versioned briefs and rotating fixtures.
- Build a portfolio piece with an evidence log and AI usage disclosure.

## Who it's for

Job seekers in marketing, sales, design, engineering or operations who already work with AI tools and can show real, checkable work; no special setup is needed beyond reading a brief.

## Get started

Pick a challenge from the challenges folder (General 000 is the open one), read the brief, and build the artifact. Pre-screen your packet with the validator script, then apply through the Single Grain careers page.

```
python3 scripts/validate_submission.py path/to/your_submission.md
```

Tags: hiring, ai-literacy, marketing, challenge, careers