Anthropic's Original Take-Home Assignment Now Open Source

Anthropic has made a significant move in the tech community by releasing its original performance take-home assignment to the public domain. The assignment, which is now available on GitHub, represents a transparent look into the company's engineering hiring process.

This release provides developers and aspiring engineers with direct access to the types of technical challenges used by one of the world's leading AI safety companies. The move has already sparked conversation within the developer community, highlighting the growing trend of transparency in technical hiring practices.

The assignment is hosted on GitHub under Anthropic's official repository, specifically titled "original_performance_takehome." This repository contains the complete take-home challenge that was previously used internally for evaluating engineering candidates.

By making this resource public, Anthropic has created a permanent, accessible record of their assessment criteria and technical expectations. The repository includes all necessary materials for understanding the assignment's scope and requirements.

Key aspects of the release include:

• Complete assignment specifications and requirements
• Technical context and problem statements
• Original evaluation criteria and expectations
• Structured framework for candidate assessment

The release has generated immediate interest within the technical community, particularly on platforms where developers discuss hiring practices and technical challenges. The assignment's availability has been noted on Y Combinator's Hacker News, a prominent forum for technology discussions.

Initial community engagement shows modest but meaningful interaction with the released materials. The discussion thread has received 5 points and 1 comment, indicating early interest from developers and industry observers.

Community members have expressed interest in several aspects of the release:

• The technical depth and complexity of the assignment
• How it compares to other company take-home challenges
• Potential use as a learning resource for interview preparation
• Insights into Anthropic's engineering culture and standards

The decision to open-source a take-home assignment aligns with broader industry trends toward transparency in technical hiring. Many companies have faced criticism for lengthy, unpaid take-home assignments that require significant time investment from candidates.

By making their assignment public, Anthropic provides a benchmark for what constitutes a reasonable and well-structured technical challenge. This transparency helps candidates better understand expectations and allows other companies to learn from Anthropic's approach.

The release comes at a time when the AI industry is experiencing intense competition for engineering talent. Companies are increasingly looking for ways to differentiate themselves and create positive candidate experiences while maintaining rigorous evaluation standards.

For developers preparing for technical interviews, this release offers a valuable study resource. The assignment provides concrete examples of the types of problems and expectations that might be encountered when applying to AI companies.

Engineering candidates can use this resource to:

• Understand the scope and time commitment typically expected
• Practice solving problems similar to those used in professional settings
• Gain insight into how technical skills are evaluated in the industry
• Prepare more effectively for their own interview processes

The open-source nature of the assignment means it can be continuously improved and adapted by the community, potentially creating a collaborative resource for technical interview preparation.

The release of Anthropic's original take-home assignment represents a meaningful contribution to the technical hiring landscape. It provides transparency into one of the industry's most respected AI companies while offering practical value to the developer community.

This move may encourage other companies to follow suit, potentially leading to more standardized and transparent hiring practices across the technology sector. As the industry continues to evolve, such transparency could help create more equitable and efficient evaluation processes for engineering talent.