About PraxisAI

Software engineering now happens with an AI agent in the loop, and the skills that matter have shifted toward scoping a problem, directing the agent, verifying its output and explaining the result. PraxisAI gives engineers a place to practice that work on real code and gives hiring teams a way to assess it, with the evidence attached.

On the practice site, engineers take timed bug-fix challenges drawn from real GitHub issues in open-source Python projects, and take-home projects built from a brief, with an AI agent in browser VS Code. Each round is graded by tests and recorded, and the report scores six dimensions: outcome, prompt quality, token economy, verification, speed and recovery.

Free practice shows a score, verdict and grading result. Paid plan access adds detailed reports with recorded prompts, prompt coaching and replay. See the sample report and the practice guides.

PraxisAI for hiring teams assesses engineers on real repository bugs and take-homes with a coding agent. Grading tests check the outcome, and the recorded prompts, agent activity and test runs support review of the candidate's process. Assessments are priced per assessment, agreed with each team.

By fixed rules applied to the recording, with the evidence behind every number. Scores help a person review the work; they do not predict job performance and are not meant to be the sole basis for a hiring decision. The full method and its known limits are on How scoring works.

No. PraxisAI lives at www.praxisai.site and is not affiliated with Praxis AI, the education company, or with open-source projects named Praxis.

Email info@praxisai.site or use the contact page. Updates are posted on X.