Software Developers: Share Your AI Coding Sessions

$500/task

rate as listed

Workload: ~10 hrs/week
Engagement: Project-based
Location: Location not stated
Field: STEM and Coding

Use OpenCode on a real software project while recorded sessions show how you select and work with AI models. The research focuses on authentic terminal-based development rather than assigned coding exercises.

The work

You will continue building your own verifiable software project in OpenCode, a terminal-based coding assistant, while each working session is recorded. Projects may include a side project, startup, or LLM-powered feature. For each task, you will use one chat, select from the provided open-weight and Gemini models, and switch models when you naturally would.

What the platform screens for

Mercor is looking for developers who already use AI coding tools such as Cursor, Claude Code, Codex, or Cline and can describe specific, recent workflows. Screening is likely to verify that your project is real, that you can work fluently with git and a terminal on Mac or Linux, and that your model choices reflect the needs of the coding task. Experience building agentic or LLM-integrated features is a plus, not a stated requirement.

Logistics

The project is remote, with flexible scheduling at about 10 hours per week and an immediate start. The listing does not specify recurring synchronous meetings, but recorded OpenCode sessions are central to the work. Pay band: $100–250/hr

What they look for

Active development of a verifiable software project
Regular use of AI coding assistants such as Cursor, Claude Code, Codex, or Cline
Terminal-based software development
Git workflows on Mac or Linux
Task-level judgment when selecting and switching AI models
Agentic or LLM-integrated feature development

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This checks whether there is a genuine project suitable for natural recorded work, rather than a dormant repository or a project created solely for screening.
A strong answer: Identify the project, its users or purpose, the current stack, and a feature or issue worked on recently. Point to concrete evidence such as repository activity, a deployed product, release history, or a live demonstration without exposing confidential material.
Where people lose it: Candidates lose points by describing an idea or old repository without recent commits, active issues, deployment evidence, or a specific current workstream.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

STEM AND CODING on Sidequest

What stem and coding AI work pays

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