OpenAI opens four-week Codex studio for faculty and researchers

Selected academics will use their own course, research, code, lab or department materials across four virtual sessions from July 29 to August 19.

OpenAI’s four-week virtual Codex studio will support faculty and researchers working on teaching, research, code, laboratory and department projects

OpenAI has opened applications for a four-week virtual studio that will help faculty and researchers use Codex to build one practical example from their own academic work.

The OpenAI Codex Summer Studio for Faculty & Researchers will run through four one-hour sessions on consecutive Wednesdays. Participants can work on teaching and student learning, research and code, or lab and department workflows. Coding experience is optional.

Applicants need an idea rather than a completed project. OpenAI asks them to bring one asset they are comfortable using, such as a course assignment, notebook, repository, data workflow, lab onboarding document, simulation concept or department process.

Selection is required. The OpenAI Education team will review applications and contact successful participants with calendar invitations and session links. The published program information does not give an application deadline, cohort size, selection criteria, cost or geographic restrictions.

Himanshu Koshe, Head of AI Deployment & Success for Edu at OpenAI, introduced the studio on LinkedIn. He wrote: “Bring an idea you’ve wanted to build. We’ll help you get started. The people closest to the problems should have the power to build what comes next.”

Koshe also wrote that academics are already using Codex to create interactive tools for students, test research approaches and automate tasks such as maintaining a Canvas course.

Three tracks cover teaching, research and university workflows

The studio divides academic work into three tracks. Teaching and student learning covers assignments, code examples, simulations, technical course materials, student guidance and feedback workflows.

Research and code is intended for work involving notebooks, repositories, scripts, data checks, simulations, experiments and reproducibility.

The third track focuses on lab and department workflows, including onboarding, standard operating procedures, student support, meeting preparation, project tracking and knowledge handoffs.

Each participant is expected to build one useful example using material connected to their chosen area. OpenAI will provide a Codex Build Kit containing starter workflows, prompts, example inputs, review checks and before-and-after examples.

Four sessions lead to a faculty showcase

The first session, scheduled for July 29, will examine how OpenAI Research uses Codex in research workflows. An OpenAI researcher will demonstrate tasks including reading an unfamiliar repository or notebook, identifying failures, cleaning code, adding checks, running an experiment and summarizing changes.

On August 5, participants will separate into the three tracks and begin applying starter examples to their own material.

The August 12 session will introduce the Codex Build Kit. Planned topics may include repository walkthroughs, notebook cleanup, teaching simulations, reproducibility checks and lab onboarding.

Between August 12 and August 19, participants will submit a case-study snapshot explaining what they built, how they used Codex, what they reviewed or changed, what improved and what another faculty member could reuse.

The final session on August 19 will present examples from across the three tracks. Participants will examine the original academic work, how Codex was used, the human review involved and what changed during the process.

Selected examples may lead to follow-up interviews and possible publication through the OpenAI for Education website or other OpenAI Education channels. OpenAI states that publication requires approval from both the faculty member and their institution.

Applications request the applicant’s name, email address, institution, department, title or role, preferred track and proposed project. Applicants must also confirm that they are available and interested in joining the virtual studio. Questions can be sent to education@openai.com.