Your Project Story
Prepare a project story that communicates your contributions clearly and accurately during interviews. Organize it around five clearly connected parts: customer, problem, build, proof, and handoff. Select a project with specific checkable artifacts, distinguish your decisions and implementation from collaborators’ work, and explain one meaningful trade-off. Report outcomes with their denominators and limits, and describe only the operating responsibilities someone actually accepted. Practice introductory, presentation, and deep-dive versions while keeping the underlying facts consistent. Turn the account into a résumé bullet that preserves the result’s scope, and identify evidence gaps to verify before telling the story.
“Tell me about something you built.” Every stage of the loop asks some version of this, and most candidates answer it differently each time. A better approach is one well-prepared project story told at different depths: the facts stay fixed, and only the emphasis changes. This lesson builds that story from the project candidate in your checklist and turns it into a résumé bullet.
What goes into the story?
The course’s project-story framework is customer → problem → build → proof → handoff. Each part answers one question an interviewer will ask:
Customer: Who used or needed the work? An internal operator, another engineering team, or an external customer all count.
Problem: What was going wrong in their workflow, and why did it matter?
Build: What did you decide and implement, and what did collaborators contribute?
Proof: What did you check, what did it show, and where does that result stop?
Handoff: Who took responsibility for running it afterward? If nobody did, say so.
Together, the five parts let an interviewer follow the work from a need to a team that owns it. Keep all five even in a short answer, and change only how much detail each gets.
The framework mirrors the role. OpenAI’s role description covers discovery, scoping, design, building, production rollout, partnership with customer teams, adoption, workflow impact, and eval-driven feedback, and it values direct coding, delivery trade-offs, and patterns others can reuse. Your story should show those skills at whatever scale your project reached; it doesn’t need to claim production.
OpenAI’s interview guide says it wants to understand your background and contribution, and it values collaboration, communication, and openness to feedback. A precise account of your part invites good follow-up questions about how you made decisions with other people.
Which project should you tell?
Start with the candidate in preparation-checklist.md. Gather the artifacts you’re allowed to use: a design note, pull ...