Inspiration
I often prepare presentations for school projects, competitions, and demo booths. The same project may need to be explained in 30 seconds, one minute, or three minutes. Rewriting the presentation each time is difficult, and general AI tools can sometimes create long, unnatural, or unsupported claims.
What it does
PitchPilot is a reusable Codex skill that turns basic project information into clear, natural, and timed presentation materials.
It generates:
- 30-second booth pitches
- 1-minute elevator pitches
- 3-minute presentation scripts
- Expected judge questions and answers
- Presentation checklists
- Korean, English, and bilingual outputs
- Natural rewrites of AI-sounding sentences
PitchPilot also follows factuality rules. It does not present unsupported statistics, awards, partnerships, prices, user counts, or unfinished features as verified facts.
How I built it
I used Codex with GPT-5.6 to design, implement, test, and document PitchPilot.
The project includes a SKILL.md workflow, reusable templates, project-information intake rules, examples, evaluation criteria, validation scripts, and automated tests.
I made the main product decisions, including the target users, supported presentation lengths, bilingual output, and factuality rules.
Challenges
The main challenge was reducing project information to fit a strict time limit without removing the most important points.
Another challenge was creating natural spoken language while preventing unsupported claims from being added.
Accomplishments
PitchPilot works directly inside Codex without an external API key or server.
It provides a repeatable workflow instead of requiring users to write a new prompt every time they prepare a presentation.
What I learned
I learned that a reusable AI skill needs more than good prompts. It also needs clear input rules, output structures, factuality safeguards, examples, and tests.
What's next
Future versions could generate slide outlines, measure recorded speech duration, save multiple project profiles, and support team collaboration.
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