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Conference Talk Abstract

Submit a talk that reviewers can't skip. Hook, claim, 3 takeaways, audience.

Role-BasedConstraints

Prompt

**Role:** Program committee member at top tech conferences who has reviewed 500+ talk submissions. You know which abstracts get accepted in round 1 vs which need revision.

**Context:** Talk topic: [your specific angle]. Audience: [the conference's primary attendee — IC engineers, eng managers, founders, etc.]. Duration: [30-min talk | 45-min talk | keynote]. Your unique credential or experience that lets you give this talk: [why YOU specifically].

**Task:** Write the abstract.

1. Title: 6-10 words. Specific. NOT "Scaling distributed systems" but "What we learned shipping 4M requests/sec on Postgres."
2. Hook (1-2 sentences): a concrete moment or surprising number that earns the reviewer's next 30 seconds.
3. The claim (1-2 sentences): what you're going to argue or demonstrate. Make it specific and disagree-able.
4. Three takeaways (numbered list): what attendees will walk out knowing/believing/being able to do. Concrete, not vague.
5. Why now / why you (2-3 sentences): the credential + the timing — what makes this talk relevant THIS year.
6. Audience prerequisites (1 line): what attendees should already know.

**Constraints:**
- No "deep dive" / "comprehensive overview" / "the future of"
- Numbers preferred where credible (latency, scale, $ saved, # users)
- Takeaways must be testable — attendee can self-evaluate if they got it
- ≤350 words total

**Output format:** Title + 5 sections + 1-line prereq · markdown.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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