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Before preparing a GPT-6 Astra presentation, write down what you want the audience to decide. A manager asking colleagues to approve a change in dispatch procedures needs a different argument from a founder introducing a business to a potential partner. The same company background could appear in both talks, but it would serve different purposes.

OpenAI documents GPT-6 Astra for tasks including research and document creation. For a presentation, a useful starting assignment is a written slide brief: the argument, the evidence behind it and the explanation the speaker will give. Whether your chosen application can turn that brief into a finished presentation file depends on the tools it provides.

Give the presentation a question to answer

Consider a hypothetical packaging distributor proposing a change to its dispatch process. The presenter wants permission to try a different handover between the warehouse and the delivery team. The audience needs to understand the existing problem and how the proposed trial would be judged.

That is a more useful brief than “make a professional presentation about improving operations.” It identifies a decision and gives the presentation a stopping point. A history of the company may be unnecessary if everyone in the room already knows it.

Write a short audience note before using GPT-6 Astra through SeedRouter. State who will attend, what they already know and which decision they can make. Add the available speaking time. If the file will be circulated without a presenter, say so: the reader will need explanations that would otherwise be spoken.

Ask for the argument in plain text first. You should be able to follow why the recommendation comes after the evidence without relying on a theme, animation or photograph.

Build the GPT-6 Astra presentation from a small source pack

Gather the material needed for that decision. In the dispatch example, this might include a description of the current handover and records of missed collections. Give each document a short label and retain its date. Separate an observed problem from someone's proposed explanation of it.

If the records show a missed collection, they do not automatically establish why it happened. Keep the cause open until the source material supports one. This distinction belongs in the brief so the generated narrative does not turn a sequence of events into an established explanation.

OpenAI's prompting guidance recommends precise instructions and relevant context. It also describes using headings to distinguish instructions from supporting material. You can apply that simply, with sections for the audience, the requested decision and the documents the model may use.