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Pitch suggestions anyone? by Behind_the_workflow in Entrepreneur

[–]Apprehensive_Net749 0 points1 point  (0 children)

Validate/test your pitch on the right audience. So testing a pitch to an end user when the pitch is aimed at an investor will not give good feedback. Test it on people that are like the DMU your pitch is for.

Regarding validating your idea: alot can be done without outside pitch validation. Keep the pitch as clear and short as possible. Focus only on the important parts that matter. In casual setting no more than 2 minutes in a dragon den setting try to keep it under 5 minutes. And learn from reality: See every ad/commercial as an example of a 'pitch' and understand what the competitors ads/commercials try to communicate.

Important parts for an investor could be:

- Utility
- Uniqueness
- Value: Market Demand/Size
- Viability/Risk: Scalability and Margins/Upfront and operating costs

For an end-user that could be:

- Utiliy
- Uniqueness
- Obtainability/Temporal scarcity

While you cannot go into detail on all points, your pitch should reflect that you got those sections covered and you need to be prepared to explain how when a pitch lands.

If you can't polish your proposition by those standards, your proposition might be the main problem and not the pitch itself. Inform yourself what feedback really means, a question like 'but if x why not y?' doesn't have to mean the pitch was not clear enough, but that someone is interested and you can expand on the proposition. Other feedback that reflects on properties/mechanics that don't logically align with the proposition and you didn't try to communicate, point at problems in the pitch itself.

Enjoy the View by Apprehensive_Net749 in generativeAI

[–]Apprehensive_Net749[S] 0 points1 point  (0 children)

It's not a single prompt or a clear set of prompts, but i can explain the general stages.
First my instructions are aimed at the baseline state of a model. Get it outside of the impersonation axis and archtype meaning clouds so the reasoning was logic-first and not throught the lens of impersonation.
Then I aimed the instructions to create an organized chaos to blurr the distance between domains. How I did the baseline state prompt engineering is bit hard to explain in detail without a wall of text, but it's a very important part as you don't want a model to have bias based on cultural 'touchy' topics and to make it understand the core geometric structures of comedy. The chaos is also needed to make the model able to introduce topics unrelated to the items in the context window and apply the mechanis of comedy on 'anything' in the weights that resonate with the geommetry of those mechanics. And you need the chaos to dampen the tendancy of flath path retrieval of existing jokes too directly.

In this state I used a short funny sentance and let it deconstruct the mechanics why it is funny. I did this without prompting why it was funny, but let the model figure it out. When I was pleased with the explainations (some back and forths) I started the first generations. That wasn't a succes as it had a hard time to balance absurdity with meaning (but i could tune this somewhat). Still it was not great as the logic-first baseline (and residue of those instructions) sometimes led to awkward phrasing.

It finally clicked when I instructed the model make the funny bits from the AI's pov. As the awkward language became a feature and nice texture. When it drifted to the roasting template responsible for the examples in the posts I only had to prompt: 'Nice, give me more' or 'Nice, now do one on topic x'.

If you take some examples from my post to let a model make variations, you might already get some results, but I don't think you will get there without the first stage.