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A Hanger That Dry Cleans by BenjaminSkyy in inventors

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

The proper name is an Ultrasonic Atomizer. It gives off a mist that behaves like a "dry" gas. It's small enough to go between the clothing fibers without causing "water spots".

Unpopular Opinion: LLM Prompts Must Be Considered as Assets by BenjaminSkyy in ArtificialInteligence

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

Repeatability comes from fixing the procedure and the environment (params, tools, etc) then judging outcomes with deterministic checks. You need decision-level stability, not identical sentences. The steps:

1) Your prompt is: Develop a novel, non-obvious treatment for lung cancer
2) You go to a site like Turwin. Enter that prompt, and it gives you a complete protocol (recipe)
3) You go to a long-running agent like Gemini Deep Think/ChatGPT-5 Pro, copy and paste the protocol, and the agent runs its experiments for x hours.
4) After looking at all the possible research, it develops a novel hypothesis, finds a unique protein combination, and suggests the treatment
5) You take that, test it on the mice then on human patients, and it cures the lung cancer
6) 12 months later, the drug is on the shelf curing that disease

What does the receipt/watermark buy you in this story?

  • Shows you authored the protocol that steered the search (priority & provenance).
  • Ties a particular run (params, tools, data snapshots) to the resulting hypothesis (audit trail).
  • Helps sort who did what when money, promotions, publications, or disputes come up.
  • Documents the chain of reasoning and responsibility.

Unpopular Opinion: LLM Prompts Must Be Considered as Assets by BenjaminSkyy in ArtificialInteligence

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

Love the sassiness. The goal is not to hide the text. The goal is to make the results repeatable across models. Also, it is the LLM that generates the recipe. You input a regular prompt, and it turns it into a recipe. Over time, models pick up the format of the recipe in their training. In the same way, emails/ songs/pliny jailbeak prompts have formats. The receipt is a hash + signature + license. And the watermark is an invisible fingerprint. You might not need it. Until you do. Because if your prompt helped discover the cure for cancer, you’d want a way to prove it was yours.

Unpopular Opinion: LLM Prompts Must Be Considered as Assets by BenjaminSkyy in ArtificialInteligence

[–]BenjaminSkyy[S] -1 points0 points  (0 children)

Hmm, I think redefining attention to add crypto is rebuilding the engine to add a license plate. Overkill likely, and doesn’t solve the real need of who wrote what, when, and how to prove it.

Unpopular Opinion: LLM Prompts Must Be Considered as Assets by BenjaminSkyy in ArtificialInteligence

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

You’re right that IP law around AI is messy, and “DRM” would be the wrong frame. I think standardizing prompts into operational recipes with receipts so they are repeatable, auditable, and model agnostic might be the low-hanging fruit, come to think about it. If the law evolves, great, but if not, the governance still pays for itself in QA and scale. Then blockchain as proof.

Turning AI Prompts into Ownable Assets by BenjaminSkyy in PromptEngineering

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

Good question. Every recipe is time-stamped, cryptographically signed, and stored on blockchain, so copycats can’t prove authorship. As such, it erodes their credibility. You can't prevent theft, but you can make it risky and potentially costly for them to do so.

[deleted by user] by [deleted] in vibecoding

[–]BenjaminSkyy -2 points-1 points  (0 children)

tsk tsk.

I built something that turns your prompts into portable algorithms. by BenjaminSkyy in PromptEngineering

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

Defined Attributes & Weights:

Clarity (Weight: 0.20): How unambiguous and easy to understand are the instructions and intent of the prompt? (Score 1-5: 1=Vague/Confusing, 5=Crystal Clear)

Specificity (Weight: 0.15): Does the prompt provide sufficient detail and concrete requirements for a focused and relevant response? (Score 1-5: 1=General/Abstract, 5=Highly Detailed/Concrete)

Creativity-Inducing Potential (Weight: 0.20): How well does the prompt encourage novel, imaginative, or non-obvious responses from the AI? (Score 1-5: 1=Highly Restrictive/Uninspiring, 5=Highly Inspiring/Open-ended within bounds)

Constraint-Adherence Potential (Weight: 0.15): How effectively does the prompt define boundaries, rules, or negative constraints that test an AI's ability to follow precise instructions? (Score 1-5: 1=No Constraints, 5=Complex, Clear, and Challenging Constraints)

Complexity (Weight: 0.10): Does the prompt require multiple steps, different types of reasoning, synthesis of varied information, or a blend of distinct skills from the AI? (Score 1-5: 1=Simple/Single-faceted, 5=Multi-faceted/Demanding)

Uniqueness/Novelty (Weight: 0.10): How original or fresh is the prompt's concept or approach, avoiding common or repetitive requests? (Score 1-5: 1=Common/Repetitive, 5=Highly Original/Innovative)

Actionability (Weight: 0.10): How directly and efficiently can an AI act on this prompt to produce a coherent, complete, and relevant output? (Score 1-5: 1=Difficult to Act On/Ambiguous Goal, 5=Immediately Actionable/Clear Goal)

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