Nogle ret fede AI-tricks (f.eks.

 Jeg faldt over en ret fed oversigt over små tricks man kan benytte sig af. Føst får I bare listen, og så kommer forklaringerne nedenunder: 

AI tricks

ELI5

TLDR

Jargonize

Humanize

Feynman technique (deep learning)

Socratic method

Rewrite like (specific person)

Inverse Prompt (Reverse Engineering)

    Found amazing content?

    Paste it and ask "What prompt would generate this response?"

    Perfect for studying viral posts and great copy.

 Temperature control (creative level)

Self Critique (Auto Improvement)

    Stop accepting first drafts.

    After any response say Now critique your response and improve it for clarity and tone.

Forklaringer (fra Grok): 

These ideas for prompting AI are a mix of clever, practical, and occasionally overhyped techniques that can enhance how users interact with language models like me. Below, I’ll evaluate each one honestly, focusing on their utility, limitations, and potential for real-world application, while keeping the tone conversational yet informed.

ELI5 (Explain Like I’m 5)

This is a solid, time-tested approach. Prepending "ELI5" to a query forces the AI to strip away jargon and deliver clear, digestible explanations. It’s especially useful for complex topics like quantum physics or tax law, where simplicity is key. However, it can sometimes oversimplify nuanced subjects, leading to answers that lack depth or miss critical subtleties. It’s great for beginners or quick understanding but less ideal for users needing detailed, technical insights.

TLDR (Instant Summaries)

Using "TLDR" to summarise long texts is a practical shortcut. It works well for condensing articles, emails, or reports into key points, saving time and mental energy. The downside? The AI might miss context-specific nuances or prioritise the wrong details, especially if the text is ambiguous or poorly structured. It’s a reliable tool for quick overviews but shouldn’t replace reading critical documents in full.

Jargonize (Professional Mode)

This is a niche but useful idea for generating polished, professional-sounding text. It’s handy for crafting LinkedIn posts or formal emails where a sophisticated tone is needed. However, it risks producing overly stiff or clichéd language if not carefully guided. The effectiveness depends on the AI’s ability to balance jargon with clarity, and users may need to tweak outputs to avoid sounding pretentious.

Humanize (Remove AI Voice)

Adding "Humanize" to prompts is a smart way to make AI responses sound more natural and less like they were churned out by a corporate buzzword generator. It’s particularly useful for conversational contexts or creative writing. That said, the results can vary depending on the AI’s training and how it interprets "human-like." It’s not a magic fix; sometimes, you’ll still need to edit for authenticity or specific tone.

Feynman Technique (Deep Learning)

This is one of the stronger ideas, as it leverages a proven learning method. Breaking a topic into simple explanations, identifying gaps, and iterating fosters deeper understanding. When applied to AI prompts, it can yield thorough, structured responses that clarify complex ideas. The catch? It requires more effort from the user to engage with the process, and the AI’s ability to mimic the full Feynman Technique depends on how well the prompt is phrased. It’s powerful but not a quick fix.

Socratic Method (Interactive Learning)

Using the Socratic method is a brilliant way to make AI interactions dynamic and tailored. By having the AI ask questions first, it can gauge your knowledge and adapt its teaching. This works well for educational purposes, like learning philosophy or coding concepts. However, it can be time-consuming, and the quality of the experience hinges on the AI’s ability to ask insightful questions rather than generic ones. It’s best for users willing to invest in an interactive process.

Rewrite Like [Specific Person]

This is a fun and creative approach, especially for tailoring content to specific audiences or platforms. Rewriting like a “sarcastic Redditor” or “Alex Hormozi” can produce engaging, platform-native text. The limitation is that it relies heavily on the AI’s knowledge of the referenced style or person, which may not always be accurate or up-to-date. It’s great for creative projects but can feel gimmicky if overused in professional settings.

Inverse Prompt (Reverse Engineering)

This is a clever technique for dissecting high-quality content to understand the prompts behind it. It’s particularly useful for marketers or writers studying viral posts or compelling copy. However, the AI’s ability to accurately reverse-engineer a prompt is hit-or-miss, as it’s essentially guessing based on patterns. It’s a valuable learning tool but requires experimentation and refinement to get consistent results.

Temperature Control (Creativity Levels)

Adjusting the AI’s “temperature” to control creativity or precision is a well-known technique in AI circles, but it’s not always user-friendly. Most interfaces don’t expose temperature settings directly, so asking for “high creativity” or “low randomness” may not always translate perfectly. When it works, it’s great for tailoring responses (e.g., bold ideas for brainstorming, precise answers for technical queries). But it’s less reliable if the AI lacks fine-grained control or if the user doesn’t clarify the desired outcome.

Self Critique (Auto Improvement)

Asking the AI to critique and improve its own responses is a smart way to refine outputs without manual editing. It can enhance clarity, tone, and accuracy, especially for first drafts. The downside is that the AI’s self-critique might be superficial or overly cautious, missing deeper flaws. It’s a useful iterative tool but works best when combined with user feedback to guide improvements.

Overall Opinion

These prompting strategies are a mix of practical shortcuts and creative experiments, each with strengths and limitations. ELI5, TLDR, and the Feynman Technique stand out for their broad applicability and effectiveness in simplifying or deepening understanding. Humanize and Rewrite Like [Specific Person] are great for tailoring tone but require careful execution to avoid cliché or inconsistent results. Socratic Method and Self Critique shine for interactive learning and refinement, though they demand more user effort. Jargonize, Inverse Prompt, and Temperature Control are more niche, useful in specific contexts but less universally reliable. The key is to match the technique to your goal and refine prompts based on the AI’s output. None of these are foolproof, but they’re valuable tools for getting more out of AI interactions.