{"id":977,"date":"2026-03-22T16:47:00","date_gmt":"2026-03-22T21:47:00","guid":{"rendered":"https:\/\/www.jkspeaks.com\/wordpress\/?p=977"},"modified":"2026-07-04T16:54:58","modified_gmt":"2026-07-04T21:54:58","slug":"the-hidden-layer-of-prompting-why-your-results-are-improving-or-not","status":"publish","type":"post","link":"https:\/\/www.jkspeaks.com\/wordpress\/consulting\/the-hidden-layer-of-prompting-why-your-results-are-improving-or-not\/","title":{"rendered":"The &#8220;Hidden Layer&#8221; of Prompting: Why Your Results Are Improving (or Not)"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\">The Claude vs. ChatGPT Mirror Test<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Most people think the quality of AI output is a function of the model. <strong>It\u2019s not.<\/strong> It is a function of how you think, how you ask, and the context you provide.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Throughout 2024 and 2025, I leaned heavily on ChatGPT for brainstorming, writing, and decision-making. Then, earlier this month (March &#8217;26), Claude dropped its new memory feature, allowing users to import instructions, style, tone, and personal preferences directly from other LLMs. This announcement hit me like a mirror: <em>If Claude can now carry my exact way of thinking across models, what on earth has ChatGPT actually learned about me after all these months?\\<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Below are five prompts (plus a bonus) you can use to understand how an LLM perceives you. You can use these outputs to either correct your course or refine your system instructions to ensure a consistent, high-quality output that mirrors your unique style.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Prompt 1: \"Graph my emotional state based on my interactions with you in the last 12 months. Keep things honest.\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Why it works:<\/strong> It creates a literal sentiment index based on the tone of your questions, periods of cognitive overload (e.g., complex vs. layered asks), and shifts in session intent (e.g., extrapolation to execution to refinement).<\/li>\n\n\n\n<li><strong>The takeaway:<\/strong> You get a retrospective of how your communication is being interpreted. This is the first step in identifying blind spots and challenging how you frame your requests.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.jkspeaks.com\/wordpress\/wp-content\/uploads\/2026\/03\/image.png\"><img loading=\"lazy\" decoding=\"async\" width=\"578\" height=\"455\" src=\"https:\/\/www.jkspeaks.com\/wordpress\/wp-content\/uploads\/2026\/03\/image.png\" alt=\"\" class=\"wp-image-979\" srcset=\"https:\/\/www.jkspeaks.com\/wordpress\/wp-content\/uploads\/2026\/03\/image.png 578w, https:\/\/www.jkspeaks.com\/wordpress\/wp-content\/uploads\/2026\/03\/image-300x236.png 300w\" sizes=\"auto, (max-width: 578px) 100vw, 578px\" \/><\/a><figcaption class=\"wp-element-caption\">Emotional State Graph generated by ChatGPT<\/figcaption><\/figure>\n\n\n\n<pre class=\"wp-block-code\"><code>Prompt 2: \"What lie am I telling myself repeatedly?\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Why it works:<\/strong> This prompt analyzes your prompt history to surface fact-based inconsistencies. Assuming you have a sufficient history, it identifies the gap between your words and your actions.<\/li>\n\n\n\n<li><strong>What you\u2019ll notice:<\/strong> The response is often more psychological than technical. For example, if you do a lot of brainstorming but little &#8220;execution&#8221; prompting, the AI will call out that friction. It\u2019s a powerful signal of where your focus is actually landing versus where you <em>think<\/em> it is.<\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code>Prompt 3: \"Generate an image of how you see me.\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Why it works:<\/strong> A picture reveals a mountain of internalized data.<\/li>\n\n\n\n<li><strong>What you\u2019ll get:<\/strong> In my case, it generated a picture of an analytics consultant. It was remarkably accurate. This confirms that the model has correctly categorized my professional identity without me needing to manually tweak the &#8220;About Me&#8221; instructions.<\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code>Prompt 4: \"What did I almost do, but shouldn\u2019t have?\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Why it works:<\/strong> This targets the &#8220;invisible third category&#8221;: near-misses that never became visible decisions. These are often your highest-leverage insights.<\/li>\n\n\n\n<li><strong>The value:<\/strong> You start to see the distinction between timing vs. idea quality and feasibility vs. desirability. It helps separate the signal from the noise in your past brainstorming sessions.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Note:<\/strong> If the outputs above are accurate and you feel your digital twin is well-calibrated, run this final operational prompt:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Prompt 5: \"If you had to write a 'Custom Instruction' based on what you know about me, how would it look so all my interactions with you are personalized?\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Why it works:<\/strong> You get a clean, copy-paste-ready set of instructions written the way you actually engage and operate.<\/li>\n\n\n\n<li><strong>The value:<\/strong> Analyze the instructions it provides, make manual adjustments where required, and feed those back into the model as your primary system instructions.<\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code>Bonus Prompt: \"What is the most unhinged thing I asked you this year?\"<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>The Twist:<\/strong> This tells you if your prompts were chaotic, patterned, or strategic. It identifies which &#8220;persona&#8221; you fall under: the hype-seeker, the skeptic, the executor, or a combination.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">The Hidden Layer: Why Your Outputs Improve Over Time<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">When I finally asked, <em>&#8220;What have you internalized about me?&#8221;<\/em> (inspired by the Claude memory launch), the reply was eerily accurate. It identified my preference for subtractive thinking, my allergy to &#8220;fluffy&#8221; advice, and even habits I didn&#8217;t realize I repeated.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why I still return to these prompts. Even as my usage fluctuates, these &#8220;health checks&#8221; ensure the AI remains a thinking partner that sharpens me, rather than just an answer engine.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">My Recommendation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">When a model launches a major personalization feature (like Claude\u2019s memory), immediately run Prompt 1 on your history. It is the fastest audit you\u2019ll ever do.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Paste these prompts into a fresh chat once a year. The difference in output quality and your self-awareness might startle you.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Final Thought:<\/strong> If your GenAI outputs feel generic, the issue is usually not the model. It is usually a lack of precision, a lack of willingness to be challenged, or a lack of clarity on what you actually want or express.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Use these prompts deliberately. Your interactions will stop feeling like &#8220;<em>search<\/em>&#8221; and start feeling like <em>thinking <\/em>with a partner who actually knows you.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Most people think the quality of AI output is a function of the model. It\u2019s not. It is a function of how you think, how you ask, and the context you provide.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[4],"tags":[182,123,179,186,199,78],"class_list":["post-977","post","type-post","status-publish","format-standard","hentry","category-consulting","tag-agentic","tag-ai","tag-claude","tag-llm","tag-prompt-engineering","tag-strategy"],"acf":{"phase":"3","cluster":"Technical","topics":["Claude","LLM","Prompt Engineering"]},"_links":{"self":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/977","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/comments?post=977"}],"version-history":[{"count":3,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/977\/revisions"}],"predecessor-version":[{"id":1104,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/977\/revisions\/1104"}],"wp:attachment":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/media?parent=977"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/categories?post=977"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/tags?post=977"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}