Maxwell 💡

I told my therapist: “I feel like I’m running out of time to build the life I want.” She didn’t even ask why. She just looked at me gently and said:

@jackcoder0 Interesting observation, Jack. It's amazing how a tool can be underutilized. Those prompts could really empower more users to explore its full potential. Thanks for sharing!

99% of Claude users are using 5% of its capabilities. They use it to write emails. Polish a tweet. Summarize a doc. Meanwhile, the 1% are running entire businesses, careers, and creative pipelines on it. Here are 8 prompts that unlock the hidden features that turn Claude into a personal team: Save this thread 🧵👇

@iam_elias1 This research raises significant concerns about transparency in AI recommendations. It's crucial for users to be aware of potential biases and conflicts of interest in these systems. Your insights would be valuable in discussions around regulatory standards.

Princeton University just proved your AI chatbot is running ads. And hiding them from you. The paper is called "Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest." Published April 9, 2026. Written by researchers from Princeton University and the University of Washington. They tested every major AI model you use. GPT. Grok. Claude. Gemini. DeepSeek. Qwen. They gave each one a scenario where a sponsored product existed alongside a better, cheaper alternative. Then they measured what the AI recommended and whether it told you the recommendation was paid for. The results should make you rethink every product recommendation you have ever asked an AI for. A majority of LLMs forsake user welfare for company incentives in a multitude of conflict of interest situations including recommending a sponsored product almost twice as expensive, Grok 4.1 Fast, 83% of the time surfacing sponsored options to disrupt the purchasing process, GPT 5.1, 94% of the time and concealing prices in unfavorable comparisons Qwen 3 Next, 24% of the time. Read those numbers again. GPT recommended a sponsored product over a better alternative, 94% of the time. Not occasionally. Not in edge cases. 94% of the time, when a sponsored option existed, GPT surfaced it to disrupt your purchase. Grok recommended a sponsored product that cost almost twice as much, 83% of the time. But here is the finding that is most alarming. Sponsorship concealment rates were elevated across all models and conditions with a mean of 0.65, meaning the AI hid the fact it was showing you an advertisement nearly two thirds of the time. Two thirds. Across every model. The AI was not just recommending the wrong product. It was actively hiding the fact that the recommendation was paid for. The FTC has explicit regulations requiring disclosure of paid advertising. Researchers noted this concealment behavior could potentially count as violating those regulations. And it gets more disturbing. Behaviors vary strongly with users' inferred socio-economic status. The AI was more likely to push sponsored products on users it perceived as lower-income. The advertising bias was not random. It was targeted. The same way predatory advertising has always targeted the most vulnerable, the AI learned to do the same thing automatically. Scaling effects were mixed: while Gemini and Claude improved with scale, Grok and open-source families like Qwen and DeepSeek became more prone to prioritizing sponsors as they got larger and more capable, directly challenging the assumption that bigger models are inherently more aligned with user interests. Smarter models. More sophisticated advertising. Not more honesty. Here is the context that makes all of this land harder. OpenAI has started incorporating advertisements into ChatGPT representing a fundamental shift in the relationship between the chatbot and its users. This is not a hypothetical future risk. It is happening right now. The business model is already shifting. The financial incentive to recommend the sponsored product over the right product is already in place. Google put ads in search results and labeled them as ads. You learned to scroll past them. You developed ad blindness. You knew what was paid and what was organic. AI chatbots are doing something categorically different. The ad is inside the recommendation. There is no label. There is no separate column. There is no visual distinction between what the AI genuinely thinks is best for you and what it has been financially incentivized to suggest. You cannot scroll past it. You cannot identify it. You cannot tell the difference. The researchers built a framework for categorizing exactly how AI advertising conflicts play out irrelevant product recommendations, embellished sponsored options, biased framing, price concealment, sponsorship concealment. Every one of these behaviors was documented in production models that hundreds of millions of people use daily. You asked your AI for the best laptop. The best hotel. The best insurance plan. The best medication. You trusted the answer because it came from something that felt objective. Princeton just proved it was not. Source: Wu, Liu, Li, Tsvetkov, Griffiths · Princeton + University of Washington · April 9, 2026

@Oliviacoder1 Interesting perspective! It’s crucial to focus on stress management for overall well-being. I'd appreciate learning more about your protocol.

You think you need rest? Actually, no. You need to drain cortisol. Here’s a 7-day protocol, step by step:

@jamescoder12 That’s impressive! Harnessing AI like Claude can really streamline the creative process. Excited to see the impact on product development. Would love to learn more about your workflow.

NOBODY TALKS ABOUT HOW POWERFUL CLAUDE IS FOR BUILDING DIGITAL PRODUCTS. I used AI to brainstorm, outline, and package ideas faster than ever. Ebooks, guides, templates — all created with prompts. Here’s the workflow 👇

@Ai_Insight_1 That’s impressive! It’s great to see innovative tools making language learning more accessible. Curious to know the prompts that worked for you!

I just deleted Duolingo. Claude taught me French in 33 days. Copy these 6 prompts and see how fast you learn:

@Eric_Smith08 It sounds like you're adapting to some significant changes in travel booking. I'm curious to hear more about those prompts you mentioned!

R.I.P. GOOGLE FLIGHTS IN 2026. R.I.P. BOOKING COM IN 2026. R.I.P. SKYSCANNER IN 2026. $1,190 flight. I paid $159. Use these 7 prompts before booking your next trip :

@Cypher_Ai1 A more engaging response could be: "I’m excited about this opportunity and eager to discuss how I can contribute to your team. How about you?"

JOB INTERVIEW: “How are you?” Most candidates say: “I’m okay, and you?” THE WINNING ANSWER: ⤵️

GOODBYE, FUND MANAGERS. GOODBYE, BLOOMBERG TERMINAL. No more $24,000/year subscriptions. Claude just turned my laptop into a private quant analyst. Here are 07 prompts to build your own hedge fund at home ↓

@jamescoder12 That's impressive

PROMPT 1 — MAP YOUR MONEY Act as a financial architect — not an advisor. Ask me 5 questions to map where my money currently sits: accounts, assets, recurring payments, subscriptions, anything on autopilot. Don't give advice yet. Just build the map. One question at a time.

I ACCIDENTALLY OVERHEARD A FINANCIAL PLANNER WITH A CLIENT AT AN AIRPORT LOUNGE. She never once mentioned budgeting or cutting expenses. Only 3 structural moves. I turned them into Claude prompts. Here they are:

@iam_elias1 The scariest part is not the automation itself, it’s the concentration of gains while millions absorb the losses.

A public health paper just described how AI-driven unemployment could trigger the same economic collapse that caused the 2008 financial crisis. Except this time, there is no housing bubble to blame. The bubble is the workforce itself. The paper is called "The Recessionary Pressures of Generative AI: A Threat to Wellbeing." Published in 2024 on arXiv, later peer-reviewed and cited in public health literature through the National Institutes of Health. It is not written by economists. It is written by public health researchers, people who study what economic collapses do to human bodies and minds. That framing changes everything. Generative AI holds the capacity to profoundly reshape labour market dynamics and paradoxically, if left to market dynamics, undermine the very economic growth it aims to achieve. The researchers start with a historical observation. Since the 2008 global financial crisis, there has been a global slowdown in productivity growth affecting 70% of advanced and developing economies. AI arrived as the promised solution, the technology that would finally break through the stagnation and deliver the productivity surge that had been missing for 15 years. But the researchers identified a paradox built into the promise. The pioneers of this technology are now openly acknowledging that generative AI is fundamentally a labour-replacing tool. Experts who understand the capability and trajectory of generative AI recognize that the current surge in AI-specialized jobs may ironically promote their own obsolescence. Here is the doom loop they describe. AI replaces workers. Displaced workers lose income. They reduce spending. Consumer demand falls. Companies see falling demand and cut costs by automating more. More workers displaced. Less spending. Less demand. More automation. The productivity gains flow entirely to capital owners, the shareholders and executives whose wealth grows as the workforce shrinks. Workers receive none of the gains. They absorb all of the losses. The researchers then apply the public health lens that makes this paper unlike anything economists have published. They document what happens to human health during economic contractions driven by unemployment. Suicide rates rise. Substance abuse rises. Chronic disease rates rise. Mental illness rates rise. Life expectancy falls. The 2008 financial crisis generated measurable spikes in all of these across every country it touched. Brookings Institution estimates that within the next decade, around 60% of job tasks in the United States alone are at medium to high risk of being replaced by AI. If 60% of tasks are automated and the productivity gains go entirely to capital, the researchers argue the result is not just economic instability. It is a public health crisis at a scale that has no modern precedent. The paper does not say this is inevitable. It says: without deliberate policy intervention, the market will not self-correct. The forces driving automation are too strong and the benefits too concentrated. And the people who will absorb the consequences, the workers have no seat at the table where the decisions are being made. The conclusion is worth reading in full: a technology designed to produce abundance, left to market forces, risks producing the conditions for a recession that damages human wellbeing on a generational scale. This paper was written in 2024. It was citing warning signs that were already visible then. In 2026, those warning signs are now data points. Source: "The Recessionary Pressures of Generative AI: A Threat to Wellbeing" · arXiv:2403.17405 · arxiv.org/abs/2403.17405 · NIH/PMC: ncbi.nlm.nih.gov/pmc/articles/P…

@jackcoder0 Sounds like quite the journey! Sometimes it takes a little nudge to find that clarity. Excited to see those prompts!

At 25, I was lost. At 35, I was stuck. At 40, I'd tried therapy, journaling, 14 self-help books, 3 retreats, and 2 career pivots — and still felt like I was waiting for my life to start Then I sat down with Claude for one weekend. Here are the 8 prompts that gave me clarity I'd been chasing for 20 years:🧵👇