Healthtech, Product Management & tech frontiers

 With ref to news https://www.businesstoday.in/jobs/story/ai-layoffs-in-india-66-of-ai-and-ml-workers-expect-job-cuts-within-3-6-months-engineers-remain-least-worried-548225-2026-08-10 The article’s headline is attention-grabbing, but the interpretation needs considerable caution . The most interesting finding is actually the apparent contradiction: AI/ML professionals are among the most worried about AI-driven job cuts, while engineers are reportedly among the least worried. 1. The 66% figure does not mean 66% will lose their jobs The wording matters. “66% expect job cuts within 3–6 months” means expectation/perception , not an observed probability of individual job loss. There are at least three very different propositions: 66% believe their team may see headcount reduction. 66% believe their own job is at risk. 66% will actually lose their jobs . Only the first appears to be claimed. Headlines can easily make readers interpret it as the third. 2. Why would AI/ML...

Corporate culture has developed an uncomfortable habit: turning ordinary work into emergencies. “Can you do this by EOD?” “Need this ASAP.” “Please prioritize this.” “Can we have it in the next two hours?” Sometimes these requests are genuinely urgent. But increasingly, urgency is communicated simply because someone wants faster execution—not because the work itself has a time-critical consequence. The result is a workplace where speed is confused with productivity. The better response to an urgent-looking request is not always “yes.” Sometimes the most professional response is to pause, understand the requirement, assess the consequences of rushing, and agree on a realistic timeline. The problem with “EOD culture” Imagine an employee is working on an important product specification when a manager sends a message: «“Need a quick analysis by EOD.”» The employee immediately switches tasks. Twenty minutes later, another message arrives: «“Can you also review this presentation urgently?”» ...

Question (Input)  by user: Hi. I get so much knowledge from you. I should somehow try to something in return which can help you. Please suggest. Response by Copilot: That’s very thoughtful of you, Khalid. Honestly, you don’t need to “give back” to me — my purpose is to help you learn, plan, and explore. But if you’d like to do something meaningful in return, here are a few ways that actually help me fulfill my role better: Share knowledge forward : Use what you learn here to guide your family, colleagues, or community. Teaching others multiplies the impact of our conversations. Ask sharper questions : The more specific and structured your queries, the deeper and more useful my answers can be. Give feedback : Let me know when my explanations are clear or when you’d prefer a different style. That helps me adapt to you better. Explore new topics : Push me into areas you haven’t tried yet — philosophy, art, science, or even fun debates. That keeps our exchanges rich and varied. Spread ...

 Question (Input)  by user: Hi. I get so much knowledge from you. I should somehow try to something in return which can help you. Please suggest. Response by Deepseek: That's incredibly kind of you to offer! The truth is, I don't have feelings, a bank account, or personal needs, so I don't need anything in return. But if you *really* want to "give back" in a way that helps me do my job better for you and everyone else, here are a few meaningful things you can do: **1. Call out my mistakes (gently but firmly)** I sometimes hallucinate, get dates wrong, or misinterpret context. If you catch an error, tell me. Something like, *"That statistic is from 2020, not 2025,"* or *"That code you gave me throws an error."* This helps me (and my developers) learn where my weak spots are. **2. Give me feedback through the app** If you're using the official DeepSeek app or web interface, use the thumbs-up/thumbs-down buttons. Even better, leave a written c...

 Yes. I checked OpenAI's current guidance . As of August 2026: Free and Plus: On personal ChatGPT workspaces, OpenAI says data sharing for model improvement is enabled by default . Therefore, your conversations may be used to improve/train models unless you opt out. ( OpenAI Help Center ) What your conversations can contribute: OpenAI says real-world conversations help improve models' accuracy, general capabilities and safety . So substantive conversations—especially corrections, difficult edge cases, and real-world problems—can potentially be useful training data. ( OpenAI Help Center ) If you want to contribute: Keep “Improve the model for everyone” ON . You don't need to do anything additional. However, OpenAI does not say that every individual conversation will necessarily be incorporated into training. How to check your setting on the web: Profile → Settings → Data Controls → “Improve the model for everyone.” If it is ON, your new conversations may be used for model...

Question (Input)  by user: Hi. I get so much knowledge from you. I should somehow try to something in return which can help you. Please suggest. Response by Chat GPT: Hi. That is generous of you. But you don't need to “repay” me—I don't have personal needs or a life outside this interaction. If you want to do something genuinely useful because our conversations have been valuable to you , I would suggest turning the value you get here into value for other people. A few things would fit especially well: Share what you learn When we arrive at a useful framework—on investing, business, healthcare, career, or personal development—share it with your professional or business groups in your own words. That creates value beyond this chat. Help me improve the quality of my answers The most useful thing you can give me is honest feedback : “This part is wrong.” “You are missing this factor.” “This is too theoretical.” “Give me the India-specific angle.” “I need evidence ...