naveegator.in

  • Being useful vs being valued

    A post from Better Than Random talking about how being useful and being valued are two different things.

    Being useful means that you are good at getting things done in a specific area, so that people above you can delegate that completely. You are reliable, efficient, maybe even indispensable in the short term. But you are seen primarily as a gap-filler, someone who delivers on tasks that have to be done but are not necessarily a core component of the company strategy. “Take care of that and don’t screw up” is your mission, and the fewer headaches you create for your leadership chain, the bigger the rewards.

    Being valued, on the other hand, means that you are brought into more conversations, not just to execute, but to help shape the direction. This comes with opportunities to grow and contribute in ways that are meaningful to you and the business.

    It took me a few years to truly grasp the difference. If you’re valued, you’ll likely see a clear path for advancement and development, you might get more strategic roles and involvement in key decisions. If you are just useful, your role might feel more stagnant.

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  • Six years as shareholder of Dabur

    There is really nothing for me to write about my investment in Dabur. Just like D Mart, the journey has been a painful one. The XIRR (Figure 1) has snaked around the 0% value on the X axis since last six years and as of today it stands at -4.2%. In contrast the Nifty Next 50—of which Dabur is part of—is at an impressive 19.1%. In fact, in the last six years Dabur has unperformed Nifty Next 50 for 5 years.

    Figure 1
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  • Binge bank

    Jeet Mehta talking about how to keep on publishing even when you have single digit readers. His last suggestion is something he calls it, binge bank.

    Your Binge Bank is the collection of content that your future fans will want to consume. It’s the rabbit hole of content they’ll go down. Your audience might not exist now, but when it does in the future (and you can bet it will), they’ll want to go back in time and see everything you’ve produced.

    This is why YouTubers with millions of followers have hundreds of thousands of views on their first few videos. Those videos didn’t get any views when they were first published. They were revisited after they became famous, by their most loyal fans.

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  • ChatGPT and students

    A rant by a professor posted on Reddit on his struggles with ChatGPT use among students.

    I actually get excited when I find typos and grammatical errors in their writing now.

    …

    My constant struggle is how to convince them that getting an education in the humanities is not about regurgitating ideas/knowledge that already exist. It’s about generating new knowledge, striving for creative insights, and having thoughts that haven’t been had before. I don’t want you to learn facts. I want you to think. To notice. To question. To reconsider. To challenge. Students don’t yet get that ChatGPT only rearranges preexisting ideas, whether they are accurate or not.

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  • Entrepreneurship

    Saw this on Hacker News. The discussion on it is also worth reading.

    Entrepreneurship is like one of those carnival games where you throw darts or something.

    Middle class kids can afford one throw. Most miss. A few hit the target and get a small prize. A very few hit the center bullseye and get a bigger prize. Rags to riches! The American Dream lives on.

    Rich kids can afford many throws. If they want to, they can try over and over and over again until they hit something and feel good about themselves. Some keep going until they hit the center bullseye, then they give speeches or write blog posts about “meritocracy” and the salutary effects of hard work.

    Poor kids aren’t visiting the carnival. They’re the ones working it.

    Life isn’t fair. But then, each one of us have our own unfair advantage. We just don’t compare our unfair advantage.

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  • Input risk in LLM

    Doug Slater talking about input risk when using LLM to code.

    An LLM does not challenge a prompt which is leading or whose assumptions are flawed or context is incomplete. Example: An engineer prompts, “Provide a thread-safe list implementation in C#” and receives 200 lines of flawless, correct code. It’s still the wrong answer, because the question should have been, “How can I make this code thread-safe?” and whose answer is “Use System.Collections.Concurrent” and 1 line of code. The LLM is not able to recognize an instance of the XY problem because it was not asked to.

    The post covers a lot more ground on the risks involved with LLM generated code. Another thing that caught my attention was:

    LLMs accelerates incompetence.

    Simon Willison talks about the other side when he says:

    LLMs amplify existing expertise

    The conclusion is: If you are smart, LLMs can make you—or at least make you sound—smarter. If you are dumb, LLMs will make you dumber, without you ever knowing.

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  • Addiction to… vibe coding

    Fred Benenson talking about how you can get addicted to vibe coding. Yes, vibe coding.

    I’ve been using AI coding assistants like Claude Code for a while now, and I’m here to say (with all due respect to people who have substance abuse issues), I may be an addict. And boy is this is an expensive habit.

    Its “almost there” quality — the feeling we’re just one prompt away from the perfect solution — is what makes it so addicting. Vibe coding operates on the principle of variable-ratio reinforcement, a powerful form of operant conditioning where rewards come unpredictably. Unlike fixed rewards, this intermittent success pattern (“the code works! it’s brilliant! it just broke! wtf!”), triggers stronger dopamine responses in our brain’s reward pathways, similar to gambling behaviors.

    What makes this especially effective with AI is the minimal effort required for potentially significant rewards — creating what neuroscientists call an “effort discounting” advantage. Combined with our innate completion bias — the drive to finish tasks we’ve started — this creates a compelling psychological loop that keeps us prompting.

    However, the post is less about addiction and more about the perverse incentives that AI companies have for verbose code generation.

    1. The AI generates verbose, procedural code for a given task
    2. This code becomes part of the context when you ask for further changes or additions (this is key)
    3. The AI now has to read (and you pay for) this verbose code in every subsequent interaction
    4. More tokens processed = more revenue for the company behind the AI
    5. The LLM developers have no incentive to “fix” the verbose code problem because doing so will meaningfully impact their bottom line

    Don’t miss to read the chuckle inducing postscript.

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  • Thinking

    Dustin Curtis talking about how AI is impacting his—and possibly others—thinking.

    I thought I was using AI in an incredibly positive and healthy way, as a bicycle for my mind and a way to vastly increase my thinking capacity. But LLMs are insidious–using them to explore ideas feels like work, but it’s not real work. Developing a prompt is like scrolling Netflix, and reading the output is like watching a TV show. Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

    The Netflix analogy hit hard.

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  • Text in PDF

    From PDF to Text, a challenging problem by Marginalia.

    Extracting text information from PDFs is a significantly bigger challenge than it might seem. The crux of the problem is that the file format isn’t a text format at all, but a graphical format.

    It doesn’t have text in the way you might think of it, but more of a mapping of glyphs to coordinates on “paper”. These glyphs may be rotated, overlap, and appear out of order, with very little semantic information attached to them.

    You should probably be in awe at the fact that you can open a PDF file in your favorite viewer (or browser), hit ctrl+f, and search for text.

    Today I learned, text in PDF is just mapping of glyphs to coordinates on “paper”.

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  • Happiness and politeness

    Shani Zhang sharing 21 observations from observing people. My favourite:

    It is easy to tell how happy someone is to see another person enter a conversation. There is happy, and there is polite, and they look very different. Polite has a mechanical quality to it, like carrying out all the right movements to replace batteries in a remote. Happy has a boundless quality: unpredictable, even when it is at a low level. There is an openness, allowing another person to surprise and delight them. The easiest way to say this: there is no script for happy. It tumbles out of the body. Polite comes from the mind –it is restrained and calculated – measured lines and pauses. There are reinforcing loops in a polite person and a happy person. A person closed to the possibility of delight finds less of it. A person open to it finds more.

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