naveegator.in

  • 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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  • Shallowness of LLMs

    Jason Cohen talking about how LLMs, in their knowledge, are wider but shallower than humans.

    It’s interesting how LLMs are wider than any human, but shallower than the best humans. (At many things; not, e.g. chess)

    It can’t do customer service as well as the best humans, but it can do it in 100 languages, which no human can.

    It can’t program as well as the best humans, but it can program in 100 languages and 1000 libraries, which no human can.

    It’s not as good at math or law or medicine or research or history as the best humans in each of those fields, but it is better than the median human in those fields.

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  • Visual Basic 6

    I read an insightful article by Ryan Lucas on the history and legacy of Visual Basic. This article links to another chuckle worthy article by David Platt—written way back in 2012—on why Visual Basic 6 still thrives. Excerpt below.

    A student of mine named Eric once joked that Visual Basic 6 was “the un-killable cockroach” in the Windows ecosystem. That analogy goes deeper than you might think. Cockroaches are successful because they’re simple. They do what they need to do for their ecological niche and no more. Visual Basic 6 did what its creators intended for its market niche: enable very rapid development of limited programs by programmers of lesser experience. It was never meant for heavy-duty coders developing complex applications.

    Visual Basic 6 accomplished its goals by abstracting away the complexity of the underlying Windows OS. Simple things were very simple to accomplish. On the other hand, complex things, such as dealing with threads, were impossible. My rule of thumb for Visual Basic 6 was: if I couldn’t do it within 10 minutes, I couldn’t do it at all.

    …

    Almost all Visual Basic 6 programmers were content with what Visual Basic 6 did. They were happy to be bus drivers: to leave the office at 5 p.m. (or 4:30 p.m. on a really nice day) instead of working until midnight; to play with their families on weekends instead of trudging back to the office; to sleep with their spouses instead of pulling another coding all-nighter and eating cold pizza for breakfast. They didn’t lament the lack of operator overloading or polymorphism in Visual Basic 6, so they didn’t say much.

    The voices that Microsoft heard, however, came from the 3 percent of Visual Basic 6 bus drivers who actively wished to become fighter pilots. These guys took the time to attend conferences, to post questions on CompuServe forums, to respond to articles. Not content to merely fantasize about shooting a Sidewinder missile up the tailpipe of the car that had just cut them off in traffic, they demanded that Microsoft install afterburners on their busses, along with missiles, countermeasures and a head-up display. And Microsoft did.

    But giving Visual Basic .NET to the Visual Basic 6 community was like raising a coyote as a domestic dog, then releasing him into the woods, shouting, “Hunt for your dinner as God intended, you magnificent, wild creature!” Most of them said, “Heck with that. I’m staying on my nice warm cushion by the fire while you open me a can of Alpo.” And Visual Basic 6 kept right on going.

    Ryan Lucas then goes on to argue that because Microsoft made it very difficult—if not impossible—to move from Visual Basic 6 to VB.NET, it ended up costing Microsoft the battle for web.

    Microsoft had broken the trust of its army of Visual Basic developers. Faced with the options of either starting over from scratch in VB.NET or moving to new web-native languages like JavaScript and PHP, most developers chose the latter—a brutal unforced error by Microsoft. (It’s easy to forget the pole position that Microsoft had on the web in 2001: Internet Explorer had 96% market share, and Visual Basic apps could even be embedded into web pages via ActiveX controls.)

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