• Pretending

    The Oatmeal talking about AI art.

    As a kid, I had one of those little Casio keyboards where you could hit a button and it’d automatically play a song.

    I remember hitting the button.

    I remember standing there, pretending to make music.

    That’s how I see Al art.

    Standing there.

    Pretending.

    Pretending. This resonated with me. At times I have had this feeling whenever I used AI. While generating proposals. While generating code. While generating ideas. It seems I am pretending to work.

    So is the future of work that we all pretend to work?

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  • Pride in the little jobs

    Ted Lamade writing about taking whatever chances that you get, especially the insignificant ones. He then shares below quote by William McRaven from his book ‘The Wisdom of the Bullfrog’.

    I found in my career that if you take pride in the little jobs, people will think you worthy of the bigger jobs

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  • Hazardous state + environmental conditions = accident

    This comment by kqr on the news that Ryanair flight landed at Manchester airport with just six minutes of fuel left.

    In safety-critical systems, we distinguish between accidents (actual loss, e.g. lives, equipment, etc.) and hazardous states. The equation is

    hazardous state + environmental conditions = accident

    Since we can only control the system, and not its environment, we focus on preventing hazardous states, rather than accidents. If we can keep the system out of all hazardous states, we also avoid accidents. (Trying to prevent accidents while not paying attention to hazardous states amounts to relying on the environment always being on our side, and is bound to fail eventually.)

    One such hazardous state we have defined in aviation is “less than N minutes of fuel remaining when landing”. If an aircraft lands with less than N minutes of fuel on board, it would only have taken bad environmental conditions to make it crash, rather than land. Thus we design commercial aviation so that planes always have N minutes of fuel remaining when landing. If they don’t, that’s a big deal: they’ve entered a hazardous state, and we never want to see that. (I don’t remember if N is 30 or 45 or 60 but somewhere in that region.)

    For another example, one of my children loves playing around cliffs and rocks. Initially he was very keen on promising me that he wouldn’t fall down. I explained the difference between accidents and hazardous states to him in childrens’ terms, and he realised slowly that he cannot control whether or not he has an accident, so it’s a bad idea to promise me that he won’t have an accident. What he can control is whether or not bad environmental conditions lead to an accident, and he does that by keeping out of hazardous states. In this case, the hazardous state would be standing less than a child-height within a ledge when there is nobody below ready to catch. He can promise me to avoid that, and that satisfies me a lot more than a promise to not fall.

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  • It’s much easier to fund a promise than a real business

    Om Malik’s interview with Rodney Brooks.

    Om: It’s much easier to fund the promise than a real business, because real businesses have limitations on how fast they can grow. Whereas if you don’t know, you can live (and fund) the dream. There’s nothing wrong with living the dream—that’s how you get to fund crazy things in this industry. But people doing more rational things do pay the price.

    You’ve been in robotics for a long time. There are misconceptions about robots and robotics. The biggest fallacy is that we think of them in human form. Ten years later, that idea of a humanoid has become so pervasive. We don’t think about things that do robotic tasks, like ad systems that serve ads constantly—they are also robots.

    Rodney: The robots—they’re not embodied. I always say about a physical robot, the physical appearance makes a promise about what it can do. The Roomba was this little disc on the floor. It didn’t promise much—you saw it and thought, that’s not going to clean the windows. But you can imagine it cleaning the floor. But the human form sort of promises it can do anything a human can. And that’s why it’s so attractive to people—it’s selling a promise that is amazing.

    Om’s statement highlights the current state of AI. Everybody is funding the dream.

    Rodney’s statement highlights the business idea which actually needs funding but isn’t getting one.

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  • Politics

    Matheus Lima explaining politics at workplace.

    Politics is just how humans coordinate in groups. It’s the invisible network of relationships, influence, and informal power that exists in every organization. You can refuse to participate, but that doesn’t make it go away. It just means decisions get made without you.

    Think about the last time a terrible technical decision got pushed through at your company. Maybe it was adopting some overcomplicated architecture, or choosing a vendor that everyone knew was wrong, or killing a project that was actually working. I bet if you dig into what happened, you’ll find it wasn’t because the decision-makers were stupid. It’s because the people with the right information weren’t in the room. They “didn’t do politics.”

    Meanwhile, someone who understood how influence works was in that room, making their case, building coalitions, showing they’d done their homework. And their idea won. Not because it was better, but because they showed up to play while everyone else was “too pure” for politics.

    Ideas don’t speak. People do. And the people who understand how to navigate organizational dynamics, build relationships, and yes, play politics? Their ideas get heard.

    When you build strong relationships across teams, understand what motivates different stakeholders, and know how to build consensus, you’re doing politics. When you take time to explain your technical decisions to non-technical stakeholders in language they understand, that’s politics. When you grab coffee with someone from another team to understand their challenges, that’s politics too.

    Good politics is just being strategic about relationships and influence in the service of good outcomes.

    I too thought of politics at workplace is something to be avoided. But politics doesn’t meaning backstabbing your opponent. As per Wikipedia it means:

    Politics is the set of activities that are associated with making decisions in groups, or other forms of power relations among individuals, such as the distribution of status or resources.

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  • Friction vs effort

    Jameel Ur Rahman shares his take on how overcoming friction leads to growth. We have seen this in nature where the struggle of butterfly to come out of its cocoon helps develop its wings. But this comment by gwd makes a distinction between friction and effort.

    Can I make a distinction between “friction” and “effort”?

    If you’re riding a bike up a hill, you can’t go up without effort. But not all of your effort is actually moving you up the hill — some of it is being lost in friction: inefficiencies in your muscles, friction in your gears and wheel and chain, wind resistance.

    Similarly, you can’t learn anything without effort; but it’s often the case that effort you put in ends up wasted: if you’re learning a language, time spent looking for content rather than studying content is friction; effort spent forcing yourself to read something that’s too hard is effort you could have spent more profitably elsewhere.

    Put that way, we should minimize friction, so that we can maximize the amount our effort goes towards actually growing.

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  • A market for lemons

    Frank Chimero referring to the paper by George Akerlof and explaining what a market for lemons means. He then goes ahead and explains that we are in the lemon stage of the internet.

    The idea is called “a market for lemons.” The phrase comes from a 1970 paper by George Akerlof that explains how information asymmetry between buyers and sellers can undermine a marketplace. Akerlof asks us to imagine ourselves buying a used car. Some cars on the lot are reliable, well-maintained gems. Others cars are lemons, the kinds of cars that can make it off the lot but are disasters waiting to happen. The sellers know which cars are which, but you, as a buyer, can’t tell the difference. That information asymmetry affects the average price in the market and eventually impacts the overall market dynamics.

    The thinking goes like this: if a buyer can’t distinguish between good and bad, everything gets priced somewhere in the middle. If you’re selling junk, this is fantastic news—you’ll probably get paid more than your lemon is worth. If you’re selling a quality used car, this price is insultingly low. As a result, people with good cars leave the market to sell their stuff elsewhere, which pushes the overall quality and price down even further, until eventually all that’s left on the market are lemons.

    I think we’re in the lemon stage of the internet.

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  • From AI will replace humans to AI is in a bubble

    Stephanie Palazzolo writing for The Information.

    Not only has the one-year-old Thinking Machines not yet released a product, it hasn’t talked publicly about what that product will be. Even some of the company’s investors don’t have a very good idea of what it is working on. While raising capital for Thinking Machines earlier this year and late last year, Murati shared few details about what it would be building, prospective investors said.

    “It was the most absurd pitch meeting,” one investor who met with Murati said. “She was like, ‘So we’re doing an AI company with the best AI people, but we can’t answer any questions.’”

    Despite that vagueness, Murati raised $2 billion in funding—the largest seed round ever—at a $10 billion pre-investment valuation from top Silicon Valley VC firms including Andreessen Horowitz, Accel and GV. The investors also made the highly unusual decision to give her total veto power over the board of directors. (Thinking Machines is using Nvidia-powered servers it rents from Google Cloud, whose ultimate parent Alphabet also oversees GV.)

    When 2025 started all I could read was AI is going to replace humans. Now its all about—AI is in a bubble. These valuations don’t make sense.

    I don’t know what to believe anymore. But I am bookmarking this in case the bubble explodes in the future.

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  • Comprehension debt

    Jason Gorman explaing the challenge of comprehension debt with AI generated code.

    When teams produce code faster than they can understand it, it creates what I’ve been calling “comprehension debt”. If the software gets used, then the odds are high that at some point that generated code will need to change. The “A.I.” boosters will say “We can just get the tool to do that”. And that might work maybe 70% of the time. 

    But those of us who’ve experimented a lot with using LLMs for code generation and modification know that there will be times when the tool just won’t be able to do it. 

    “Doom loops”, when we go round and round in circles trying to get an LLM, or a bunch of different LLMs, to fix a problem that it just doesn’t seem to be able to, are an everyday experience using this technology. Anyone claiming it doesn’t happen to them has either been extremely lucky, or is fibbing.

    It’s pretty much guaranteed that there will be many times when we have to edit the code ourselves. The “comprehension debt” is the extra time it’s going to take us to understand it first.

    And we’re sitting on a rapidly growing mountain of it.

    On a very similar note, Steve Krouse explains how vibe code is legacy code because nobody understands it.

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  • Who can build the product?

    There’s an interesting discussion on Hacker News about the news that Boeing has started working on a 737 MAX replacement. My favorite comments.

    Comment by scrlk.

    an oil industry proverb: a healthy oil company has a geologist in charge, a mature one has an engineer in charge, a declining one has an accountant in charge, and a dying one has a lawyer in charge.

    Comment by nostrademons.

    It’ll be interesting to see if they still can design and build a new ground-up airplane design. The last all-new design was the 787, initiated in 2003 and launched in 2009, and its design was fraught with problems. Before then was the 777 in the early 90s (pre-McDonnell takeover), and the 757/767 in the early 80s.

    There’s a phenomena that ofter occurs with large organizations where once their markets mature, everybody who can build a product end-to-end leaves or gets forced out, leaving only people with highly specialized maintenance skillsets. The former group has no work to do, after all, so why should the company keep them around? But then if the market ecosystem shifts, and a new product is necessary, they no longer have the capacity to build ground-up new products. All those people have left, and won’t come anywhere near the company.

    Steve Jobs spoke eloquently about this phenomena in an old interview:

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