• Morvec’s paradox

    From Wikipedia:

    Moravec’s paradox is the observation that, as Hans Moravec wrote in 1988, “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”. This counterintuitive pattern may happen because skills that appear effortless to humans, such as recognizing faces or walking, required millions of years of evolution to develop, while abstract reasoning abilities like mathematics are evolutionarily recent.

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  • Values over data

    Jim Nielsen arguing that values should drive decision making, not data:

    Data tells you what people consume, not what you should make. Values, ethics, vision, those can help you with the “should”.

    “What is happening?” and “What should happen?” are two completely different questions and should be dealt with as such.

    The more powerful our ability to understand demand, the more important our responsibility to decide whether to respond to it. We can choose not to build something, even though the data suggests we should. We can say no to the data. 

    Data can tell you what people clicked on, even help you predict what people will click on, but you get to decide what you will profit from.

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  • Transparent umbrella

    Jampa Uchoa sharing the learnings from being an engineering manager for a decade. The metaphor of ‘transparent umbrella’ struck a chord with me.

    A good manager is more like a transparent umbrella. They protect the team from unnecessary stress and pressure, but don’t hide reality from them.

    Telling the team: “Our users aren’t thrilled so far. We need to find ways to better serve them. The project risks cancellation if we don’t.” That’s fair game. They deserve to know.

    When you do deliver hard news, state it clearly and focus on how the team will do about it. If you act scared, they’ll be scared too. Your goal is to get them thinking about the next steps.

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  • Posture

    There’s a GitHub project called posturr that blurs your screen when you slouch. This comment on Hacker News by avalys explains the inverse relationship between a developer’s posture and their productivity.

    You can measure my productivity by how slouched I am.

    Sitting up straight at my desk, chair locked, perfect posture? I’m doing nothing, maybe looking through System Preferences to change the system highlight color.

    Sliding down in my chair like jelly, with my shoulders where my butt should be and my head resting on the lumbar support? I’m building the next iPhone and it’ll be done by 2 AM.

    Ha!

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  • Principled and pragmatic

    Mark Carney’s speech from Davos 2026:

    […]we aim to be both principled and pragmatic – principled in our commitment to fundamental values, sovereignty, territorial integrity, the prohibition of the use of force, except when consistent with the UN Charter, and respect for human rights, and pragmatic and recognizing that progress is often incremental, that interests diverge, that not every partner will share all of our values. 

    So, we’re engaging broadly, strategically with open eyes. We actively take on the world as it is, not wait around for a world we wish to be.

    We are calibrating our relationships, so their depth reflects our values, and we’re prioritizing broad engagement to maximize our influence, given and given the fluidity of the world at the moment, the risks that this poses and the stakes for what comes next.

    And we are no longer just relying on the strength of our values, but also the value of our strength.

    We are building that strength at home.

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  • Telegraph and the First World War

    Nicholas Carr talking about how instant communication, enabled by telegraph, was one of the catalyst the First World War.

    The unprecedented ability of far-flung leaders and diplomats to talk directly with each other without delay spurred great hopes. It seemed obvious that the resulting exchanges would ease friction and encourage goodwill among nations. Nikola Tesla, in an 1898 interview about his work on wireless telegraph systems, said that he would be “remembered as the inventor who succeeded in abolishing war.” His rival, Guglielmo Marconi, declared in 1912 that wireless telegraphy would “make war impossible.”

    What actually happened was altogether different. In the lead-up to the Franco-Prussian War of 1870, telegraphic communications inflamed tensions rather than dampening them. Writes the French historian Pierre Granet: “The constant transmission of dispatches between governments and their agents, the rapid dissemination of controversial information among an already agitated public, hastened, if it did not actually provoke, the outbreak of hostilities.” 

    The start of the First World War in 1914, two years after Marconi announced the end of war, was similarly hastened by the new communication mediums. After the June 28 assassination of Austrian Archduke Franz Ferdinand in Sarajevo, hundreds of urgent diplomatic messages raced between European capitals through newly strung telegraph and telephone wires. As the historian Stephen Kern describes in The Culture of Time and Space 1880–1918, the rapid-fire dispatches quickly devolved into ultimatums and threats. “Communication technology imparted a breakneck speed to the usually slow pace of traditional diplomacy and seemed to obviate personal diplomacy,” Kern writes. “Diplomats could not cope with the volume and speed of electronic communication.”

    Same as ever.

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  • Lessons from the cloud build-out

    This research report from Motilal Oswal which compares the current AI headwinds for the Indian IT industry, with the cloud build-out period of 2016-18:

    Lessons from the cloud build-out: Headwind, then a huge tailwind:

    • The present AI investment cycle closely resembles the early cloud build-out period (2016-18), where cloud initially acted as a headwind for Indian IT services. During those years, cloud migration and platform consolidation eliminated several traditional service lines (infrastructure management, legacy hosting, on-prem ops) and triggered pricing pressure in adjacent portfolios.
    • However, once the cloud infra build-out stabilized, the next phase created an entirely new set of revenue pools: application modernization, cloud-native development, re-architecture of legacy estates, data engineering, DevOps, managed services, and security.
    • These work streams ultimately more than offset the services that cloud displaced, leading to a multi-year technology services upcycle.

    This gives me hope.

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  • Effort heuristic

    JA Westenberg explaining what is effort heuristic:

    There’s a concept in behavioral science called the “effort heuristic.” It’s the idea that we tend to value information more if we worked for it. The more effort something requires, the more meaning we assign to the result. When all knowledge is made effortless, it’s treated as disposable. There’s no awe, no investment, no delight in the unexpected—only consumption.

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  • Bridge

    Kent Beck’s thought provoking post on, what he calls, ‘bridge model’ to make connections with others:

    Here’s the mental model that finally helped me: a bridge.

    I can unilaterally construct a bridge to another person. I can reach out. Make contact. Say something real. The further the distance—emotionally, culturally, socially—the harder the bridge is to build. But it’s possible with almost anyone of positive intent. (It’s also possible with people whose intent toward me is negative or merely transactional. That’s a different problem.)

    With the bridge in place, I can walk halfway across.

    Half. Way. I can make an investment. Do something a little uncomfortable. Reveal something true about myself. Share an observation that matters to me. Ask a question that shows I’m paying attention.

    And then I have to stop.

    I have to stand in the middle of the bridge and wait.

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  • Replacing developers

    This insightful post by Stephan Schwab where he shares a brief history of how we have dreamt of replacing developers and failed. But the pursuit of this dream has created enormous value.

    Perhaps the recurring dream of replacing developers isn’t a mistake. Perhaps it’s a necessary optimism that drives tool creation. Each attempt to make development more accessible produces tools that genuinely help. The dream doesn’t come true as imagined, but pursuing it creates value.

    COBOL didn’t let business analysts write programs, but it did enable a generation of developers to build business systems effectively. CASE tools didn’t generate complete applications, but they advanced our thinking about visual modeling. Visual Basic didn’t eliminate professional developers, but it brought application development to more people. AI won’t replace developers, but it will change how we work in meaningful ways.

    The pattern continues because the dream reflects a legitimate need. We genuinely require faster, more efficient ways to create software. We just keep discovering that the constraint isn’t the tool—it’s the complexity of the problems we’re trying to solve.

    Understanding this doesn’t mean rejecting new tools. It means using them with clear expectations about what they can provide and what will always require human judgment.

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