• 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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  • Children

    Jacob Schroeder sharing his 25 lessons on money and meaning. This lesson regarding raising kids stood out for me.

    The cost of children is an admission to adventure, love, pain, joy, despair, loss, fulfillment – all that life can and should be. Then one day it’s over. The ride comes to a stop – hopefully, much later than sooner – and that emptiness is a bittersweet debt. It is a debt that can never be repaid. You are left desperately wishing to repay it only to take it out again so you can relive it all over, desperately wishing to take out a second mortgage on all the spills, the cuts and bruises, the breaks, the heartaches, the tears, the smiles, the hugs, the laughs, the I love yous and the goodbyes, enough to get you angry at the unfairness of it all.

    I am still on this adventure.

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  • Observing, listening and understanding

    This comment by nicbou who is sharing their thoughts on the layoffs among technical writers due to AI.

    I write documentation for a living. Although my output is writing, my job is observing, listening and understanding. I can only write well because I have an intimate understanding of my readers’ problems, anxieties and confusion. This decides what I write about, and how to write about it. This sort of curation can only come from a thinking, feeling human being.

    I revise my local public transit guide every time I experience a foreign public transit system. I improve my writing by walking in my readers’ shoes and experiencing their confusion. Empathy is the engine that powers my work.

    Most of my information is carefully collected from a network of people I have a good relationship with, and from a large and trusting audience. It took me years to build the infrastructure to surface useful information. AI can only report what someone was bothered to write down, but I actually go out in the real world and ask questions.

    I have built tools to collect people’s experience at the immigration office. I have had many conversations with lawyers and other experts. I have interviewed hundreds of my readers. I have put a lot of information on the internet for the first time. AI writing is only as good as the data it feeds on. I hunt for my own data.

    People who think that AI can do this and the other things have an almost insulting understanding of the jobs they are trying to replace.

    I would implore you to read the comments in the Hacker News thread. A lot of folks are having a feeling that there’s no going back and it reminds me of this—we are in a market of lemons.

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  • Hype first and context later

    Carette Antonin reflecting on the recent viral tweets of Jaana Dogan and Andrej Karpathy and how ‘Influentists’ are hyping up AI only to add context later on, which ends up deflating the hype.

    This pattern of “hype first and context later” is actually part of a growing trend.

    I call the individuals participating to that trend “The Influentists”. Those people are members of a scientific or technical community, and leverage their large audiences to propagate claims that are, at best, unproven and, at worst, intentionally misleading.

    But how can we spot them?

    I personally identify these “Influentists” by four personality traits that characterize their public discourse.

    The first is a reliance on trust-me-bro” culture, where anecdotal experiences are framed as universal, objective truths to generate hype. This is a sentiment perfectly captured by the “I’m not joking and this isn’t funny” tone of Rakyll’s original tweet, but also the dramatic “I’ve never felt that much behind as a programmer” from Andrej Karpathy’s tweet. This is supported by an absence of reproducible proof, as these individuals rarely share the code, data, or methodology behind their viral “wins”, an omission made easier than ever in the current LLM era. And finally, they utilize strategic ambiguity, carefully wording their claims with enough vagueness to pivot toward a “clarification” if the technical community challenges their accuracy.

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  • Renewable energy

    Weimin Chu has documented the scale of renewable energy in China in series of photographs. Yale Environment 360 showcases these photographs along with the energy capabilities of these renewable energy sources.

    Last year China installed more than half of all wind and solar added globally. In May alone, it added enough renewable energy to power Poland, installing solar panels at a rate of roughly 100 every second.

    The massive buildout is happening across the country, from crowded eastern cities increasingly topped by rooftop solar panels to remote western deserts where colossal wind farms sprawl across the landscape.

    “From the ground, it’s hard to grasp the scale of these power plants,” said Chinese photographer Weimin Chu. “But when you rise into the air, you can see the geometry, the rhythm — and their relationship with the mountains, the desert, the sea.”

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