ai

  • 10x Faster, Same Speed

    I’m hearing it everywhere—and experiencing it myself. Software Engineers are experiencing a second youth. Even the most skeptical started embracing LLMs in the past few weeks. But the more I use these tools, the more I realize they’ve exposed what’s always been true—writing code was never the hardest part.

    This inflection point raises so many questions. Is this the last generation of Software Engineers that wrote code by hand? How will future engineers develop the intuitions that you gain by building large systems by hand? Are those intuitions lost forever? And how will it shape the industry’s future? Perhaps questions that deserve another blog post.

    I’ve been wondering about the increase in productivity, which, at the macro level, doesn’t seem particularly dramatic. And at the micro level, I now implement in 1 hour what used to take a day—and yet the project still ships at roughly the same speed. Perhaps it’s too early to measure, since adoption is likely very uneven and most of us are not fully realizing LLMs’ true potential. There are at least two more explanations. One is that this shift made it more apparent that implementation time is not the bottleneck. The real bottleneck is figuring out what to build. Another explanation is that Amdahl’s law is at play. We’ve improved code generation time, but that’s just a fraction of the development process. I find myself spending less time on coding but more time on scoping, project definition, and QA.

    Regardless of the actual productivity improvements, I fear that market pressures, combined with a limited understanding of current model capabilities, might lead to premature task force reductions—more layoffs, in human speak.

    Then there are all the posts invoking Jevons Paradox with the promise of increased demand for software. I’m not convinced it’s that simple. If it’s true that companies can continue to grow with just 30% of their current software engineers, what are they going to do with the remaining 70%? Will large companies expand into new verticals? Perhaps. But large organizations are not known for moving at the pace of technological change. If companies decide to just layoff their surplus engineers, will there be a boom in startup creation? I don’t see that happening either, when the bottleneck is deciding what to build. And if there were a start-up boom, competition would be fierce, as good ideas are scarce. If the scarce resource is knowing what to build, making code cheaper won’t unlock much new demand.

    My recommendation? Embrace change, get used to rapid adaptation, and get good at judging what is worth building in the first place. Lastly, brace yourselves: 2026 will be a hell of a roller coaster.

  • Tsundoku, Telex, and the Art of Productive Procrastination

    I love books. Specifically, I love the physical artifact, also known as a codex, for its role in passing on wisdom through the ages—as beautifully described in Ken Liu‘s short story “The Bookmaking Habits of Select Species.”  

    I don’t read many books a year, as I prefer to practice slow reading and savour each one of them—I’m kidding, I’m just a slow reader. My love for books, combined with my slow reading ability, makes me a perfect practitioner of tsundoku—to reduce my pile, I started gifting my friends the books I want to read instead.

    This was just a long intro to say that I’ve been thinking about writing short reviews for the books I read each year—to keep track of them and maybe spark a few conversations. And… who am I kidding? It’s just performative reading. But naturally, instead of just doing it, I came up with an elaborate excuse to postpone the whole thing: “I need an easy way to display book covers on my blog, and that means building a custom WordPress block that automatically downloads the cover from a title.” I knew I’d never find the time, however small, to implement that—and I didn’t like what I found. But then Automattic released Telex, an AI block builder.

    With my excuse gone, I had to try what my colleagues had come up with. And I have to say that my first experience with the tool, despite its current limitations, exceeded my expectations. (Disclaimer: even though I work at Automattic, no one asked me to write a positive post about Telex. Besides, I would never compromise my integrity and lose the trust of my audience—the five friends who actually read my blog.)

    Things I loved

    A few moments that surprised me in the best way:

    • The preview of the AI-generated block in WordPress Playground was delightful—not just because you can test the block, but because you can tweak it right there in the browser.
    • All the reasonable little choices the AI model made regarding things I hadn’t specified, like what to include in the sidebar settings, small animations, UI decisions, etc.
    • The priceless conversation where the model convinced me that scraping Goodreads for book covers was a terrible idea and suggested using OpenLibrary’s public API instead. It was like trying to convince your uptight friend to board a tram without a ticket in Vienna. I gave up.
    • All the CSS I didn’t have to write or rewrite—my favourite thing in the world.

    Things that still need improvement

    Not dealbreakers, but worth noting:

    • Iterating on small details—tiny UI tweaks and the like—felt slow, as it seemed the model was rewriting the entire block for every change I asked for. Granted, I could have made those tweaks myself, but I wanted to see how far you could get without touching a single line of code.
    • The model didn’t always follow my instructions, which was a bit frustrating given the long waits between iterations. Like most agents I’ve tried, it nails the first 70% and then struggles with the remaining 30% as if it’s solving cold fusion.

    Book cover grid block in action

    After a few teaks, I’ve submitted it to the WordPress.org’s plugin repository for review. So if/when it gets approved it will be available at https://wordpress.org/plugins/book-grid. And here’s how the block looks with a mix of books I’ve read this year…and books I’ve merely acquired. 😅

    understanding michael porter
    Understanding Michael Porter
    Inspired: How to Create Tech Products Customers Love
    Inspired
    demand side sales
    Demand Side Sales 101
    the five dysfunctions of a team
    The Five Dysfunctions of a Team
    reboot
    Reboot
    7 powers
    7 Powers
    awareness
    Awareness
    creative act
    The Creative Act: A Way of Being

    Telex reminded me that most of the time we procrastinate because of the initial friction involved in going from zero to one. AI is reducing that friction and leaving us with fewer excuses to hide behind. So here I am, staring down a pile of books I’ve avoided reviewing for months. Looks like it’s finally time to re-read—and to write.

  • AI is Coming for Your Job

    AI tools are slowly but gradually changing the Software Engineering profession. Although some might argue that the gains in productivity are overestimated, I think this is only the beginning. As those tools improve and evolve to become agentic, such as Devin AI, the industry has started to wonder if there will be much demand for Software Engineers, or even if AI could replace engineers altogether. I have colleagues reaching out to me and being worried about their career in a 18-month horizon. I guess Mark Zuckerberg’s recent statement in the now infamous “masculinity energy” Joe Rogan’s podcast episode is not helping either:

    I think this year, probably in 2025, we at Meta […] are gonna have an AI that can effectively be a sort of mid-level engineer that you have at your company that can write code.

    I was initially skeptical about AI’s impact within such a short timeframe. Then, I started to worry. Now, I believe we’re facing a rapid transformation, where Software Engineers must embrace AI tools and work at a higher level of abstraction—but we won’t be replaced. Yet.

    In the short term, before we achieve AGI, I believe we humans still hold some advantage, and what will become increasingly important is our taste and creativity—qualities that LLMs can’t replicate yet. I agree with Lenny’s view here that Software Engineers need to become more focused on products and customer needs. Understanding customer pain points and figuring out what to build will be the most crucial skill. Engineering and Product Management may merge into a new role.

    Will there be the same demand for this new Product Engineer role as there is for Software Engineers? I am optimistic about this and believe there will be even greater demand. This will likely continue until we reach AGI. After that, predictions become increasingly uncertain.

  • Unveiling My Blogging Journey: Embracing New Beginnings and Exploring the Influence of AI

    Starting a new blog has been on my to-do list since I joined Automattic–the company behind WordPress.com, Tumblr, Jetpack, and many other products–almost four years ago. To push me to finally doing it, I decided to include it in my New Year’s resolution for 2024. Then, I saw Matt’s Birthday Gift post asking readers to write a blog post before January 10th, his birthday, and a link to his post. Matt Mullenweg is Automattic’s CEO, so what better way to accelerate my 2024 blogging goal? On the other hand, research says that publicly announcing your goals makes you less likely to achieve them–maybe keeping this blog hidden from my close friends might help balance things out with my goals 🤷‍♂️. We’ll see.

    In this blog, I’ll try to find a style, my own voice, and a recurring theme. I’ll share my thoughts and experiences on leadership in a distributed tech company, but I might explore other, perhaps tangentially related, topics as I go–like AI-related news or books I’m reading. 

    Speaking of books I’m reading, AI, and topics I’d like to explore, I’d like to close this post with an excerpt and a reflection. I started reading On Writing Well, which in the Introduction section of the 30th Anniversary Edition has a paragraph that got me thinking:

    That condition was first revealed with the arrival of the word processor. Two opposite things happened: good writers got better and bad writers got worse. Good writers welcomed the gift of being able to fuss endlessly with their sentences-pruning and revising and reshaping without the drudgery of retyping. Bad writers became even more verbose because writing was suddenly so easy and their sentences looked so pretty on the screen. How could such beautiful sentences not be perfect?

    On Writing Well, 30th Anniversary Edition – Zinsser, William

    Are AI assistants like ChatGPT, the new word processor? As the lead of the team in charge of the Jetpack AI Assistant product, I feel this is an important question to have in mind, and I wonder how we can create a tool that not only makes it easier to create content but also helps bad writers become better ones.