Three years ago, I bought an Asus laptop, specifically the Zenbook Pro 17. It's a powerful machine and works just fine for my needs, but it had one problem that made me want to either return it or throw it out the window. I would work on projects for hours on end and close the lid when I was done. I haven't manually shut down a computer in more than 10 years. I only do so after a forced update or during a debugging session. So I would close the lid, and a couple of hours later I would open it back up. Instead of waking from sleep, the computer would start from scratch as if it had been turned off and the battery was nearly dead. That meant everything I had open was closed. I'm lucky that most of the applications I run can restore a previous session, but it was extremely annoying. I had a similar issue with my previous Asus, and I had blamed Windows for it. The computer often woke from sleep just so Microsoft could perform an update, which used up all my battery. Sometimes I would open my backpack to find a dead laptop that was warm to the touch. I've written this blog post at least five times. Each time I thought I had solved the issue, but then it came back. This time, though, I think I have finally resolved it. So if you have an Asus laptop running Windows and you experience this very annoying issue, you are not alone. In my case, the culprit was the Wi-Fi adapter, specifically the MediaTek Wi-Fi 6E MT7922. The Solution On Windows: Open Device Manager. Expand Network adapters. Right-click the MediaTek device and click Properties. Click the Advanced tab. In the Property box, select Power Saving. In the Value field, select Disabled. That's it. After three years of annoying restarts, this finally solved my problem. Now let me explain what was going on. What Was Happening (based on Windows Event Viewer) When the laptop lid is closed, Windows initiates "Modern Standby." In this state, the screen turns off to save power, but the system remains partially active to maintain background network connectivity. Shortly after, Windows attempts to transition into a deeper low-power state and disconnects the network adapter to conserve battery. However, the MediaTek Wi-Fi driver (mtkwlex) fails to handle this low-power transition properly. About a minute later, it generates Event ID 1033 errors referencing a network device path (specifically \Device\NDMP3 in my logs). Because the driver's error message resource is missing or corrupted, Windows Event Viewer cannot interpret the error and displays a generic warning instead: "The description for Event ID 1033 from source mtkwlex cannot be found. Either the component that raises this event is not installed on your local computer or the installation is corrupted..." Because the Wi-Fi driver fails to sleep, it keeps the system partially awake. This causes abnormal background battery drain and heat buildup, which is exacerbated when the laptop is in an enclosed space like a bag. In response to this abnormal drain, Windows triggers Event 507: "Austerity Battery Drain Budget Exceeded." It's important to note that this event is Windows intentionally waking the laptop up to prevent the battery from dying completely. However, because the Wi-Fi driver is already in a crashed or unstable kernel state, the system fails to recover from this forced wake-up. The result is a silent system crash or thermal shutdown, followed by Event 12 ("The operating system started"), which confirms the laptop rebooted. The Result With the fix in place, the Wi-Fi device no longer attempts to enter its power-saving sleep mode, so it never crashes. The ultimate solution would be a fixed MT7922 driver, but try as I might, I haven't been able to find one online. It's been three weeks so far, and I've been able to resume my work without coming back to a crashed computer. I hope this helps someone else.

It's easier for someone in my position, after working 20 years in this field to talk about morals. I can disagree with the choices my employer makes. In fact, I can walk away. But I remember the dilemma I felt I was in, earlier in my career. The lead developer stood behind me while I was working on a feature and asked me to make a div clickable. That's it. Technically, it's the simplest thing you can do. But, I hesitated. He watched from behind as I tabbed through every application on my computer, doing everything but what he asked. "Just make it clickable," he said again. I have made divs clickable a thousand times in my then short career, I knew that html standards were merely a suggestion. But this one rubbed me the wrong way. Instead I said, "I already have an anchor tag below, the div doesn't need to be clickable." "The fuck you're talking about? Just do it." We got into an argument, and I ended up doing exactly what he said. A little after I pushed my code, he revisited my code and added a slight delay to my click event using setTimeout to disconnect the user action to what occurred after. If what I'm saying sounds a bit vague, that's how it was framed at a time. We had disconnected the technical ask, clickable div, from the actual feature to make the whitespace on the page clickable. Let me make it even clearer. Have you ever used a coupon website? You buy something on a website, let's say nike.com. When you get to the checkout cart, they have a little box that says "enter coupon code for a discount". So you scour the web to find a coupon that will help you pay less for your purchase. You land on our website where we offer a dozen coupons, but they are all partially hidden. The section says "click to reveal". When you click, some random popup appears, then the code is revealed for you to copy and paste and you go on your merry way with a discount. Everything sounds fine so far. What you don't know is that the coupon website gets credit for the sale. A portion of the price you paid goes straight into our pocket, whether you got a discount or not. We get credit from the referral, that's how affiliate marketing works. So why is making the div clickable, or the whitespace clickable a big deal? Because it captures accidental clicks. The company doesn't care if they help you find a good discount or not. In fact, they don't even care if the code works. They just want you to click and for that popup to open so they can get the credit. My task was framed as a technical request, instead of outright saying "trick the user into clicking." When the Honey scandal surfaced, I was confused why it was news anyway. Deception in affiliate marketing is a standard. Very often we disconnect our work from the real world consequences. Back in 2019 I met this girl at a friend’s birthday party. She worked at a bank in the software development sector, and told me about the project on which she’d been working. Their system collected data from various sources on people applying for financial services (e.g.: loans) and would indicate if someone was eligible, or raise a red flag. In the latter case they would have to deal with substantial additional bureaucracy, and often times would not be able to access these services anyway. She seemed quite proud of her work, and told me her team had demoed it the previous week in front of the whole office. They’d shown the report that the system generated for each person in the team. In her case, the system flagged her as “dangerous”, and she was not eligible for a loan. Her grandmother was from Iran, and because there’s frequently cases of money laundering or other irregularities in Iran, she’s immediately flagged too. Despite her being a Dutch citizen, born and raised in the Netherlands, and working in this Dutch financial institution, her bloodline was “too risky” for her employer to lend her money.1 I was confused, and honestly, heartbroken. This person was telling me how proud they were of their work, building a system that discriminates them based on their bloodline. I questioned what she thought about it, and she explained “well, the rules are there…” —she paused a few times— “the rules are there…”. I remained silent and she eventually finished her sentence after repeating it a few times “the rules are there to protect us”. Even though this was six years ago, every time I remember this situation it brings me great sadness. Here was a person who’d worked hard to build a system which would discriminate against them, and yet stood proudly defending their work. We don't see it as our responsibility to question the system. We are happy to do the work as long as we don't see the immediate consequences. I feel this whenever I see flock cameras mounted in the street. Someone had to design them, write the code, test them, ensure that they work to spec. Someone had to install them. These are people doing a good technical job, yet I'm sure they wouldn't be happy if they were tracked by the very system. This is why I was mad when Anthropic wrote their manifesto saying they are against tracking citizens, as opposed to non citizens. You don't get one without the other. We track everyone then discriminate later. This is why I'm against age verification systems, no matter how technically impressive the solution is. Because in the end, I'm the one who has to upload my ID to a system that I cannot trust. With AI, it's even easier to disconnect your day to day work from its consequences. I understand it's much easier to ignore these things when you are just getting started in your career, but eventually, you have to voice your opinion.

During the pandemic, we completed one of our largest projects at work. To celebrate, since we couldn't meet in person, we all ordered food on DoorDash and played an online escape room game together. We were on a Zoom call, helping each other out and having fun. The first challenge was to escape a jail cell. To escape, each of us had to find clues in our own cell to figure out how to open the doors. We each had to find an object that solved a piece of the puzzle, and once we put them all together, the door would open. As a first challenge, it was easy enough. Everyone found a brightly colored object in their room and described it to the team so we could piece it together. Everyone but one team member. "Come on, read it, man, we can win this." He froze. Someone jumped in to help: "Mine was the most obvious green object in the room. Just look for something bright. Maybe blue, or orange, something that seems out of place." He didn't respond. He just sat there, frozen on camera. We figured he was having internet connectivity issues. We waited a good five minutes before he finally found it, and we moved on to the next level. I didn't think much of that day. We finished the game, we had fun, it was great. He waited until our next one-on-one to explain what had actually happened. He panicked, and he was embarrassed. It turned out he was colorblind. We were yelling random color names at him, and he couldn't, for the life of him, see any of them. As far as I can tell, I'm not colorblind, and it never would have occurred to me that this was something to account for. Just last week, I learned about Vehicle Motion Cues on the iPhone, a feature that helps reduce motion sickness. I don't think I've ever experienced motion sickness myself, or at least never in a car. Watching a blind person navigate a website was eye-opening for me. I realized that many of my past design choices would have worked against their experience without my ever knowing it. The same goes for someone navigating a computer entirely by voice. I recently rediscovered Windows Speech Recognition, which I found pretty annoying for my own needs. But for someone who relies on it for all of their computer use, it's an essential tool. A coworker once mentioned, almost in passing, that she struggles to read certain fonts because of dyslexia. Tight letter spacing and low-contrast text make some of our internal tools nearly unreadable to her. I had picked those fonts because they looked good on a demo slide. It had never crossed my mind that a font choice could be the difference between someone reading a document easily and someone giving up on it entirely. In some of our zoom calls, a teammate would often ask if he could do audio only before the call. While it didn't bother me at all, the managers kept insisting on everyone turning on their cameras. But after he used the camera for a few minutes, his connection would start dropping. I just assumed he had slow Internet. But the reality was he was located in a rural area and he relied entirely on his phone's hotspot to connect to the internet. The zoom call was using up all his data in minutes. None of these problems were problems for me. That's exactly what made them invisible. Unless you are experiencing these issues, there's little reason to ever notice them. We tend to design our tools, our meetings, and our expectations around our own experience of the world, and then mistake that experience for the default. It takes a colorblind teammate freezing on a call, or a friend who can't ride in the passenger seat without getting sick, to remind us that "normal" was only ever normal for us. You can never anticipate every invisible problem in advance, that's impossible. But at the very least, we should remember that our own experience is rarely the default. We should be a bit more curious on how others experience the tools we build.

Amazon has been accused several times for ripping off merchants on its platform. And every single time they denied any wrongdoing. A merchant, or anyone really, can create a product (or source it from China), then resell it on amazon. Amazon is the service provider, and hosts all the metrics concerning the products. If Amazon themselves were in the business of creating and selling products, then that creates a potential of conflict of interest. Because they have the data of all products that sell and sell well. They could replicate that success without doing any further research since the merchant has already confirmed the existence of demand. It's not surprising that Amazon Basics quickly became the best selling "private-label brand" on Amazon. They already know what sells because they have access to the data. Yet they continued to deny it, and state that they only ever use publicly available data from sellers. An Amazon spokesperson said the company believes the allegations are "factually incorrect and unsubstantiated," adding that Amazon strictly prohibits the "use or sharing of non-public, seller-specific data for the benefit of any seller, including sellers of private brands." Yet the results are right there for all to see. If you sell any product through Amazon, you are exposing your company's operations to them. If you want to keep that information to yourself, then you don't get to reach your customers, which in reality are Amazon's customers. If you want to buy something online, and get it shipped as quickly as possible, then Amazon is a blessing. Most often than not, you are not buying the product directly from Amazon. An independent store or vendor with a presence on Amazon will fulfill your order. The seller only has minor identifying characteristics on the platform. On the search result page, the space designated to the seller is small and insignificant. The customer has very few reminders that products are offered by anyone but Amazon. (Although if you want to dispute a sale, you are starkly reminded that the item is from a 3rd party vendor.) So there is no surprise when companies embrace AI internally, they are putting themselves at the risk of sharing their product with their competitors. Maybe the most obvious example is when Antropic came up with Claude Design. A tool to help users generate designs, wireframes, etc. Kinda like Figma. That's not a problem on its own, but when Antropic's chief product officer sits on Figma's board of directors, you can't say that there isn't a conflict of interest there. In fact, the chief product officer resigned from the board merely days before Claude Design was announced. He basically extracted all value from Figma then resigned. Figma's AI features are built on top of Claude. So Anthropic literally pulled an Amazon Basic on Figma. When companies force their own employees to use AI to do their day to day work, they are basically asking employees to upload company data to a 3rd party that may become a competitor. Sure something in the contract clause says that the AI company won't train on enterprise customer data, but nothing stops them from peaking at successful product data. Whenever someone tells me that they used AI to build an app and boast of its values or uniqueness, I want to remind them that if you can just prompt-create a product, so can the AI provider. In fact, they might have better resources to create a competing product if it displays any sign of success (see Figma). While it looks like plenty of people are benefitting from AI today, all this information is being shared with AI providers. We are giving them full access to our thought process. When you include them in your workflow, you are basically providing them with a step by step approach on how to do your job. Don’t be surprised when you see a native Antropic/OpenAi project management application suite. Or a CRM, or any software that is trying to integrate with AI and may experience success. A few years back, when I worked in Customer Service Automation, we discovered that most companies used Zendesk to manage their customer service. Since customers mainly contacted support via email, an intentional database had been built that tracked users through their shopping experience throughout the web. While so much could be done with that data, like identifying “problematic” customers, or recommending products based on their history, we ended up finding something more helpful. We could easily detect a pattern of issues for certain shipping carriers. We could see when UPS was having delays in certain cities, or when Fedex was having technical issues when updating the last mile status. None of these things were features designed or provided by anyone. However, having access to businesses’ data gave us insight where we had none before. That became a feature for us, only because we were not competitors to all these online retailers. When you expose your company's internal data to a potential competitor, don’t be surprised when they build a competing business to rival you.

Whenever I saw someone type a natural language query into Google, it made me cringe. "It's not a person," I would say. "Type like you're talking to a machine." This was especially true for programmers and it was before AI took over everything. Instead of "how do I write a function that reads a file?", I would suggest they use specific keywords, something that sounded more like machine language than conversation. "js function to read csv file" or "css gradient background property example." This got you better results. Even though Google was a sophisticated search engine, it was still doing a kind of keyword matching under the hood. But not anymore. You don't get any advantage from writing in "machine language." Google understands natural language just as well. In fact, even better. How is it that in 2026, I Google things less than ever? It's not that I know everything now. It's more that I don't want to call the friend who always talks too much. If the height of the Eiffel Tower ever comes up in conversation, I'll type "eiffel tower wiki" and click through to Wikipedia. I don't want to have a conversation about it. Googling something these days feels like Google is trying to join my private conversation. Where it used to be a tool for finding answers elsewhere, now it's a buddy who gives you an answer. And just as you're about to leave, it says, "hey, did you also know that..." There used to be a machine between me and the information I was looking for. It was good at its job. It sorted, ranked, then presented information. But now, the machine is constantly pushing information at me, watching my reaction, learning from it, and feeding me more, unsolicited. Before, information lived on the web and was hard to find. Today, information still exists, but it's buried under noise. Google no longer helps you find it, it just gives you an answer. That answer might be right or wrong, and right below it, in small print: "AI responses may include mistakes." You rarely get to verify whether the answer is correct, because almost no one clicks through to the source. I know this firsthand. More than three-quarters of my Google referral traffic has disappeared, while my search impressions keep climbing. So what's left to do? I could mourn the old Google, the simpler web. But as the title says, we aren't going back. This is the new reality, and we have to adapt. Rather than blindly embracing change, I think it's smarter to pick and choose. Just last week, I wrote about the small web still being alive. And it did exactly what its name suggests. It stayed small. There are other search engines built for people who want more control. DuckDuckGo. Kagi (my personal favorite). The habit of Googling everything is learned behavior and learned behaviors can be unlearned. What's harder to convey is that Google never presented us with facts, only sources and citations. The way the google answer is presented, we have the impression they are giving us undisputable truths. When everyone is sharing screenshots of the answer they got, all you can do is share a screenshot of the opposite answer you got. The source gets lost. That's where we are now. Skimming the average sentiment of a Reddit thread, or confirming something we already believed. This is the new reality. We're not going back to keyword matching. But I also don't have to accept the new way as the only way. Google has made its search box AI-first and that's their right, it's their product. But it's also my opportunity to try something different. We are not going back. So I might as well choose where I go next.