In 2026, AI can write software. It can generate complex 3D game engines, pass Google software engineering interviews, and build full-fledged e-commerce websites in minutes. Tech giants relentlessly assure us that “programming has been solved by AI.”
Yet, is your smartphone app crashing more frequently than before? After its latest update, did your Windows PC suddenly gain several forced AI features you never asked for? Is your car’s infotainment system lagging, freezing, or spontaneously rebooting while driving?
If you feel this way, you are far from alone. Tracking this trending discussion reveals that an overwhelming number of engineers and everyday users share the exact same frustration.
It is not your imagination. On July 24, 2026, Polish software engineer Piotr published a thoughtful essay on his personal blog titled “Nothing Works and Everyone Is Euphoric,” challenging the mainstream narrative that “AI writing code equals better software quality.” The article went viral on Hacker News, accumulating 427 points and 357 comments—a massive score reflecting a collective anxiety bursting across the developer community.
Caption: xkcd cartoon “Software Development” — satirizing the reality where shipping new features is instant, but keeping quality under control is increasingly out of reach.
Everyday Horror Stories from the Comments
The author cataloged a series of software failures he personally experienced in a single week:
- His banking app requires an average of three FaceID attempts before the payment confirmation modal pops up.
- Opening Slack on macOS resulted in the icon bouncing endlessly in the Dock. While waiting to switch to another window to type a command, the Slack window suddenly popped up, stole focus, and dispatched his unfinished
gitcommand directly into a public channel. - When submitting an online warranty repair request for his faulty LG refrigerator—a tedious multi-step form—the final submit button threw a cryptic error. He only discovered the actual error message by opening Chrome Developer Tools.
- After a software update, his car’s infotainment system randomly lost turn signal audio clicks (until a system reboot), tapping Google Maps opened the FM radio, and every screen action had a 1–2 second delay. This isn’t just bad user experience—it actively threatens driving safety.
In the comment section, one of the most resonated posts came from user mancerayder, who captured the sentiment of millions: “When I see an ‘update available’ notification, my immediate reaction is fear, not anticipation. I don’t know what unwanted things they are going to add.”
Multiple participants pointed out Microsoft as a prime example—disguising major feature additions as mandatory “security updates”, only for users to find a suite of unsolicited AI widgets after rebooting. The perception of software updates has flipped from “getting improvements” to “hoping nothing breaks.”
Why Is Software Degrading When AI Coding Is Getting Stronger?
This paradox seems counterintuitive at first, but everyday analogies make the underlying mechanics obvious. Analyzing the essay and the surrounding discussion reveals four core root causes.
1. Building Faster on a Worse Foundation
Picture a construction site. AI acts like a supercharged concrete mixer and an infinite supply of bricks—raising walls ten times faster than before. However, structural integrity was never determined solely by how quickly bricks are laid; it depends on architectural design, soil surveys, material inspection, and quality assurance at every stage.
In software development, AI coding assistants make “bricklaying” (writing boilerplate code) cheap and instantaneous. But the core pillars of software quality—architectural design, edge-case handling, graceful error recovery, and security models—happen to be where AI struggles most. Laying bricks faster doesn’t fix a shaky foundation; it merely gives product managers an excuse to demand higher towers built faster.
2. “Fixing Bugs” Produces No KPIs
Software organizations remain heavily driven by quarterly KPIs. The fundamental problem is that “making software more stable” rarely translates into impressive slide decks for executive meetings. As the essay author quoted from a fictional product manager: “This quarter we won’t ship any new features or redesign the UI—we will focus exclusively on fixing bugs.” In corporate reality, this almost never happens.
When feature volume directly dictates funding valuations, user growth figures, and PR headlines, stability and code quality become invisible debt. As AI accelerates feature delivery, this bias is magnified tenfold. If pushing new features is fast, bugs are simply patched post-launch. Yet accumulating patches is like slapping band-aids on a crumbling wall—the layer gets thicker, but the structural integrity keeps deteriorating.
3. The Cancerous Spread of Complexity
Over the past decade, software complexity has grown uncontrollably like cancer cells. A modern application depends on dozens or hundreds of third-party libraries, cloud APIs, and service dependencies. A breaking change anywhere in the dependency chain can crash the entire application.
AI tools have not reduced this complexity—they have added another layer on top. Developers now routinely commit AI-generated code that they do not fully understand. It is akin to a doctor prescribing medication without reading the label. AI generates code that “looks plausible,” but lacks genuine comprehension of boundary conditions, concurrency race conditions, security vulnerabilities, and backward compatibility.
4. The Dangerous Vicious Cycle of AI Deskilling
This is perhaps the most subtle and dangerous factor. When developers know AI can generate code for them, their intrinsic motivation to deeply understand the code declines. Repeatedly relying on AI without diving into the underlying logic causes core engineering skills to atrophy.
This reflects the intense debate around “AI deskilling”—as tools get stronger, human capabilities weaken. When everyone relies on AI for code generation, subtle logical flaws in AI output go unnoticed because few remain capable of diagnosing them. The software industry is gradually losing the fundamental ability to understand the code it ships.
Caption: xkcd classic cartoon “Code Quality” — vividly depicting the endless “fix one bug, spawn 127 new bugs” reality in software engineering.
The Villain Isn’t AI, But Efficiency-First Engineering Culture
To be clear, the author is not anti-AI. As he noted: “Those buzzing GPU farms gave us superpowers, but we still haven’t used them to build better software.”
AI itself is merely a tool. The true problem lies in the engineering culture surrounding it—a culture that incentivizes speed, feature inflation, and valuation spikes while rarely rewarding software reliability. When bug fixes are excluded from OKRs, and system stability is less attractive to investors than DAU metrics, even the most powerful AI tools will be deployed in the wrong direction.
Conclusion: Where Is the Hope?
Interestingly, the author concludes on a non-pessimistic note. He argues that as large corporations sink into “AI technical debt,” individual developers who genuinely care about quality face a unique window of opportunity—leveraging AI tools to craft software whose quality far surpasses corporate bloatware.
Early signs are already emerging: grassroots resistance movements against bloat in macOS and Windows, and independent developers building lightweight, stable alternatives. If this mindset spreads across the software ecosystem, it may eventually force the industry to re-prioritize software quality.
Until then, however, the update button remains a risk switch, and new versions often mean new headaches. Recognizing the problem is the indispensable first step toward solving it.
References
- Original Essay: Nothing Works and Everyone Is Euphoric (ptrchm.com)
- HN Discussion: news.ycombinator.com/item?id=49033004 (427 points / 357 comments)
- XKCD #2021: Software Development
- XKCD #1513: Code Quality
- Merchants of Complexity (world.hey.com/dhh/merchants-of-complexity)
- Twitter Threads in Original Essay: x.com/robj3d3/status/2076356929878966555 / x.com/thekitze/status/2076360316670054760
Image Credits
- Figure 1: xkcd webcomic used under CC BY-NC 2.5 license.
- Figure 2: xkcd webcomic used under CC BY-NC 2.5 license.
- Original site (ptrchm.com) contains only favicon.ico and author photo (/images/photo.jpg), with no article body images available for extraction.
