Since the rise of AI systems I really wonder how people wrote code before. This is exactly how I planned out implementation and executed the plan. Might have been some paper notes, a ticket or a white board, buuuuut ... I don't know.
Not only is the website layout horrible to read, it also smells like the article was written by AI.
My brain just screams "no" when I try to read that.
The other day we were discussing a new core architecture for a Microservice we were meant to split out of a "larger" Microservice so that separate teams could maintain each part.
Instead of just discussing it entirely without any basis, I instead made a quick prototype via explicit prompts telling the LLM exactly what to create, where etc.
Finally, I asked it to go through the implementation and create a wiki page, concatting the code and outlining in 1-4 sentences above each "file" excerpt what the goal for the file is.
In the end, I went through it to double-check if it held up from my intentions - which it did and thus didn't change anything
Now we could all discuss the pros and cons of that architecture while going through it, and the intro sentence gave enough context to each code excerpt to improve understanding/reduce mental load as necessary context was added to each segment.
I would not have been able to allot that time to do all this without an LLM - especially the summarization to 1-3 sentences, so I'll have to disagree when you state this generally.
Though I definitely agree that a blog article like this isn't worth reading if the author couldn't even be arsed to write it themselves.
It’s also just fluff and straight up wrong at parts. This wasn’t checked by a human or at least a human who understands enough to catch inaccuracies. For example for “Plan-then-execute” (which is presented as some sort of novel pattern rather than literally just how Claude Code works right out of the box) it says:
“Plan phase – The LLM generates a fixed sequence of tool calls before seeing any untrusted data
Execution phase – A controller runs that exact sequence. Tool outputs may shape parameters, but cannot change which tools run”
But of course the agent doesn’t plan an exact fixed sequence of tool calls and rigidly stick to it, as it’s going to respond to the outputs which can’t be known ahead of time. Anyone who’s watched Claude work has seen this literally every day.
This is just more slop making it to the top of HN because people out of the loop want to catch up on agents and bookmark any source that seems promising.
Another glaring giveaway is the over use of numbered lists and bullet point lists.
Personally it makes me less likely to read it but the content might be useful. I have some general tech interest but am not overwhelmingly interested in the subject. Sometimes good things crop up on HN too.
Now, if an author was writing for an audience with the intention to attract the interest of people who were not enthusiasts to become enthusiasts of their product they would create something readable and attractive. The LLM hasn't here.
Together, this leads me to think that the readme is not for me but is just for dedicated enthusiasts.
All the READMEs these days are such a tell. It's okay when explicitly prompted, but now thanks to reinforcement learning through people who have no clue, all the models just top off every change with some pointless documentation change.
While using Electron does indeed allow us to run web technologies across platforms, the conversation around browser diversity goes beyond packaging websites as desktop apps. Many mainstream apps are built with Electron, but that doesn't mean there isn't room for innovation in the browser space. Projects like THIS ONE (ChatGPT Atlas) attempt to integrate AI features more tightly with browsing to enhance productivity.
It's worth mentioning that there are alternatives to Electron for building cross‑platform desktop applications that are more resource‑efficient. *Tauri*, for example, uses Rust for the backend and leverages the system's built‑in WebView instead of bundling Chromium.
We may "already do" have tons of cross‑platform apps with Electron, but exploring alternatives like Tauri or even new browser engines could lead to better performance and I'm hopeful that new approaches will push the envelope further.
What's the purpose to have access to smart assistants if it doesn't result in improving your basic needs, not improving your quality of life? Who is spending now? Only high income households, while majority is struggling with high utility bills and grocery prices - very basic needs.
I got a 5 year old Lenovo Thinkcentre for free and tried multiple desktops. The only desktop that had great scaling at a 4k screen was KDE. Gnome was okay with 1x or 2x scaling, but 1.3x ... big nope. Did not work out, performance was very bad.
With the end of Windows 10 support, I installed KDE Neon on my parents computers. Works fine, they can use it. Even on the Surface Pro 5 touchscreen, KDE works great.
In the past I was using Gnome (or Ubuntu's Unity) and never was a fan of KDE, but right now (especially because of the great 4k scaling), I really like it.
