I notice the trend that people are reading much less in public and on public transporation -- before if you went on a long-haul flight you would bring a couple of books or magazines, now people much prefer to consuming video content. On a flight every row I saw passengers either watching a movie on their phone/laptop/ or screen seat.
If you walk into a cafe it would be odd to see someone reading a book.
And its almost impossible to buy physical newspapers even the Sunday edition for the NY Times as most grocery stores or convenience stores don't carry them.
Personally I'm also guilty of listening to more podcasts and background play -- but I only watch YT visual content when its interesting there is just too much stuff out there. I consume most of my news online -- so my reading comes from mostly articles. Its just more convenient and practical now -- though requires much less effort than say reading longer form content of a book or long essay.
Lately I've been going on TikTok just out of curiosity for entertainmentto watch amusing or funny videos. Its basically like digital crack -- before you know it you spent an hour just watching mindless content and its designed to get you hooked. It really is low-effort instant gratification at its worst (probably worse than porn -- because you stop after a while once satisfied.)
And you see kids as old as 1-2 years old with personal devices watching videos -- so it seems to be a disturbing trend And I heard that professors don't even assign books since they know their students won't read them and will just ChatGPT for summaries.
Most companies aren’t Apple, Nvidia, or Google chasing the top 0.1% of “elite” talent. Outside of a few AI-focused startups, the reality is that 90% of companies are sitting on legacy codebases, still running VMs, or duct-taping CRUD apps together with APIs.
If you happen to be a superstar with a rare niche skill (like building frontier AI models), you basically skip the interview loop and get fought over with million-dollar offers. But that’s a tiny fraction of the market.
For everyone else, hiring looks a lot like dating: both sides aim for a “10,” but usually settle for a “6 or 7.” And the whole process is signaling—candidates overstate their skills, companies oversell their culture and tech stack, and the match lands somewhere in the middle.
Probably the most important non-technical skill is dealing with the egos in the industry since you will come across a lot of them.
Anyone who thinks their boss/coworkers are their friend is surely deluded. There is no loyalty in this day and age-- both from the employer and employee side.
Even asking "how was your weekend?" -- its implied that you just say good rather than sharing details of what you actually did -- they don't really care.
Even if you want the most cynical approach - networking is an essential aspect of career development. If you stick to just "job description during work hours" you won't get far.
Building a cohesive team involves sharing interactions like this. If you truly value your privacy, I suggest you come up with an alternative thing to discuss: sports, weather, funny stories, etc.
I've certainly had weekends where I very much did not want to share what i did, so I deflected in a way that kept the conversation going.
If HR is asking about where you were at 3:15pm on Saturday, and who you were with, and whether you were using work resources at that time, I would start to worry. But a very large and generic, "so what did you do this weekend" - where you are in the driver's seat, that's not the same thing.
When I look back at previous jobs, my strongest regrets are not building stronger interpersonal relationships with my coworkers. I've since rectified that.
Think of it this way, if you must: coworker relationships are owned by the company - personal relationships are owned by the employees. When you become friends with a coworker, you acquire an asset that will go with you when you leave the company. Much like a new skill, this asset will allow you to get higher pay somewhere else.
Just tested this on a rather simple issue. Basically it falls into rabbits holes just like the other models and tries to brute force fixes through overengineering through trial and error. It also says "your job should now pass" maybe after 10 prompts of roughly doing the same thing stuck in a thought loop.
A GH actions pipeline was failing due to a CI job not having any source code files -- error was "No build system detected". Using Cursor agent with Sonnet 4.5, it would try to put dummy .JSON files and set parameters in the workflow YAML file to false, and even set parameters that don't exist. Simple solution was to just override the logic in the step to "Hello world" to get the job to pass.
I don't understand why the models are so bad with simple thinking outside the box solutions? Its like a 170 iq savant who can't even ride public transporation.
> why the models are so bad with simple thinking outside the box solutions
There is no outside the box in latent space. You want something a plain LLM can’t do by design - but it isn’t out of question that it can step outside of its universe by random chance during the inference process and thanks to in-context learning.
They're very good at things have been done a million times before. I use both Claude and Gemini and they are pretty terrible at writing any kind of Vulkan shader but really good for spitting out web pages and small bits of code here and there. For me that's enough to make them useful.
I'm thinking OpenAI's strategy is to get users hooked on these new features to push ads on them.
Hey, for that recipe you want to try, have you considered getting new knives or cooking ware? Found some good deals.
For your travel trip, found a promo on a good hotel located here -- perfect walking distance for hiking and good restaraunts that have Thai food.
Your running progress is great and you are hitting strides? Consider using this app to track calories and record your workouts -- special promo for 14 day trial .
I use WARP.dev CLI terminal that works as a coding agent and has all the models not just from Anthropic and works very similarly to all the CLI Coding Agents (Claude code, Codex, Jules, etc.)
It works very fast compared to Cursor -- biggest limitation is that it doesn't have workspaces where you can get context from several repos for building your application.
MCP servers also work as well just a little more complex.
Warp can actually index your codebases and cross-reference across indexed repos for context: https://docs.warp.dev/code/codebase-context#multi-repo-conte...
For example, if you reference the example repo in your prompt, the agent will use that in what it's working on in your current repo in coming up with code diffs and running commands
The biggest costs for businesses are labor costs and capex. So indirectly higher prices (inflation caused by tariffs) will demand higher wages for workers and cause higher prices for consumers for services seemingly unimpacted by tariffs.
