It took me like five years to realize it was really not good idea for a small B2B business to spend a part of the limited resources in that. I needed several experiences to understand that in many cases good customer relationship and reliable system is much more important. But it wasn’t until recently that I started thinking like “wait, if it tricks the users into doing something they’re unwilling to do, isn’t it unethical?”

It makes me wonder how little we think about the ethics and the consequences of our investment. It’s not like we understand it’s unethical but do it anyway for profit. We simply don’t care how unethical it can be, not even slightly, until the evidence of the harmful effects are not negligible after years and decades.

For example, to automate processing emails, it needs to 1. go to Gmail 2. log in to Google if necessary (This often requires two step verification so it's hard to completely automating, but possible) 3. read the latest mail 4. check the content and choose the action - if needed, reply the email - if it mentions tasks, add them to the todo list - if it mentions schedules, add them to the calendar 5. repeat for all emails based on specified conditions. And each step requires dozens of DOM (a11y tree) analyzes and actions (fill username/password input, check keep logging in, click submit button, etc). Based on the model used, each step can take ~100s. So easy tasks can easily add up to tens of minutes or even hours.

For frequently used tasks, I write skills like /logging-in, /read-latest-emails, using playwright scripts and let the agent choose them And based on the email content, the agent chooses other tools like /write-reply, /add-todo, /add-event, etc, so that the model can only focus on the core tasks requiring thinking. It reduces the execution time drastically.

But it can buries important business logic in the playwright scripts, not the agent's instructions. For examples, simplified steps to add TODO items are like; 1. read the email 2. check if it's about todos, then decide to add them to Asana 3. extract and summarize the title, content, priority, due date, tags, etc. 3. access to Asana (log in if necessary) 4. check if there are similar tasks 5. if not, add the tasks This can take tens of minutes, and each step can have important business logic, like; - how to decide the priority and due date - how to choose tags based on the content - how to decide if two tasks are similar This information should be read and updated by not only developers, but managers and other teams. And if I write those steps in skills with playwright scripts, it improves the speed, but all those business logic are buried in the code, so not accessible by non-technical people. It's also error-prone because web sites often tweak the UI and scripts can stop working.

So it's very convenient if the agent processes these step once, then decides it's worth writing the playwright script so that the next time those mundate processs can be executed instantly.

With automatic skill generation, the agent decides by itself if there are workflows worth writing skills with playwright scripts, like /log-in, /extract-information, /check-similar-tasks, /add-tasks. Like Just-In-Time compiler, the skills are a byproduct of the agent instruction, all business logic are written in the agent's instruction, and doesn't need to be updated manually nor tracked in a version control system.

This can reduce a lot of execution time and API cost, and be applied other than browser automation, like computer use or any other agentic tasks if it's possible to write automation scripts for tasks not requiring thinking.

    The warning can be suppressed by `--no-xattrs --no-mac-metadata`.

    -  tar czf dist.tar.gz dist
    +  COPYFILE_DISABLE=1 tar czf dist.tar.gz dist

  “Duplication is far cheaper than wrong abstraction."

  1. The scale of the fraud was too big
  2. From emails it seemed she intentionally tricked investors
  3. The product, medical equipment, endangered patients.

I was just thinking about what had been avoiding enshittification, and Apple's hardware was the only thing I came up. All other stuff, all products from Google, MS, Facebook, Twitter, and even Nvidia though the performance was improved has gone downhill. It's not only tech companies, but fast food, car manufacturers, real estate, and many others, if it wasn't shit from the start like consulting, healthcare, and marketing.

They have flaws, like not allowing users to repair the hardware, but well, at least it's consistent.

I really hope Apple (hardware at least) will remain free from enshittification.

I can't control my mood, but when I am positive, I start a new hobby like dancing or playing an instrument, cook healthy, lift, sleep well, study new things, etc. But when I'm depressed, I lose all interest in my life goals, eat junk food, skip exercise, and browse the Internet all night. I can't even enjoy my hobbies anymore.

It's always my mood that comes first, then I can find life goals and naturally do all healthy stuff.

Funnily, when I'm mentally healthy I also visit Hacker News frequently, but when I'm depressed all I do is infinite scrolling Reddit/TikTok.

I created a GCP project (my-app-dev) for exploring how to scale up the cloud service. I added several resources to mock the production, like compute instances/cloud SQL/etc, then populated the data and run several benchmarks.

I changed the specs, number of instances and replicas, and configs through gcloud command.

  $ gcloud compute instances stop instance-1 --project=my-app-dev
  $ gcloud compute instances set-machine-type instance-1 --machine-type=c3-highcpu-176 --project=my-app-dev
  $ gcloud sql instances patch db-1 --tier=db-custom-32-131072 --project=my-app-dev

  $ gcloud projects list
  PROJECT_ID     NAME       PROJECT_NUMBER
  my-app-test    my app     123456789012
  my-app-dev     my app     234567890123     <- the dev project I was working on
  my-app         my app     345678901234     <- the production (I know it's a bad name)

Of course I checked every commands. I couldn't YOLO while working on cloud resources, even in dev environment. But I focused on the subommands and its content and didn't even think it had changed the project ID along the way.

It continued to suggest more and more aggressive commands for testing, and I approved them brain-deadly...

  $ gcloud sql instances patch db-1 --database-flags=max_connections=500 --project=my-app
  $ gcloud compute instances delete instance-1 --project=my-app
  $ echo 'DELETE FROM users WHERE username="test";' \
      | gcloud sql connect my-db 
   --user=user --database=my-db --project=my-app
  $ wrk -t4 -c200 -d30s \
      "http://$(gcloud compute instances describe instance-1 \
      --project=my-app \
      --format='get(networkInterfaces[0].accessConfigs[0].natIP)')"

Fortunately, it didn't do anything irreversible. But it was one of the most terrifying moments in my career.

I'm sure in the near future, policy decisions or war strategies will be decided by prediction markets' odds, if they are not already being used.

Because the author suggested swapping caps lock and control key, I also recommend mapping escape key at the control key and change the behavior based on whether another key is pressed. For example, if you press control + a, it sends c-a, but if you only press control key and then release, it sends escape. It makes your vim life (and in general) a lot easier. You don’t have to compete the most variable real estate on the keyboard, right next to the A key.

For most bindings like moving, resizing, and splitting,I emulate vim bindings.

Also, -r flag for bind-key command is impotent, because it enables to repeat commands like changing the pane size or move focus. You don’t have to press prefix key each time.

If you want to get fancy look with minimal setting, use plugins like nord tmux theme.

Don't get me wrong, I use AI too for daily tasks and my job as a programmer, and it definitely helps me get the job done faster (sometimes it's almost instant). But it still requires a lot of effort for complex or unconventional tasks.

When I hear "AI does most of my job", I think of DOGE employees who use AI to identify "waste of money". All they do is ask AI with very lazy prompts like "list DEI projects" with the list of government sponsored projects including simple descriptions. They don't even provide what DEI means. And they just cut all projects the AI flagged. I'm sure their "productivity" is very high. They can "complete the job" that would require days, weeks, or months of investigation with a single prompt.

I also think the results have a strong tendency to flag a project as DEI, because "is this DEI" is a question often asked by racists and misogynists on right-wing websites, and often the answers are "Yes", and that likely causes a strong bias.

[1] https://www.9news.com/article/news/politics/doge-chatgpt-dei...

But I think training models using copyrighted content is stealing in the first place. It's not fair use, so it should be banned entirely.

Many stay-at-home moms (including my mom) seemed to enjoy her visit. She and my mom talked a lot, sometimes for hours (I still can't figure out how she completed her job when she spent so much time with one person). They chatted about recent events, like the daughter of the fisherman gave birth, the great-grandpa of the liquor shop died of cancer, a newly opened restaurant in the nearest town sucked, and sometimes shared even personal struggles or family matters. It really helped a lot of people combat mental struggles caused by the isolation of being traditional stay-at-home wives in a super rural area. The only downside was anything you shared with her would be spread in the entire village before dawn.