In the short term AI's perceived benefit is making existing people more efficient. Engineers being more efficient means need for LESS engineers. Downsizing 100 ICs to 90 is lower risk then it is to scale a team of 1 down to 0 (or even a fractional CEO).
If you believe AI predictions to be directionally accurate then we can expect/observe that managers will start gaining more responsibilities/tasks as their efficiency goes up. A place to test this hypothesis would be management consulting companies. If we are seeing the big 3 make layoffs and decreased revenue. I think consulting companies are a valid proxy for this idea because they act as buffer capacity for the work you describe as CEO work.
Are these layoffs outside of of a normal range? If we assume the rate is consistent for the remainder of the month we can say `currentLayoffs * 2.5` using Layoff.fyi[0] numbers that puts us around 6k people for the month.
TLDR: I have a laptop riser similar to a roost stand, a usb-c second monitor, mechanical keyboard (nuphy air75), wireless mouse (Logitech g305). I also have kindle paper white.
Extra Info:
The second monitor works fine for documentation, but I have gotten a few design contracts lately and the color accuracy on it is pretty rough. At first it worked with only the USB-C cable, but lately I have had to use USB-C + HDMI. I have gotten better at using a window tiling manager, and gotten rid of my addiction to second screening video content, so I have been pondering dropping the second screen. I have tried a few keyboards, the nuphy is fine. The feet keep falling off because I pack it up and move, but super glue fixes it. There is a smaller nuphy that might have been a better choice, I don't need the function row. The mouse has been good so far, I carry around 2 usb c AA batteries. I pondered subbing out second screen for a tablet. I fit everything into a 25L Tom Bihn Synapse.
I use Calibre [0] for ebooks, and PDFs are just in a file on the desktop. I supose you could put them into calibre, but reading papers on an eink reader doesn't sound idea.
Yes, the pandemic motivated me to take an earlier retirement that switched into part time work, and perhaps a career change.
Wife and I had worked toward FIRE for a while. In 2021 it became financial viable. We have been transient in North America and Europe since October 2021. Our plan was to never work again, but some friends convinced me to take a contract job that is ~25 hours a week.
My motivations for leaving: New manager due to re-org, company's goals changed, non-necessity of work for survival, identity issues around career, pressure from family because I wasn't happy. All those motivations lead to suicidal thoughts. I have always done ux, design, and front end development. I think I am going to start a more traditional computer science education path because I find it enjoyable and could be fun for a second career.
What is the pain you are looking to alleviate? YMMV with notion. I think your personal reflections are probably the most important part of this because personal productivity and organization are so personal.
Single app has worked better for me. I am at 4 months of journaling and planning every day (I have used notion for a few years). When I was using desecrate apps I would go 1-3 weeks before system would fall apart.
For me the main pros are: Ability to move and copy elements from tickler to daily plan so easily. Ability to link todo's to documentation. Ability to take notes in a way that works with how I think, and ability to take handle incoming thoughts as fast as they need to be documented.
Main cons are: only "date time" construct in databases, I would prefer a "time" construct. Offline. Data portability.
> I feel like maybe this is the heart of it, having a personal cache to make a temporary mess in until you have time to clean it up later. I could see that being useful - though id want to move everything out of that place and not organize things within it
Cal Newport has a `working_memory.txt` file on every one of his desktops that he chucks random information into and then processes it at the end of the day. Maybe a system like that could be more your jam.
I might one day work up the courage to use [https://bangle.io/](https://bangle.io/) + github. Feels like owning my data + a bit more flexibility could be nice, but that seems like a lot of work.
I have never used it for business cases, but I am in notion for at least an hour a day for personal uses. I use it for a daily planner, personal wiki, and ticker(getting things done) I am naturally unorganized, so I overcompensate. I don't think much of what I do is outside of Notion's primary use case, but maybe it is???
Daily planner
- Every morning I do gratitude, "single most important task", and quick retro on the previous day.
- Schedule out my day giving every 15-minute block of time a goal. While being burnt out I would beat myself up for "not knowing what I am doing with my life". Having a schedule allows me to say "I should be doing x, I don't have to, but that is what I planned to do with this time" it calms some of that negative self-talk.
- Space for me to document random thoughts so they don't use active memory/thought process
Personal Wiki
- I have struggled with too many tabs open, or too many bookmarks in the past. To keep that at bay I have been trying this personal wiki approach for about a year.
- I have a few top-level pages for major categories of my life like bikes, household maintenance, fitness, computers, and programming. then I populate it with different types of content like pages, notes, and databases. These are things like car maintenance schedules, checklists for cleaning, and links/formulas I need to pay quarterly taxes.
Ticker file
- Single database with a few attributes. One attribute is the "review date" that I filter by.
- I chuck random things into this so I can pull them out of my active memory and come back to them later.
I am very lucky, I don't have to do much estimation. I am just a cog in a machine, more senior people break apart work and I execute it. I tried to get a client who has a team in place and just needed extra velocity.
Non-technical people are part of the job, I try my best to explain the tradeoffs of different implementations and let their internal people make those calls. Long term problems are theirs so if they cut corners that is on them in 2 years.
I was based in Denver Colorado, and years ago worked full time for an agency/consulting company. I got my one and only client through a contact I kept in touch with at that agency. After doing some work with that client I started traveling a bit. My hourly rate is lower then most others in the area but it is enough for for me since we don't spend much.
I first acknowledged burnout at the end of 2020. It took 6-12 months of struggling before a baseline could be established and to this day I don't feel "recovered" but I am improving. From reading a lot about burnout I realized people are different and what works for one person may not work for all. Looking back my burnout was caused by constant context switching and a self imposed requirement to always be available. In the moment I thought it was about the work I was doing and how I felt like it wasn't improving the world.
To ease the struggling stage my biggest win was acknowledging what is the minimum actions needed to take to keep coasting, Once I accomplish those things I didn't beat my self up. Examples of this would be acknowledge 6 hours of meetings in a day is a full day, and I don't need to do 6 hours of dev work on top.
To start the healing process I quit my fulltime job and took 3 months off. After that I started contracting instead, billing hourly, and working less then 40 works for my budget and the strong disconnect between working and not working is helpful to me.
I would ask your self the question, do you need to `fix "everything"`. Sounds like a lot of pressure to put on yourself, maybe you need that pressure, maybe you don't.
In the short term AI's perceived benefit is making existing people more efficient. Engineers being more efficient means need for LESS engineers. Downsizing 100 ICs to 90 is lower risk then it is to scale a team of 1 down to 0 (or even a fractional CEO).
If you believe AI predictions to be directionally accurate then we can expect/observe that managers will start gaining more responsibilities/tasks as their efficiency goes up. A place to test this hypothesis would be management consulting companies. If we are seeing the big 3 make layoffs and decreased revenue. I think consulting companies are a valid proxy for this idea because they act as buffer capacity for the work you describe as CEO work.