The confounding factor here is the size of the company. You are saying, more than "I like managers who contribute technically (whatever that means)", that you like working for small companies.
It's as if people are saying they want a direct democracy in which every issue is voted on directly by the participants, with just one layer between the people and the "prime minister." Good luck with that when the group size exceeds 50 people, and one realizes that people don't want to vote on every issue affecting a larger society or organization.
Despite the proclamations of torment, suffering, and unwillingness to do it, but, they say, "such is life and this is what needs to be done", I often found in CEOs announcing big layoffs a quite visible undercurrent of joyful power-tripness.
Also, it is clear at this point that thought tech leaders decide, probably over group chats mere mortals are not allowed in, on messages to deliver for a few days, urbi et orbi: introspection is overrated; the leaders-followers dichotomy; now, the disdain for "people managers," as if they were imposed by the Galactic Empire instead of being people whom their organization hired for years.
And, like, what sort of message is, to be sent when announcing lay-offs: "from now on, teams will have not 14 but 15 ICs (whatever numbers), the new IC will be the manager, who will continue to be a manager but also will do some IC work"?.
I am repeating what many have said. Nevertheless, it is becoming clear that LLMs can increase productivity (in certain areas and at certain times) for people who are already knowledgeable (in a specific niche or field) due to a combination of better prompts, tool selection, and critical evaluation of LLM output.
But, for those who don't possess those traits, they mostly seem to be, at best, a better search and, at worst, an agent of confusion.
Yesterday, I used Gemini to evaluate some pictures I took. It said things like, "This is great! Beautiful eye and sense of proportions." Then, when I added "no sycophancy" to the prompt, the evaluation changed to "poor technical skills, digital distortion, don't even think of publishing those pictures, you fool."
While LLMs are a phenomenal technological achievement, I am already becoming somewhat jaded, rather than being increasingly bullish. They are very useful as coding agents and excellent as a human-friendly, more efficient Google search, but confusing to the point of being useless in many areas (as of now, of course).
This weekend, I received confirmation that, for data analysis and modeling, coding agents represent a qualitative leap forward comparable to the widespread adoption of personal computers.
I stopped doing scientific research years ago, but before moving on to other things, I had, like many others, I imagine, certain problems that I wanted to study, but given the lack of time and other concerns, I would never have picked them up again.
I launched Codex, and it managed to untangle old files and analyses, find datasets that I didn't know where they had ended up, launch analyses under my guidance, and build visualizations that would have taken me days, if not weeks, to complete.
Of course, I have experience, I know what needs to be done, and I had to correct some errors made by Codex (I am paying for Codex and Gemini now, but I could go back to paying for Claude too), but I was amazed by the quality of the analyses.
To give an example, I had a dataset of weather observations that I had downloaded from a website years ago, hundreds of time series across weather stations.
Codex managed to recover the missing time series, even though the website is no longer active, by first comparing the downloaded data with the data I had, and then also finding a digital elevation model.
Now I will guide Codex in developing a model of extreme events that will allow me to have a spatio-temporal model of extreme events that, without Codex, I would never have had the time or inclination to build.
It may appear so, in the sense that I would think the same if I were the one reading my comments, but, even if I am sure that my resume could be improved (I worked on it multiple times, asked colleagues to have a look, as well as getting some feedback from LLMs), there is nothing obviously wrong with it.
I interviewed dozens of candidates over the years, and I have seen some crazy resumes (10 pages, every technology under the sun listed, dubious certifications). Mine is certainly not one of them.
At first, I was a bit selective about my applications (meaning I was applying to maybe 5 positions per week, not one per month), but in the last six months, I have sent dozens of applications for positions (real or fake, I don't know) that I thought were appropriate for my skills and experience (director, manager, some senior IC positions, not even staff).
I have no problem relocating; I could do so in 15 days (I currently live in California).
I also contacted hiring managers via email and LinkedIn, but I received virtually no response.
At this point, you might think that there is something wrong with me (professionally speaking), that I have a bad reputation of some kind, but that is not the case.
The market is clearly telling me that there is no need for someone with my credentials on paper. Many people find jobs, even quite easily, and millions of people are employed in the tech industry. But thousands of people in the tech industry are also looking for jobs every day and have a stronger network than I do. Either they are looking for you, or they are looking for someone like you, and in the latter case, there are you and hundreds of others.
Have I really tried everything? No, but I've tried a lot.
I want to make it clear that I was presenting my case in response to a question and that this is not a “poor me” post (in fact, I am anonymous and there are no links to my real identity). I am in a privileged position: I have decent savings and can get by for quite a reasonable time, but it is certainly quite disconcerting, disorienting, frustrating, and, frankly, sometimes humiliating not even to get an interview, or a call back.
This could be a problem, but only if I had interviews or even just a phone call from a recruiter. But I'm not even getting to that stage. I just get rejection after rejection via email for every type of company and position I apply for.
Dozens of rejections, and you get to a point where it becomes a waste of time to even apply. Also, many of the job postings are clearly fake; companies like Capital One, JP Morgan, or NBC, just to name the first three companies that come to my mind, have been advertising the same positions for months, if not years.
What happens is that you fall out of the loop and become invisible, if not an outcast that no one wants to touch. You reach out to your network and you receive cold indifference; all the "friends" you thought you had are not interested in providing any factual support (e.g., strong referrals). Basically, it comes to a point where you are begging for attention and some support.
What's discouraging is that there are so many people in leadership positions who have terrible leadership skills or competence. Not that it's something others should think I possess, I'm clearly biased in this case, but they certainly don't have it.
The world is what it is, and plenty of people get laid off and are able to get interviews and find jobs. I am certainly in part responsible for the situation I am in (not in the sense that I did anything shameful or despicable, in the sense that maybe I should have spent time developing a network different from the one I have), but it is not a fun situation to be in.
Being rejected every day, thus subjecting myself to the humiliating ritual of modern times, by companies that I believe could make the most of my talent (my last title was Director of AI, before I was a Staff ML Scientist at a FAANG and an award-winning scientist).
They all seem rather disappointed, at least in the automated rejection emails (mailboxes not monitored, of course) they send me, that they have found other candidates more suited to the position. It seems we are both disappointed, after all.
Not all is lost, though. I am in the enviable position of having perfect health and decent savings.
Without getting into a she-said/he-said debate, I don't believe traffic is shrinking because of the viability of fewer engineers.
If that were the case, it would also be easy to hire hundreds more. With the confusing mix of X.ai, Grok, and SpaceX, I don't think anyone would notice.
X seems to be much more relevant to social and political debate than any other social media platform, which, despite a declining user base, makes it an extremely valuable tool for Musk and his circle.
It may seem like I'm defending or supporting Musk, but that's not my point. What I can say is that Musk made a huge bet when he substantially, even dramatically, reduced X's workforce, and I think he won that particular bet.
The recommendation algorithm they implement is a choice they make, it is not that if they had more engineers they would deploy a “better” one.
Every recommendation algorithm is, in the end, “bad” in some way.
The TikTok algorithm was considered the non plus ultra among recommendation algos; now you cannot watch a video of a cat on TikTok for more than 5 seconds that the next 50 videos they serve you are of cats.
The Netflix recommendation algorithm has not shown something to me that I considered hidden but interesting in years. They just show you whatever they want to push, mostly (I worked there).
You buy a pan to cook steaks on Amazon and, for some reason, the algorithm recommends to buy it along with stroboscopic lights.
I have no professional, personal, or parasocial ties to Musk, so you can safely continue without this having any effect on me beyond a normal conversation, even if contentious.
I would limit the conversation to X, as it is the company that started the famous “you can do the same with 5% (or something like that) of the workforce” movement.
I don't think X is objectively a worse product now, in terms of its technical and technological aspects. This is different from saying that users were better/worse before, and the same goes for the algorithm or the type of information that is “pushed” on the platform.
Let's be honest: people and advertisers left X not because their product was unusable, had a bad UX/UI, etc., but for other non-technical reasons.
One needs to tease apart the effects of Musk and Musk's "policies" on advertising investments, number of users, the boom and slow decline of social media platforms (see Facebook, Instagram coming down from their peak, TikTok gaining ground, but people seem to be already tired of it and waiting for something new) and the technical/technological part of the enterprise.
I don't like layoffs, in particular when I am the one getting laid off (not at X), but the X experience, for a casual user like me, did not get worse, if it did, because there are way fewer people working at X. One may say, I don't like the algos, but that's not coming from a lack of engineers, it is a policy.
Anyone who has worked in the big tech industry knows that probably more than half of the workforce performs tasks that, in essence, are superfluous.
But these things happened: 1) Musk has shown that Twitter can operate with 5% (approximately?) of the workforce he inherited; 2) laying off a lot of people was seen as a sign that the company was in trouble, but not now because; 3) artificial intelligence makes point 2) not a semi-desperate move, but a forward-thinking adjustment to current and future technology development.
I've been out of work for almost a year now, after being laid off, and I think it's very unlikely that I'll ever return (not because of my choice but their choice) to work in the tech industry as a W2 employee. Oh well.
Autogenic training is a practice that works wonders for your ability to control yourself under pressure, whether in specific situations, in the spotlight, or under more mundane pressures. Only after consistent training (but not gruelling! It doesn't require tedious 10-day meditation retreats) can you finally notice how much mental and physical tension, and fears, real or imagined, are present in your life.
In the same way that we practice motor skills (which are also mental skills) separately (think of preparatory running exercises as pedagogical tools for sprints) and then integrate them into performance (soccer players train with specific drills for ball control and one- or two-touch passing), we should practice mental skills first in isolation and then integrate them into performance (Dave Alred, the famous coach who was once the kicking coach for Wilkinson, the fly-half for the English national rugby team, wrote about this in his book “The Pressure Principle”).
Similarly, the autogenic training skills we develop must first be developed in isolation and then integrated (but integration begins on day one) into the performance itself. That is, it is not enough to be relaxed in bed, even if this is reflected in “real life,” but relaxation, which does not mean a state of torpor, far from it, must be part of every activity and challenge.
You don't believe the current version of Claude Code will be able to write complex software on its own.
On the one hand, there is a lot of hype, an incredible amount, actually, but on the other, we have been observing in real time a technological miracle that gets better by the week.
We have no idea what, five years from now, the coding agent will be able to develop.
After two weeks of viral posts, articles, and Mac Mini buying sprees, as it's been happening up to now for every AI product that was not an LLM, it kinda disappeared from the consciousness-- as well as from the tooling, probably--of people.
A couple of months ago, Gemini 3 came out and it was "over" for the other LLM providers, "Google did it again!", said many, but after a couple of weeks, it was all "Claude code is the end of the software engineer".
It could be (and in large part, is) an exciting--and unprecedented in its speed--technological development, but it is also all so tiresome.
While I find the aspiration noble, it seems to me that we don't even know ourselves what we want, or, alternatively, we re-discover every day how our revealed preferences differ from our stated ones. We don't even trick other people, we trick ourselves.
There was also some evolutionary biology/psychology theory developed by Robert Trivers years ago on self-deception and fitness.
We buy a book thinking we are going to like it, and then we don't even open it. The recommender systems give us more of what we interact with (with some quite extreme funnel effects at times, like when we curiously look at a pimple popper video and for the next ten minutes the algo gives us pimple after pimple), but we find out, as stated but not as revealed, that we don't want more of what we interact with.
Nobody wants, in theory and as stated, to be constantly enraged by social media, but most of us, since numbers don't lie, are revealed to enjoy getting enraged.
I don't think AI will have a different effect in the near future, as the main problem is that we don't know, broadly speaking, what we want, apart from the obvious, e.g., I want to watch a football game and I am going to turn on the tv and watch it.
It's as if people are saying they want a direct democracy in which every issue is voted on directly by the participants, with just one layer between the people and the "prime minister." Good luck with that when the group size exceeds 50 people, and one realizes that people don't want to vote on every issue affecting a larger society or organization.