Don’t get me wrong, I absolutely love and crave the experience of working with other people to make things. And I cannot for the life of me understand why seemingly intelligent and talented people like Rands would fritter away their lives and those of others in such trivial pursuits in many cases, and downright evil doings in others.
Here I am, worrying about how I am going to afford housing after a divorce, and I’m reading insightful leadership advice from an author who has seemingly spent their career building this leadership expertise at one company that makes the most insanely technologically advanced gambling distraction devices imaginable, another company that makes war and mass surveillance products seemingly out of a corporate strategy to profit from human suffering, and the least objectionable company that only made the most distracting communication-platform-cum-torture-device when it convinced us all email wasn’t fast enough to get things done™ and that now embodies an actual AI hallucination as a company strategy. Why can we not have good leaders in making a society where divorce doesn’t threaten basic human needs? Or maybe one where healthcare is a given? Food being widely available?
Instead we band together and create more than $5 trillion worth of “value” in three companies that make absolutely nothing of worth to real human needs. And then we read about the games played inside those companies by humans who could be using their skills for anything else useful and we come here to argue about the merits of middle management.
What are we doing? How did we get here? Can any leadership help us work together to dismantle the horrors we’ve created to make room for making things that address real needs?
However, you're right that most people at these companies are so accustomed to the "free money faucet" from ads, huge margins, etc. that it's incredibly easy to end up totally disconnected from reality. That's probably what frustrates you the most.
I will say - after having left Google just about a year ago now - that there is literally no better time to make money in tech than right now. AI is eroding the moat of all large tech companies, and skilled individuals with passion and drive can make a huge impact on the world with an incredibly small budget.
You'll make it. All of us will.
For line managers, they are deluged with impossible, specific asks and they have no real way of knowing if the team will be able to perform, or be happy to. They survive by maintaining fictions and blinders, and staying just ahead in chips.
I think he's underselling to say it's instinct; in law it's called ripeness, waiting for when something really needs to be addressed, and then ideally just reflect that in a way people can take on instead of taking control. The senior's job is not to intervene unless necessary, and even then to prefer activating others.
So I feel it's a project manager mindset to always be tallying asks; while a senior manager is really tracking issues and capabilities on a different timescale, doing the prep to build the capability to address the issue when it's ripe.
> Coffee in hand, I sit down in the Cave. Any Tuesday during the work week, a sip, and I parse the calendar.
How many Tuesdays are there in his work week?
Sometimes we do stuff well because we like the other monkey we're doing it with. Sometimes we do stuff badly because we are an angry monkey. Sometimes we do the right thing but we cannot really explain why. We can sort of predict what the future will be like but not really well.
Management is pretending to "execute programs" and "align value chains" and "strategize on market trends" because the suits they wear are very expensive. But the reality is that they are also monkeys, who try to manage the emotions and urges and pitfalls of other monkeys by guiding interactions between the monkeys.
This kind of slightly wooly, slightly look-at-me-being-business-y kind of writing feels to me like selling your "I'm a monkey who can sometimes make other monkeys interact more effectively" as some cold hard logical skill.
It's a good exercise to mentally go around the a meeting room and think about what each person wants from it. Given Rands' job, he obviously starts thinking about it earlier, and for longer, but even a few minutes while everyone's settling in and chit-chatting can make a difference in how you participate.
I take this as generally focusing on the what ask (and hence give) becomes. But it reminds me of the business classic Theory of Constraints. To me the laserlike focus, or attempt to get to singular clarity is the point; in this highlight we're seeing the notion of software skills rather then a data-based approach, as it's a soft problem.
Both matter. I appreciate this reminder.
Does going throuh all that "AI" slop daily makes people unable to tolerate any other kind of style?
Is "it was AI generated" a replacement for "I don't like his style"?
But I also found the article really unsatisfying. The idea that middle management should spend enormous amounts of time building relationships because other middle managers got vibes that one day it might be useful is insane. I think the article represents the worst of big, slow tech bureaucracies.
Replacing middle management with AI would not work, but using AI to avoid managers needing to have all these meetings would probably work really well. The idea that there's some AI system that has access to all the documents/email/task management systems at the company is a good one, and it could identify situations (like the one in the article) where two projects on opposite ends of the organization are colliding.
Instead of two middle managers needing to do 1:1s with no clear need for years because other middle managers got vibes that they should could be replaced by an AI system that uncovered situations like the ones mentioned in the article.
This wouldnt replace middle managers, but it might help them do their jobs better.
If your org has anywhere north of 100 engineers across separate teams, intelligence gathering and relationship/trust-building is the only way to effectively do work that crosses the boundary of your team's area of responsibility. It's also the only way to protect your team from stepping headfirst into hot bullshit cooked up by clueless product managers, junior executives and other engineering teams who've unilaterally decided your area of responsibility is in their critical path.
> Instead of two middle managers needing to do 1:1s with no clear need for years because other middle managers got vibes
This isn't actually how this happens in practice. These 1:1s happen after their teams consistently have to share ownership over something or their work conflicts. It's more of a standup saying what your team is doing and what you're concerned about than a typical 1:1. You also calibrate the frequency as needed. For most of these it's a QBR but for some teams this will be monthly or even weekly. It's not "because vibes".
LLMs are inherently gullible.
We're not going to call it "management" necessarily, but there is no question that LLMs are going to take over decision making from managers eventually. Why choose a monkey guessing what the evidence says you should do when you could have an optimised evidence-weighted statistical model making the bets? The only reason to use humans is there are still technical limits on how general the models are, limits that seem to be falling away at a pleasing rate.
Firm disagree on claims 2 and 3 (paths to unbias each), though I agree humans (managers included) are inherently gullible.
There's a lot of research into human biases and how to overcome (or at least mitigate) those biases; and one can in principle always hire a "no man" to look for things which can go wrong. This is kinda what corporate lawyers (and, I hear, corporate economists) are there for.
AI, unfortunately, have a weakness which isn't present in meat-based intelligence, one which won't go away even if we get brain-uploads to copy meat-minds into silicon to make better AI: the very fact of being cheap enables us to find their weaknesses by spamming a bajillion variations at them to see what slips past their cognitive blind-spots.
Unfortunately, my take on the second paragraph is even more cynical than yours:
> We're not going to call it "management" necessarily, but there is no question that LLMs are going to take over decision making from managers eventually. Why choose a monkey guessing what the evidence says you should do when you could have an optimised evidence-weighted statistical model making the bets? The only reason to use humans is there are still technical limits on how general the models are, limits that seem to be falling away at a pleasing rate.
We're already seeing LLMs take over decision making from managers, not because they're good in the "optimised evidence-weighted statistical model" sense, but because they're good in the "hyper-persuasive to lazy primate brain" sense.
This also shows the limits of the "hire a no-man" strategy, as this is happening despite the list of people saying "aaaaa this is dangerous!" including many of the people developing these particular AI models, along with some Nobel laureates, various campaign groups marching around with placards, and a bestselling book.
Whats easier, training AI to make good bets (what does that mean in business? Make the most money? Worker quality of life? World a better place?) or training it to get code to compile?
Something tells me people will still be in the mix here.
Isn't such a model inevitably going to be lagging what is happening?
(Monkeys can see/smell/recognise the scat or track of a large cat very quickly and don't sit around to check the data)
People, especially in remote jobs, benefit from being organized into groups intentionally, with distinct rituals that enable them to operate effectively while they get to know each other better. Another person needs to design and oversee all that.
While you can provide templates for that structure that allow oversight to scale so that one person can oversee larger groups, that tends to be more effective in non-remote, and more predictable, work environments. Modern software development is very little of that.
I don't have much in-person experience with middle management in contexts outside of software development, and I suspect there are some opportunities to use AI to bring engineers closer to customers.
If you do rituals you'll get ritual compliance, not people getting to know each other better.
* You're an engineer with 3-6 years of experience in a primarily IC role
* Maybe you've done some tech lead stuff, but you've never actively worked in engineering management.
* You feel that management (and HR for some reason?) is constantly in the way of you getting stuff done, and that your life would be easier if you could simply decline every meeting and only communicate through pull requests.
Humor me, please. I'll explain after.
By extension we're going to need a lot less middle managers as coordination problems decrease.
As for the point I think you're trying to make, the problem with middle management and other chokepoints in general (like PM teams) is that often they become an antipattern. They soak in all the information and then dole it out parsimoniously, so the typical experience as an IC is to be barely able to see the full picture
ICs advocate for AI because they believe they are "doing the most valuable work." A rational AI would see that and let them do it. In this situation, remove the mid management, replace HR/marketing/sales/etc with AI and use AI to enable them to figure out what to build and they build twice as fast. They forget that the "rational" choice might not be what is best for them, their project, or their career.
Each one rebuts this with the way the system has failed them (managers feel that workers do everything BUT the work that moves the company forward, ICs feel like they can do everything BUT the work that moves the company forward)
I had a 50/50 chance of guessing which side of the bell curve you were on and I was wrong. :)
The right work just doesn't get done without staff engineers and architect types having frequent conversations & meetings as well as constant code reviewing. Or long-term ICs effectively doing this role without the title and expectations/responsibilities (raises hand). You can identify these people because they ask questions relentlessly. Always well-considered ones, but even the ones that might make them look stupid in a meeting.
Coding is a small percentage of the work but also just as important. That's the sweet spot. The "non-stop meetings/socializing" people and the "headphones on & grind PRs" types are both two extremes of behavior that are boat-anchors in any organization and will bring productivity/customer-impact to a screeching halt if it goes unchecked for long enough.
And it's _always_ those stupid-seeming questions that uncover showstopping problems that would have bit you if left ignored.
Edit: Not to greenlight anything Palantir is doing, but in my opinion the FDE/FDSE model is probably everyone's near-future if your company is B2B. You can't be an "ignore meetings" type of person and do that.
Not "Ask". "Ask" is a verb.
but in this case, specifically. who are these career people thinking about orgs and their movement in years?
especially in a job economy where employees are expected to be laid off despite "staggering profits". It feels completely orthogonal to the environment I exist in.
is there room for lifers in big orgs? without getting the boot or worrying about the boot?
I would like to move on but also given the current climate that seems ludicrous.
People I talk to in similar places are in the same boat. Hiring is frozen, there's not enough people to manage everything we have, and everyone remaining is hanging on for dear life.
Here are the 1-2 tags defining the intended audience for each article on the front page:
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YouTube to automatically label AI-generated videos Tags: Digital Content Creators, General Tech Consumers
A Eureka machine that thinks like nature and explores what AI cannot Tags: Computer Scientists, AI Researchers
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I think Anthropic and OpenAI have found product-market fit Tags: Tech Entrepreneurs, Product Managers
Hallucinate – Massively Multiplayer Online Rave Tags: Gamers, Creative Coders
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Rapira (Рапира) – Soviet programming language interpreter Tags: Programming Historians, Language Enthusiasts
What Apple and Google are doing to push notifications Tags: Mobile Developers, Privacy Advocates
Commission fines Temu €200M for breaching the Digital Services Act Tags: E-commerce Professionals, Tech Policy Analysts
Ruby vs. Java vs. TypeScript: my experience on building a Cowork DOCX plugin Tags: Software Engineers, Web Developers
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The Ask (the article you previously asked about) Tags: Engineering Managers, Tech Leaders
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Rust (and Slint) on a Jailbroken Kindle Tags: Hardware Hackers, Rust Developers
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Go: Support for Generic Methods Tags: Go Developers, Systems Programmers
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FBI Arrests CIA Official with $40M in Gold Bars in His Home Tags: General Audience, Intelligence Buffs
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Warm up your MacBook (2019) Tags: Mac Users, Hardware Hobbyists
Incident with Pull Requests, Issues, Git Operations and API Requests (GitHub) Tags: DevOps Engineers, Software Developers
A New Typst Template for Pandoc (2025) Tags: Academic Writers, Technical Writers
Stress disrupts hippocampal integration of overlapping events, memory inference Tags: Neuroscientists, Psychology Researchers
Google employee charged with $1M Polymarket insider trading bet on search term Tags: Tech Finance Enthusiasts, General Tech Consumers