dasil003

There’s also a compounding effect. Even though they tend to be a bit hand-wavy, you can use the words synergy or paradigm in a sentence and still have it confer some kind of meaning. However as soon as you utter the phrase “synergistic paradigm” you are obviously and completely full of shit.

Also a lot of corporate jargon does have specific connotations for skilled communicators to send a message that is seemingly polite but is actually saying something controversial that is picked up only by those in the room savvy enough to understand. In skilled hands it’s very useful, in unskilled hands it’s complete gibberish. In many ways that’s a feature as the clueless cargo-culters quickly out themselves, and then the smart leaders can use that knowledge to route around them or deploy them in non-harmful ways. All without any overt confrontation ever taking place.

I really don't get this point of view at all. I acknowledge that two yours into my quarter century of experience, most of what I knew was easily replaceable by the AI of today. After two decades of experience however, syntax and specific algorithm and language knowledge was perhaps 10% of my value, nowhere near the vast majority.

The idea that low-paid LLM wranglers are going to push out the experienced engineers just doesn't wash. What I think is much more likely to happen is the number of software engineers greatly reduces, but the remaining ones actually get paid more, because writing code is no longer the long pole, and having fewer minds designing the system at a high level will allow for more cohesive higher-level design, and less focus on local artesenal code quality.

To be honest AI is just the catalyst and excuse for overhiring that happened due to the gold rush over the last 20 years related to the internet and smart phone revolutions, zero-interest rate, and pandemic effect.

You're putting words in my mouth. Also, I was talking about Product Managers, there's a word of different between that role and Project Manager (or Program Manager).

I don't know how that relates to what I said, and it's certainly not something I believe. Personally I don't think any form of knowledge work can be learned quickly in 21st century, otherwise it would have been automated away already (well before the current wave of AI that further accelerates the trend). That goes for product management, design, operations, strategy equally to software engineering, data science any other technical disciplines.

You're correct I've spent most time as a software engineer or a engineering manager. I actually started my career as a web designer though. I've also been effectively an active PM in roles where there was no formal product management funtion. I've also been a co-founder of a two person operation where I did all the product and tech, and my co-founder did all the biz and operations. Another startup I co-founded I was "CTO" but was effectively the number 2 in a 100 person company and had veto power over our first PM hire. I've also been part of a larger scaleup that was acquired in a scenario that left a number of folks orphaned, so for a while I was also managing a handful of designers, program managers, and an IT manager.

So yeah, I understand your point, and if I ran a cross-functional team like that I would hopefully hire well enough that I felt the same. So maybe to restate my thinking in a way that may be slightly less controversial: AI is eating a lot of the low-level mechanistic work that used to define being a software engineer, however I never believed that was where the value was for engineers anyway. While some PMs are incredible and would no doubt be able to get good at vibe coding, the majority in my 25 years experience do not have the patience to get to a precision of requirements which is absolutely still a requirement to get anything out of AI.

I agree but my point stands, even if they don’t want to, an engineer at least has the precision of thought to specify how a product could work. Many PMs simply don’t have this, so asking them to become vibe coders is a hopeless waste of time.

As much as I recognize that a truly talented product manager is worth their weight in gold, I'd say the average engineer would be much more capable of learning to be an average PM than vice versa.

PM vibe coding a prototype for demonstration purposes? Might be a better use of a designer or engineers time, but okay I could see it being valuable. PM vibe coding something to ship to production? Your title is now engineer and you are responsible for your change, otherwise this is a direct path to destroying the quality of your product and the integrity of its data.

People absolutely do get promoted for simplicity. I've also seen promos rejected for over-engineering concerns as well. I get that the opposite can happen, and at the end of the day there is some subjectivity, and a good deal of optics involved in the promotion process at any large company, but don't be demoralized by this! The minute you give up your engineering judgment and ethical principles in pursuit of some perceived political path to promotion, you immediately lose credibility with the most competent people that you most would want to work with and learn from. I assure you they are sprinkled throughout all kinds of organizations at all levels, so don't let the bozos define your worldview.

Sure also in big companies there are plenty of places for low performers to survive by owning some very small and rigid scope that doesn’t require any real end-to-end thinking.

In my experience distribution of engineer quality is even across companies, countries, ages and any other dimension we can come up. Certain big scale skills can really only be practiced at honed at large tech companies, but it’s always a small minority that actually make those things happen. Resume alone can be an extremely misleading signal.

The more experienced I get the more I see how these simplified techniques that might be useful to a journeyman engineer in the right context can fail horribly in the wrong context.

For this particular example, the first question I have is why are we upgrading the ORM? As a codebase grows and matures, the cost of ORM change increases, and so too must the justification for upgrading it increase. Any engineer worth their salt needs to know this justification and have it mind at all times so they can apply appropriate judgment as the discovered scope increases. Let's assume now the change is justified.

The next question critical question is how do you know if you've broken anything? Right in the intro the author talks about an "untested and poorly documented codebase", but then in the example uses basic compilation as a proxy for success. I'm sorry to be harsh, but this completely hand-waves away the hard part of the problem. To have any confidence in a change like this you need to have a sense of what could go wrong and guard against those things, some of which could be subtle data corruption that could be extremely costly and hard to unwind later. This may involve logging, side-by-side testing, canary deployments, additional monitoring, static analysis and/or any other number of techniques applied based on an understanding of what the upgrade actually means under-the-hood for the ORM in question combined with an analysis of what risks that entails to the system and business/process in question. Drawing a mindmap of your refactoring plan is barely more than IntelliJ (let alone Claude Code) can already do at the click of a button.

I sort of agree that the surface area and incidental complexity of stacks give more space to plug more developers in than was true in the 70s and 80s. But I disagree strongly this invalidates Brooks Law. Certainly there are cases where adding people helps, especially if they are stronger engineers than the ones that are already there, but I’ve also seen way too many projects devolve into resourcing conversations when the real problem was over-complicated, poorly reasoned requirements, boil-the-ocean solutions promising a perfect end state without a clear plan to get there iteratively.

Safety is a nice idea but it’s not structurally pursuable at this point. Everything is moving too quickly and we don’t exactly know what is useful or not, just like we don’t know what’s safe or not.

Anyone pursuing safety will be outcompeted by someone who isnt. Given the amount of investments there is no patience for any calls to slow down. I tend to believe this won’t actually end in disaster as I don’t think it’s actually economical to put AI everywhere with enough real control that we can’t manage the risks as they evolve, but it’s a low confidence prediction.

“I learned it from watching you dad!” —An LLM

Sure, but clueless leadership is not a new thing. While big companies with structural moats can shamble along with a surprising amount of dysfunction (which is why they tolerate so many muppets in middle management), even they rely on some baseline of system integrity that will erode pretty quickly if they let go of the people who know how things work.

Don’t get me wrong, I think SWE headcounts will reduce over time, but the mechanism will be teams that know how to leverage AI effectively will dominate ones who don’t. This takes more market cycles though, and it’s even hard to nail down the specifics of these skills with the speed agentic coding tools are currently evolving. My advice is make yourself part of the second group, and worry less about bad management decisions that are inevitable.

This feels like the healthiest take (other than just opting out of social media entirely). I wish there wasn’t this tension between scale and freedom/diversity. I wish the dynamics of tech were a little less winner-takes-all. But such is the nature of global digital distribution. Decentralization and local-first are nice ideas but they create a pretty high barrier to entry that keeps a lot of interesting people out. If I’m going to be on social media I don’t want to be in a cesspool like Twitter but I also don’t want to be an idealogical hobbyist bubble.

Maybe I'm just getting old, but I don't understand the appeal of the always-on AI assistant at all. Even leaving privacy/security issues aside, and even if it gets super smart and capable, it feels like it would have a distancing effect from my own life, and undermine my own agency in shaping it.

I'm not against AI in general, and some assistant-like functionality that functions on demand to search my digital footprint and handle necessary but annoying administrative tasks seems useful. But it feels like at some point it becomes a solution looking for a problem, and to squeeze out the last ounce of context-aware automation and efficiency you would have to outsource parts of your core mental model and situational awareness of your life. Imagine being over-scheduled like an executive who's assistant manages their calendar, but it's not a human it's a computer, and instead of it being for the purpose of maximizing the leverage of your attention as a captain of industry, it's just to maintain velocity on a personal rat race of your own making with no especially wide impact, even on your own psyche.

Yeah I think being annoyed by software is far more prevalent than wishing for more software. That said, I think there is still a lot of room for software growth as long as it's solving real problems and doesn't get in people's way. What I'm not sure about is what will the net effect of AI be overall when the dust settles.

On one hand it is very empowering to individuals, and many of those individuals will be able to achieve grander visions with less compromise and design-by-committee. On the other hand, it also enables an unprecedented level of slop that will certainly dilute the quality of software overall. What will be the dominant effect?

I sort of agree the random pontification and bad analogies aren't super useful, but I'm not sure why you would believe the intent of the AI CEOs has more bearing on outcomes than, you know, actual utility over time. I mean those guys are so far out over their skis in terms of investor expectations, it's the last opinion I would take seriously in terms of best-effort predictions.

I wouldn't be surprised if someone had AI write a bot to post a complaint on every HN thread about how the articles smells like AI slop. It's so tiresome. Either the article is interesting and useful or not, I don't really care if someone used AI to write it.

This is absolute nonsense. The app stores are already saturated with tons of free apps that no one uses. Sure the numbers are up—10x of infinity is still infinity—and the reason Apple doesn't care is because this is just the natural end game of their strategy to commoditize their complement.

When it comes to software subscriptions, the bar is just that much higher. Not only do you have to pass the threshold for someone to even adopt another app/website/brand, but now you have to provide enough utility to pay for it. Claude spitting out code for a good-enough clone of an app doesn't come anywhere near the threshold. An agent that can write the code, buy a domain, provision and maintain the database, and submit the app to the app store gets closer, but now it's not looking so cheap anymore, moreso in terms of your time commitment as defacto product manager than actual tokens and hosting costs.

The actual disruption of SaaS apps will come from agents that are capable of solving problems autonomously in a different way such that you don't even need the SaaS. I'm sure we'll get there in time, but not without a lot of data integrity and security issues, and rogue agent fuckups along the way.

I gotta say you really nailed a solid explanation for what I felt reading the OA but would not have been able to articulate it this clearly.

As someone who personally had a history of wanting to be right, sometimes at the expense of being effective, this is a lesson worth taking to heart.

What I’ve learned is that raw engineering chops and deep end-to-end thinking is highly valued if and only if you understand where leadership is trying to go and you bring people along in your vision. If you pitch your boss and they say no, you need to take it to heart and understand why, if you plow ahead vowing to show how right you were you are forcing them into an awkward position where you can only lose.

A lot of replies in the thread siding with the original author and indignant on their own terms about how they’ve been wronged by “corrupt” leaders. But this betrays a misunderstanding of how large orgs work. The nature of success is you have to subvert yourself to the whims of the organization, and only stick your neck out to challenge the status quo when you have sufficient air cover from someone higher up who believes in you. Corporations are often dysfunctional and anyone working within them can clearly see the flaws, but you’ve got to be clear eyed about what influence you have, and even then, pick your battles, or you’ll be rejected like an immune response from the organization.

Is it really fair to saddle the conscientious objectors with this critique? What about the people that stay and continue to profit exponentially as the negative outcomes become more and more clear? Are the anti-AI and anti-tech doomers who would never in a million years take a tech job actually more impactful in mitigating harms?

To be clear, I agree with the problem from a systemic perspective, I just don't agree with how blame/frustration is being applied to an individual in this case.

Um, I guess this might useful to some number of readers, but I don't think it's universal and I don't think it's a secret—more like its one of a few dozen pithy focus hacks that regularly make their way through the blogosphere and social media for those interested in "productivity".

To try my hand at reductive advice, I would say this: know your strengths and what work you do has the most value. The structure exists to serve the work and not the other way around. Habits and processes can serve the work, but can quickly become a form of procrastination for certain types of personalities. Reading about productivity on the internet will not generally make you more productive. Only through honest self-reflection can you actually improve your personal productivity and impact.

True enough, though I think Tailwind suffered something of a black swan event of having lifetime pricing plus AI coding assistants hitting an inflection point that immediately and thoroughly decimated the value prop of their core monetized product.

Putting on a PM hat is something I've been doing regularly in my engineering career over the last quarter century. Even as a junior (still in college!) at my first job I was thinking about product, in no small part because there were no PMs in sight. As I grew through multiple startups and eventually bigger brand name tech companies, I realized that understanding how the details work combined with some sense of what users actually want and how they behave is a super power. With AI this skillset has never been more relevant.

I agree your assessment about the value of good PMs. The issue, in my experience, is that only about 20% (at most) are actually good. 60% are fine and can be successful with the right Design and Engingeering partners. And 20% should just be replaced by AI now so we can put the proper guardrails around their opinions and not be misled by their charisma or whatever other human traits enabled them to get hired into a job they are utterly unqualified for.

Sure, but long term business success aside, I’m sure most of the folks working at this company would die for a fraction of the adoption curve docker had.

I wouldn’t characterize it as a moat exactly. svn/cvs just had a braindead data model. Linus started git with a fundamentally better one.

I definitely see the potential of AI-native version control, it will take a bit more to convince me this is a similar step-level improvement though.

Basically you feed it a massive volume of application code. It turns out there is a lot of commonality and latent repetition that can be teased out by LLMs, so you can get quite far with that, though it will fall down when you get into more novel terrain.

> [...] by asking the right questions [...]

Now you've put your finger on something. Who is capable of asking the right questions?

Architects and engineers are not construction workers. AI can build the thing but it needs to be told exactly what to build by someone who knows how software works.

I’ve spent enough time working with cross-functional stakeholders to know that the vast majority of PM (whether of the product, program, or project variety), will not be capable of running AI towards any meaningful software development goal. At best they can build impressive prototypes and demos, at worst they will corrupt data in a company-destroying level of failure.