Ahmen! I attend this same church.

My favorite professor in engineering school always gave open book tests.

In the real world of work, everyone has full access to all the available data and information.

Very few jobs involve paying someone simply to look up data in a book or on the internet. What they will pay for is someone who can analyze, understand, reason and apply data and information in unique ways needed to solve problems.

Doing this is called "engineering". And this is what this professor taught.

[1]: https://www.shrm.org/topics-tools/news/technology/ai-will-sh...

All of sudden to ensure better support and separation of concerns people needed a team with a manager for each service. If this hadn't been the case, the industry as a whole can likely work with 40% - 50% less people eventually. Thats because at any given point in time even with a large monolithic codebase only 10 - 20% of the code base is in active evolution, what that means in microservices world is equivalent amount teams are sitting idle.

When I started out huge C++ and Java code bases were pretty much the norm, and it was also one of the reasons why things were hard and barrier to entry high. In this microservices world, things are small enough that any small group of even low productivity employees can make things work. That is quite literally true, because smaller things that work well don't even need all that many changes on a everyday basis.

To me its these kind of places that are in real trouble. There is not enough work to justify keeping dozens to even hundreds of teams, their managements and their hierarchies all working for quite literally doing nothing.

I'll never forget the sama AGI posts before o3 launched and the subsequent doomer posting from techies. Feels so stupid in hindsight.

You really want to believe, maybe even need to believe, that anyone who comes up with this idea in their head has never written a single line of code in their life.

It is on its face absurd. And yet I don't doubt for a second that Garman et al. have to fend off legions of hacks who froth at the mouth over this kind of thing.

My boss said we were gonna fire a bunch of people “because AI” as part of some fluff PR to pretend we were actually leaders in AI. We tried that a bit, it was a total mess and we have no clue what we’re doing, I’ve been sent out to walk back our comments.

Pretty obvious conclusion that I think anyone who's thought seriously about this situation has already come to. However, I'm not optimistic that most companies will be able to keep themselves from doing this kind of thing, because I think it's become rather clear that it's incredibly difficult for most leadership in 2025 to prioritize long-term sustainability over short-term profitability.

That being said, internships/co-ops have been popular from companies that I'm familiar with for quite a while specifically to ensure that there are streams of potential future employees. I wonder if we'll see even more focus on internships in the future, to further skirt around the difficulties in hiring junior developers?

Finally, the c-suite is getting it.

[1] https://news.ycombinator.com/item?id=41462545

I’m not even sure AI is good for any engineer, let alone junior engineers. Software engineering at any level is a journey of discovery and learning. Any time I use it I can hear my algebra teacher telling me not to use a calculator or I won’t learn anything.

But overall I’m starting to feel like AI is simply the natural culmination of US economic policy for the last 45 years: short term gains for the top 1% at the expense of a healthy business and the economy in the long term for the rest of us. Jack Welch would be so proud.

Undergraduate -> Graduate Student -> Post-doc -> Tenure/Senior

Some exceptions occur for people getting Tenure without post doc or people doing some other things like taking undergraduate in one or two years. But no one expect that we for whole skip the first two and then get any senior researchers.

The same idea applies anywhere, the rule is that if you don't have juniors then you don't get seniors so better prepare your bot to do everything.

On a side note.. ya’ll must be prompt wizards if you can actually use the LLM code.

I use it for debugging sometimes to get an idea, or a quick sketch up of an UI.

As for actual code.. the code it writes is a huge mess of spaghetti code, overly verbose, with serious performance and security risks, and complete misunderstanding of pretty much every design pattern I give it..

Haven't we learned that it almost always ends up in hollow PR and marketing theater?

Basically the solution to this is extending education so that people entering workforce are already at senior level. Of course this can't be financed by the students, because their careers get shortened by longer education. So we need higher taxes on the entities that reap the new spoils. Namely those corporations that now can pass on hiring junior employees.

The thinking was that they could iterate faster, ship better code, and have an always on 10x engineer in the form of Claude code.

I've observed perfectly rational founders become addicted to the dopamine hit as they see Claude code output what looks like weeks or years of software engineering work.

It's overgenerous to allow anyone to believe AI can actually "think" or "reason" through complex problems. Perhaps we should be measuring time saved typing rather than cognition.

[1] vibebusters.com

In the Swedish schoolsystem, the idea for the past 20 years has been exactly this, that is to try to teach critical thinking, reasoning, problem solving etc rather than hard facts. The results has been...not great. We discovered that reasoning and critical thinking is impossible without a foundational knowledge about what to be critical about. I think the same can be said about software development.

Independent thinking is indeed the most important skill to have as a human. However, I sympathize for the younger generations, as they have become the primary target of this new technology that looks to make money by completely replacing some of their thinking.

I have a small child and took her to see a disney film. Google produced a very high quality long form advert during the previews. The ad portrays a lonely young man looking for something to do in the evening that meets his explicit preferences. The AI suggests a concert, he gets there and locks eyes with an attractive young woman.

Sending a message to lonely young men that AI will help reduce loneliness. The idea that you don't have to put any effort into gaining adaptive social skills to cure your own loneliness is scary to me.

The advert is complete survivor bias. For each success in curing your boredom, how many failures are there with lonely young depressed men talking to their phone instead of friends?

Critical thinking starts at home with the parents. Children will develop beliefs from their experience and confirm those beliefs with an authority figure. You can start teaching mindfulness to children at age 7.

Teaching children mindfulness requires a tremendous amount of patience. Now the consequence for lacking patience is outsourcing your Childs critical thinking to AI.

You don't fire people if you anticipate a 100x growth. Who cares about saving 0.1% of your money in 10 years? You want to sell 100x / 1000x/ 10000x more .

So the story is hard to swallow. The real reason is as usual, they anticipate a downturn and want to keep earnings stable.

“My view is you absolutely want to keep hiring kids out of college and teaching them the right ways to go build software and decompose problems and think about it, just as much as you ever have.” - Matt Garman

"We will need fewer people doing some of the jobs that are being done today” - Amazon CEO Andy Jassy

Maybe they differ in degree but not in sentiment.

From the perspective of a former employee. I knew that going in though. I was 46 at the time, AWS was my 8th job and knowing AWS’s reputation from 2nd and 3rd hand information, I didn’t even entertain an opportunity that would have forced me to relocate.

I interviewed for a “field by design” role that was “permanently remote” [sic].

But even those positions had an RTO mandate after I already left.

I think sometimes the definition of work gets narrowed to a point so infinitesimal that everyone but the speaker is just a lazy nobody.

There was an excellent article on here about working at enterprise scale. My experience has been similar. You get to do work that feels really real, almost like school assignments with instant feedback and obvious rewards when you're at a small company. When I worked at big companies it all felt like bullshit until I screwed it up and a senator was interested in "Learning more" (for example).

The last few 9s are awful hard to chase down and a lot of the steps of handling edge case failures or features are extremely manual.

From a person who is responsible for delivering projects, I’ve never thought “it sure would be nice if I had a few junior devs”. Why when I can poach an underpaid mid level developer for 20% more?

- something we've been doing since forever

- the latest trend that can be picked up just-in-time if you'll ever need it

I just won't use that information in quite the excitable, optimistic way they offer it.

Especially with the amount of money that was put into just astroturfing the technology as more than it is.

> "Measuring software productivity by lines of code is like measuring progress on an airplane by how much it weighs." -- Bill Gates

Do we reward the employee who has added the most weight? Do we celebrate when the AI has added a lot of weight?

At first, it seems like, no, we shouldn't, but actually, it depends. If a person or AI is adding a lot of weight, but it is really important weight, like the engines or the main structure of the plane, then yeah, even though it adds a lot of weight, it's still doing genuinely impressive work. A heavy airplane is more impressive than a light weight one (usually).

https://nordicapis.com/the-bezos-api-mandate-amazons-manifes...

I miss her jokes against anxious nerds that just wanted to code :(

Don't forget the rise of boot camps where some educators are not always aligned with some sort of higher ethical standards.

Now as a hiring manager I’ll say I regularly find that those who’ve had humanities experience are way more capable and the hard parts of analysis and understanding. Of course I’m biased as a dual cs/philosophy major but it’s very rare I’m looking for someone who can just write a lot of code. Especially juniors as analytical thinking is way harder to teach than how to program.

Memorization is not a panacea. I never found memorizing l33t code problems to be edifying. I think it's because those kinds of tight, self-referential, clever programs are far removed from the activity of writing applications. Most working programmers do not run into a novel algorithm problem but once or twice a career. Application programming has more the flavor of a human-mediated graph-traversal, where the human has access to a node's local state and they improvise movement and mutation using only that local state plus some rapidly decaying stack. That is, there is no well-defined sequence for any given real-world problem, only heuristics.

A regular old competent developer can quickly pick up whatever stack is used. After all, they have to; Every company is their own bespoke mess of technologies. The idea that you can just slap "15 years of React experience" on a job ad and that the unicorn you get will be day-1 maximally productive is ludicrous. There is always an onboarding time.

But employers in this field don't "get" that. For regular companies they're infested by managers imported from non-engineering fields, who treat software like it's the assembly line for baking tins or toilet paper. Startups, who already have fewer resources to train people with, are obsessed with velocity and shitting out an MVP ASAP so they can go collect the next funding round. Big Tech is better about this, but has it's own problems going on and it seems that the days of Big Tech being the big training houses is also over.

It's not even a purely collective problem. Recruitment is so expensive, but all the money spent chasing unicorns & the opportunity costs of being understaffed just get handwaved. Rather spend $500,000 on the hunt than $50,000 on training someone into the role.

And speaking of collective problems. This is a good example of how this field suffers from having no professional associations that can stop employers from sinking the field with their tragedies of the commons. (Who knows, maybe unions will get more traction now that people are being laid off & replaced with outsourced workers for no legitimate business reason.)

If you're quoting something, the only ethical thing to do is as verbatim as possible and with a sufficient amount of context. Speeches should not be cleaned up to what you think they should have said.

Now, the question of who you go to for quotes, on the other hand .. that's how issues are really pushed around the frame.

I bet Google has a lot of tools to say convert a library from one language to another or generate a library based on an API spec. The 30% of code these LLMs are supposedly writing is probably in this camp, not net novel new features.

1.) Elon fired 80% of twitter and 3 years later it still hasn't collapsed or fallen into technical calamity. Every tech board/CEO took note of that.

2.) Every kid and their sister going to college who wants a middle class life with generous working conditions is targeting tech. Every teenage nerd saw those over employed guys making $600k from their couch during the pandemic.

You're committing the classic fallacy around microservices here. The services themselves are simpler. The whole software is not.

When you take a classic monolith and split it up into microservices that are individually simple, the complexity does not go away, it simply moves into the higher abstractions. The complexity now lives in how the microservices interact.

In reality, the barrier to entry on monoliths wasn't that high either. You could get "low productivity employees" (I'd recommend you just call them "novices" or "juniors") to do the work, it'd just be best served with tomato sauce rather than deployed to production.

The same applies to microservices. You can have inexperienced devs build out individual microservices, but to stitch them together well is hard, arguably harder than ye-olde-monolith now that Java and more recent languages have good module systems.

"It just means that each of us has to get more in tune with what our customers need and what the actual end thing is that we're going to try to go build, because that's going to be more and more of what the work is as opposed to sitting down and actually writing code...."

https://www.businessinsider.com/aws-ceo-developers-stop-codi...

If you read the full remarks they're consistent with what he says here. He says "writing code" may be a skill that's less useful, which is why it's important to hire junior devs and teach them how to learn so they learn the skills that are useful.

There are lots of personal projects that I have wanted to build for years but have pushed off because the “getting started cost” is too high, I get frustrated and annoyed and don’t get far before giving up. Being able to get the tedious crap out of the way lowers the barrier to entry and I can actually do the real project, and get it past some finish line.

Am I learning as much as I would had I powered through it without AI assistance? Probably not, but I am definitely learning more than I would if I had simply not finished (or even started) the project at all.

> (…)

> I’m not even sure AI is good for any engineer

In that case I’m not sure you really agree with this CEO, who is all-in on the idea of LLMs for coding, going so far as to proudly say 80% of engineers at AWS use it and that that number will only rise. Listen to the interview, you don’t even need ten minutes.

But I have not yet been able to consistently get value out of vibe coding. It's great for one-off tasks. I use it to create matplotlib charts just by telling it what I want and showing it the schema of the data I have. It nails that about 90% of the time. I have it spit out close-ended shell scripts, like recently I had it write me a small CLI tool to organize my Raw photos into a directory structure I want by reading the EXIF data and sorting the images accordingly. It's great for this stuff.

But anything bigger it seems to do useless crap. Creates data models that already exist in the project. Makes unrelated changes. Hallucinates API functions that don't exist. It's just not worth it to me to have to check its work. By the time I've done that, I could have written it myself, and writing the code is usually the most pleasurable part of the job to me.

I think the way I'm finding LLMs to be useful is that they are a brilliant interface to query with, but I have not yet seen any use cases I like where the output is saved, directly incorporated into work, or presented to another human that did not do the prompting.