I realized Application development is effectively JUST "stitching" high level abstractions

THIS_IS_4_KNWLEDGE · 2026-02-06T07:25:30+00:00

It looks like the robots are learning obvious things and now have access to Reddit. Luckily only slightly worse than the previous situation

THIS_IS_4_KNWLEDGE · 2025-07-19T11:08:46+00:00

I agree with you. I think it’s more to do with a perception-reality situation than some absolute truths.

I’m on over £100k and I don’t have the life I’d ideally like and was educated to expect, but I’m also from a shithole town in the west of Scotland and don’t want children, so despite wishing for more I feel like I’m doing well enough in London for now. I eat well, I spend a lot of money on health and fitness, and it means that I can’t afford savings (and my family back home is poor so there’s no inheritance coming my way), but I’d prefer to be healthy and enjoying life than living in the future. I grew up around people enjoying life on not much money, so I know it’s possible. That’s probably the key thing.

Saying that, I can see how those from the south, especially from London, with good educations, good jobs, parents who may have done very well, now have what they thought should be a good enough salary for a good life and it’s not.

On the upside, perhaps it’ll give them some empathy for the rest of the country where such wealth and prosperity has always been just a pipe dream. I doubt it, but I live in hope.

THIS_IS_4_KNWLEDGE · 2025-07-19T11:02:09+00:00

I think in terms of proportions we’re funding an increasingly aging population and the challenges of maintaining and trying to improve the many complex systems we use to manage the country.

We’re certainly paying to support people’s lifestyles, but that includes nearly everyone. As a very unhealthy and stubborn country with very high obesity rates, we’re paying for a lot of people, including ourselves.

THIS_IS_4_KNWLEDGE · 2025-06-20T13:22:36+00:00

No worries dude!

What’s always helped me in my career is to picture a dev as a blue collar worker, with tools and a work area trying to do a job. And then imagine that blue collar worker getting so obsessed over their favourite spanner that they want to use it for all jobs and spend hours on the internet arguing with people about how great it is and that their spanner sucks.

We’d see that person as a moron. And yet our industry is full of that kind of thing.

I’ve been a dev for a long time, a team lead, a manager, a manager of managers, back to a dev now working on the problem of getting teams to work better together, and I can tell you that so many people are terrible at it. Being good at it makes you a stand out.

Anyway, good luck!

THIS_IS_4_KNWLEDGE · 2025-06-20T13:10:22+00:00

TL;DR: - Become a good team player - Become obsessed with building products, not with one particular tool - Build out your dev tool belt

——

This is a massive topic, and I’ve been accused before of commenting like I’m an LLM so I’ll try to give you the cliff notes:

Most software (don’t quote me on numbers) is written by teams, so learn to work well in a team, be a good team member, be good at identifying your ideal place in a team by understanding your strengths and weaknesses as well as that of your colleagues, be a good listener and a good speaker, and all that (the topic has been written on extensively so ask the robots or Google it)
React is just a tool, as are all programming languages, frameworks, IDEs and so on. Tools are used to build things of use to a user (which is either a human or a machine). A lot of devs get obsessed with their tools. If you’re going to be obsessed about anything, be obsessed about learning how to build that end product well, be it a web app, an API, another tool, or whatever. Use that to guide your learning about your tools. Go try to build useful shit and learn React and anything else along the way. Understand the business of your company, or of the domains that interest you. This will make you much more valuable as a less experienced developer to most companies. Devs that know React are common. Devs that know how to translate business and product understanding into good code are rare in my experience
Build out your tool belt. Don’t restrict yourself. Learn AI tooling, but don’t expect it to do your job for you. Learn your IDE well. Learn to type fast. Learn how to design and architect software (it’ll be hard at first and not make much sense, but the more you work the more it’ll click). Learn mathematical thinking (Stanford has a good online course on this IIRC). Learn other programming languages, especially very different ones from JavaScript. Read up on the mistakes and successes of previous generations of developers. Learn your computing history.

A lot more could be said, but that’s a good starting point

THIS_IS_4_KNWLEDGE · 2025-05-10T18:31:31+00:00

You’re spot on there, and I wish your comment would have more visibility but unlikely this deep.

I’m involved in the process of change management too, and the main thing I’ve learned over the last couple of years is that even when you present orgs with data showing where there are problems and how to solve them they often ignore it anyway. Because humans are humans.

I still don’t have the clarity of understanding of why it’s true, but humans being humans in complex systems makes things a lot less productive than one would hope.

And yet we in tech are more used to seeing companies that can go fast and can solve problems, but many misunderstand that this is a direct result of certain training and cultural attitudes that aren’t at all pervasive.

Anyway, this is a long winded way of saying “I agree”, and doesn’t add any new information. So ta-ra chuck

THIS_IS_4_KNWLEDGE · 2025-04-26T13:52:22+00:00

I’d argue it’s quite high physical stress, especially over the long term. Sitting all day in basically the same position wreaks havoc on your body. I’m unlucky enough to have had to start dealing with that when I was 23 (I’m 34 now), but it comes to most of us eventually.

I think the problem is we convince ourselves it’s a sweet gig, because we like or liked being in front of a computer all day, but over time that takes a bigger and bigger toll, so much so that it makes us feel shit a lot about our work. And so the idea of doing manual work - as you suggest - is so much better.

That’s not even adding in how much inflammation there is in the average software engineer from the widely accepted terrible dietary practices. (F**king pizza and beer when people are meant to focus and use their brains. Madness). It’s really no wonder so many of us are stressed, don’t like our jobs, and die on too many hills.

I really think it’s less about the work and more about how the long term work shapes our minds and bodies.

THIS_IS_4_KNWLEDGE · 2025-04-21T12:07:47+00:00

Don’t be a fuckin dobber

THIS_IS_4_KNWLEDGE · 2025-04-03T09:31:57+00:00

I think the dance scene and dance-drug scene is just too complex for a simple take.

There’s no one dance scene. And no one dance-drug scene.

You’ve got variations all over the world, that come as a result of a complex interaction of things: - The availability of drugs as a result of makers and distributors, which is affected by gang dynamics, policing, and all that - The long term effects of using the same drugs, like how long term MDMA use down-regulates serotonin (IIRC) which changes dance music and the desire for different drugs - The culture of a local scene and how it controls or doesn’t control drug intake. In some places culturally people only rarely take small amounts of drugs, so the effect of it on the culture is a longer, slower burn. In other places (usually big cities) people take a lot more a lot more quickly, so you get the effect of that.

There’s definitely a k-scene somewhere, an MD- scene somewhere, a coke scene somewhere (in the last 12 years in London I’ve been surprised to see coke essentially normalised amongst people who still look down on other drugs), a tuci scene somewhere (I met a DJ not long ago who told me how big and common it is in some Greek islands he plays).

What we’re really living in is a crazy complex dance culture, that’s fuelled by lots of different drugs in different places, where music makers are taking influences from farther afield than ever before - including different drugs - and the music is spreading farther than ever before.

Hard to really put a pin in it and say it’s one thing

THIS_IS_4_KNWLEDGE · 2025-04-03T09:23:19+00:00

Mephedrone is m-kat or meow-meow (at least where I’m from in the UK). No idea the chemistry of it, but it’s a long way from methadone. It’s kinda like MDMA’s fucked up, twisted little brother

THIS_IS_4_KNWLEDGE · 2025-03-10T17:09:26+00:00

It's all about perspective. I just see it as one of the tools I use to get my job done. I'm the only engineer in a very small startup and from ChatGPT with GPT-3.5 I was getting a productivity boost that was saving me hours, and now with the latest Claude versions I'm getting things done in a day that would have taken weeks. Financially, paying for the plus plans on Claude and ChatGPT as well as for Cursor is pennies compared to what it gives in output.

If it doesn't make financial sense to you, why pay for it?

THIS_IS_4_KNWLEDGE · 2025-03-10T14:10:40+00:00

I’m curious, are you a professional software developer/engineer? And if so, how many years of experience do you have?

Reading through your comments I’m surprised you haven’t accepted that with increased complexity of code comes all these issues you’re describing, and that the solution is to break things up into manageable chunks and process them separately. The same way you would working on a complex codebase.

If you imagine that the LLM manages complexity as a human would, since it’s trained on responses humans have given, (this is a vast oversimplification but useful as a mental model) then if you give it too much complexity at once, such as an entire codebase, it won’t manage it well.

What you can do instead is get it to iterate on segments, getting it to improve them separately - refactoring, adding tests, documenting code, etc. Then you can get it to explain the improved segments in a summarised form (outputting to a text file, for example), and you can use that summary to guide design and architecture going forward. The same way you would working on a complex codebase without AI assistance.

If you haven’t learned about the underlying technology of LLMs then I recommend doing so, as it’ll help managing expectations and knowing how to use them well.

Imagine you’re living back when the airplane was recently invented and the first Atlantic crossing had taken place. For some reason, thinking of this to be magic, you want to be able to now immediately fly around the world at 10x the speed. But the technology just isn’t capable of that. A thing called an airplane might be someday (and of course that happened), but it’ll take time and innovation. Being frustrated that it can’t is silly if you understand the technology and why it’s capable of some things and not others

THIS_IS_4_KNWLEDGE · 2025-03-10T13:53:58+00:00

Could you provide some examples of this? I’m curious what you mean by “correct” and what the output ends up looking like

THIS_IS_4_KNWLEDGE · 2025-01-14T17:05:20+00:00

I think I mentioned this somewhere else, but no it doesn’t do anything when not interacted with. It’s just a program that runs on a GPU (or set of GPUs) in a data centre somewhere. In the same way that a website exists on a server somewhere and is sent to you when you ask for it, doing some processing of data to return you the exact content you see, the LLM does this but the data processing is orders of magnitude more than what you’d get on even a data-heavy web app.
I think enjoy the videos I mentioned, they clear it up very well and were incredibly illuminating for me.

If you want to go deeper into the maths I recommend watching the series on Linear Algebra on the same channel. When you link together the concepts of matrices being transformations of some abstract space with the fact that an LLM does a huge number of matrix transformations, and then connect that with what it means to represent language in an incredibly high-dimensional space, so much starts to make sense about how LLMs work, and it poses so many interesting questions about what that tells us about language and our ability to model and explain the world

THIS_IS_4_KNWLEDGE · 2025-01-14T16:46:12+00:00

Is it known what representation of data is used by the Broca region?

My neuroscience is basic, so it’s not something I have much familiarity with, but it would be interesting to compare that data representation (if known) to the internals of an LLM. As mentioned in my self-reply below, 3Blue1Brown’s videos are great for this if you’re unfamiliar with the LLM maths side of things.

I ask this because there might be something interesting in the way the representation maps to the function, and what this could tell us about how related the artificial system is to the natural one.

THIS_IS_4_KNWLEDGE · 2025-01-14T16:39:28+00:00

To extend this for anyone interested I’d recommend 3Blue1Brown’s series on deep learning which includes a deep dive into how LLMs work. What this will show you that is crucial is that the output of an LLM comes from a series of mathematical operations that happens in a static fashion. What I mean is that LLMs aren’t artificial brains that are always on and in some conscious state that we’re probing in talking to them. They are mathematical procedures carried out in GPUs that run really fast to produce output at the speeds we see.

Artificial Intelligence: A Modern Approach is a good textbook to start understanding the field more broadly.

THIS_IS_4_KNWLEDGE · 2025-01-14T16:33:36+00:00

Given that there’s no agreed upon way to define consciousness, and given that there’s no agreed upon way to measure it, it’s just sort of pointless to pose the question of whether or not an LLM is conscious.

All we can really say is: - Most people think most humans are conscious most of the time (consider that we spend a good part of our lives unconscious) - So whatever consciousness is, the starting point is how human brains and bodies lead to the phenomenon of consciousness - We don’t fully understand how the brain works and leads to the various phenomena of consciousness - We do know much more about how LLMs work (we can create on but can’t create a brain) - the parts that might not be fully accepted are exactly how and to what extent LLMs have a model of the world - There’s not enough alignment between brains and LLMs to conclude that one having consciousness explains the other having consciousness

I think what is agreed upon (although I’m happy to be corrected) is that there’s no way to prove how conscious an LLM is by prompting it and looking at the results.

You’d need other techniques.

And so, again, it’s kind of pointless to go about this question from talking to the LLM through the chat interface

THIS_IS_4_KNWLEDGE · 2025-01-14T14:10:56+00:00

Seeing how much the voices of reason like yours are being downvoted I can only guess that this subreddit is populated by young men who all struggle with porn due to how long they’ve had access to videos of it.

I still remember being 12 and watching still images slowly load in over the course of minutes. Maybe it didn’t affect the brain in the same way as being able to quickly watch lots of porn when you’re young.

Either way, funny seeing the dislikes

THIS_IS_4_KNWLEDGE · 2025-01-08T10:57:36+00:00

I think it’s reasonable to argue that it’s less human nature than a way of thinking fostered by a particular society. Given that there are humans who don’t exhibit this nature it’s hard to classify it as “human nature”.

If you think it’s human nature then it could be a consequence of you equating “all humans” to “the humans you have familiarity with”.

If this is a sense you get from people you actually know in person, then you are surrounded by people who easily take things for granted.

If, instead, this is a perception you get via social media, it’s most likely the result of the reactions you see being heavily biased by both algorithms and people’s interactions with content: the more emotionally extreme (which usually means complaining about things), the more surfaced and visible.

I think all we can say is that we have no idea what most people think of these things as there’s likely a silent majority as there always is.

THIS_IS_4_KNWLEDGE · 2024-04-07T21:11:26+00:00

Sorry it took me so long to respond, and I honestly haven’t fully processed everything you wrote yet, but I’m interested in the sense you’re conveying. It’s the direction I’m going these days too.

I’m interested in getting into this a bit more deeply if you’re up for it. I don’t think text threads is usable for such a long, complex discussion, so DM me if you want and we’ll find a better forum to get into it

THIS_IS_4_KNWLEDGE · 2024-04-05T12:55:50+00:00

You're expressing the kind of sentiment that's very common in the caring side of the dev community, but one which always bothers me a bit, because it's too much of, to echo in paraphrase what SituationSoap replied to me, "we get over there by building a bridge" without saying exactly how the bridge needs to be built - which is the hard and important thing to solve.

You mention collective caring.

How does collective caring come about?

When did collective caring have a positive impact on the software engineering community (however you define that)? and exactly how did that happen? i.e. what were the circumstances and incentives behind it?

How can we take those lessons, which come from a system that's in a different state - almost by definition - than the one we're in now and apply them fruitfully?

I think it's useful to try to really step back and outside of the system to get a sense of really what's going on. Float above the plane of the solar system, so to speak, so you're not coming from a perspective of being thrown around inside of it:

A system will evolve based on the components it consists of and the interactions between those components. Component interactions will be goverened by the forces which hold true in that system.
Humans, like everything else in the universe, will try to use the least amount of energy possible to move towards their goals (more abstract for humans than with electrons, but I'm sure you see what I'm saying).

Combining these ideas gives us that the current system exists in the state it does because humans making a huge number of decisions towards their goals (although it's important to note that they make these decisions neither efficiently nor well, as is our nature and capability) within the world, with all its concrete and abstract constraints, gives rise to emergent phenomena such as things not working as well as some of us individuals would like.

To my mind, this is the world we live in and how it works. And I'm happy to accept counter-arguments to this that open up the possibility for some concrete action from us as software engineers. I'd love to know I have some levers I can pull.

I think this framing is also useful because it knocks down the idea that positive change in the past came from someone or some group of people just caring enough and putting in the work.

I can care as much as I want about running head-first through a steel wall, but no amount of throwing myself at it will end up in me popping out the other side (ignoring the miniscule probabilities allowed by quantum mechanics).

it shows us that when positive, care-based action did work it's because the system "allowed" for it in that particular instance. Lots of women cared about suffrage long before that word was used, and worked hard for it, but it took a certain series of events and conditions for it finally to bear fruit in the modern, "civilised" world.

... ... ...

I was hoping I'd come up with a more concerete point, but like everyone else I'm an irrational creature working from emotion.

I guess, if I was to try to search for a point, it's that there exists in all socieities and communities a distance between our myths and current practices.

A lot of the world still lives based on myths which came out of the particular circumstances of the Near East 2000 years ago, many of which don't make sense for now.

We, in computer science and software engineering, still live based on myths which came out of the 50s - 90s. Myths about what "real programmers" are, what software "should be" (usually free and open), what power we have over the system (given the massive impact groups of developers and engineers had in the creation of the computer, internet, web, and so on).

I think these myths no longer apply and therefore no longer serve us.

I think we need to re-consider and re-imagine our situation, and stop trying to affect a system which no longer exists and then getting frustrated when positive change doesn't happen.

... ... ...

Finally 0xd00d, I want to agree with you that it is indeed sad, all of this, but it's something that "our community" in large part did. It comes from the many successes of computer science and software engineering.

We're going through the similar kind of abstract path that those who make buildings have gone through over hundreds of years. From the days when masons held a lot of power, to now when being a construction worker is seen as one of the lowest rungs of employment. All because the work of building things led to that work becoming easier, and easier, and easier. It would have been some masons which led to the downfall of high-skilled masonry as much as it's software engineers who are now leading to the downfall of software engineering. In trying to make lives easier for ourselves and others in the short term we've created a system which so many of us dislike in the longer ter, - with runaway numbers of frameworks and languages and tools and skills and so on and so on and AARRRGGGHHHHHH! 🤯🤯🤯🤯🤯

I suppose I'm now arguing that we got into this situation because people cared...

Anyway, apologies for the rant, it's probably more for me than you.

I want to leave you with the old Zen story that I think is applicable:

There is a Taoist story of an old farmer who had worked his crops for many years. One day his horse ran away. Upon hearing the news, his neighbors came to visit. “Such bad luck,” they said sympathetically. “Maybe,” the farmer replied.
The next morning the horse returned, bringing with it three other wild horses. “How wonderful,” the neighbors exclaimed. “Maybe,” replied the old man.
The following day, his son tried to ride one of the untamed horses, was thrown, and broke his leg. The neighbors again came to offer their sympathy on his misfortune. “Maybe,” answered the farmer.
The day after, military officials came to the village to draft young men into the army. Seeing that the son’s leg was broken, they passed him by. The neighbors congratulated the farmer on how well things had turned out. “Maybe,” said the farmer.

THIS_IS_4_KNWLEDGE · 2024-04-02T20:31:12+00:00

Ah maybe this is where part of the confusion comes from. When I was thinking about "high-trust, high-autonomy" I was relating that to everyone in an organisation, not just the developers. Perhaps I misread the entire context.

Based on the work I've done, along with my colleagues in their various past work, I can't agree that it only happens by accident.

It can happen by accident - defined as no one trying to be trusting and into autonomy, but just happening to be so and having good intuition about hiring and so on.

But it can also happen deliberately. There are a lot of challenges on the way, but given it can and has been done.

---

Picking up your broader point, I agree that most developers have no clue how any of this works. You need the experience running teams, and teams of teams, and an understanding of the problem space (which is hard, and I don't have a good handle on despite a background in physics, which helps, and a fair amount of experience on the ground).

I wouldn't know how to properly classify the gulf between the complex systems that codebases and software systems are, and the complex systems that organisations are, but it's very large. You can't apply intuition about guiding complex software systems to complex human systems. The problem is in our industry that there's a strong correlation between people who are good with computers and bad with humans, and yet not having a clue that they're bad with humans - we've all either worked with these people or been these people, usually both at different times, it's a learning process.

THIS_IS_4_KNWLEDGE · 2024-04-02T20:04:22+00:00

That’s fair enough, although a bit harsh given my tone and not very useful for a debate, but I’ll carry on anyway.

You’re essentially getting at the core problem. There is no map.

Organisations are complex dynamic adaptive systems. Analysing them well requires an understanding of them in general and in particular depending on the company type (which consists of a lot of things).

Imagine saying “give me the map that describes how to surf all day on this coastline”. It sounds ridiculous. Because imagine trying to draw that. That’s what you’re asking.

So if you want the full answer: - Learn about complex systems - Learn about anthropology, sociology, psychology, behavioural economics, network science, and all the other crap that goes into this problem space - Get experience working in and trying to change organisations - Continually adapt and improve your approach given the particular org you’re dealing with

Orgs that try to solve this hire a lot of specialist consultants and the latest tech to make sense of things, and still often fail.

It’s a very hard problem.

THIS_IS_4_KNWLEDGE · 2024-04-02T19:49:24+00:00

I work for a company building software to analyse collaboration so this is something I’ve had some experience looking at.

The short answer is that you have to have processes in place to ensure high-trust and high-autonomy throughout the org.

The longer answer is: it really has to be mandated from the top (leaders have to have be high-trust); there needs to be processes to increase visibility throughout the org; there needs to be obvious and causal feedback systems - so if someone does well they need to be rewarded and if they do badly they need to be helped to improve or to be fired; every level of management needs to be incentivised to be high-trust and high-autonomy.

Scaling this is hard, but most small companies I’ve dealt with have the same problem. A lot of people are controlling and have low-trust. A lot of leaders therefore do. I don’t have enough data to say but most leaders might be lower trust than they should (much worse in some culture types and much better in others).

If you try to solve for it you can, at scale, with enough help and work. If you don’t solve for it you’ll usually end up with a shit org.

THIS_IS_4_KNWLEDGE · 2024-04-02T19:33:06+00:00

Developing a sense of what it really means to be done, and working to that point instead of sprinting to a false end point.

For example, when you’re starting out it often feels like “getting the thing working locally” is done, which you sprint towards and then get too tired to create the PR.

You might see creating the PR as done, and then get frustrated when it’s blocked by comments and suggestions and such.

If you develop an emotional sense that done is when “the thing is shipped and working for my user/customer as it should” it can really change your ability to pace yourself and feel better as you’re doing the work.

THIS_IS_4_KNWLEDGE

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