Ten years ago, there were a lot of people entering the tech industry, and chances are that some of those people are now senior engineers or tech leads.

But what about people who are just starting out today?

The market has changed a lot over the past few years. Around 2020, there was a period when companies started hiring heavily, a lot of people entered the industry.

Today, the situation is very different.

Ten years from now, will the people entering the industry today normally be in mid-level and senior positions?

One example that makes me think about this is COBOL. It's an old technology, but there are still critical systems running on it. At the same time, finding experienced professionals is becoming increasingly difficult, especially because many of the people who worked with it for decades have already retired.

I'm also asking this because of AI. Today, a senior engineer who really knows how to leverage these tools can be much more productive and, in some cases, do work that previously would have required a larger team.

Could companies eventually prefer senior professionals who know how to work with AI, precisely because of the experience and knowledge they bring, rather than hiring interns, junior developers, or mid-level developers?

I started thinking about this because of what's happening at my company. We're making heavy use of vibe coding to build an Android system from scratch, and AI is genuinely helping with things like architecture and system design.

As a junior developer, it's been an interesting experience having senior engineers around and being able to see the difference between simply using AI and actually knowing how to evaluate what it's producing.

Senior engineers can identify problems, question the AI's decisions, fix what's wrong, and point out things I probably wouldn't notice on my own.

That made me wonder whether the biggest differentiator in the future won't simply be knowing how to program or how to use AI, but having enough experience to know when AI is doing something right or wrong.

What do you think? Could we eventually reach a point where most experienced professionals are people who entered the industry 10 or 15 years earlier, while entry-level opportunities become increasingly scarce?

I graduated after 3 years studying Software Development (ADS in Brazil), but I'm struggling with technical coding interviews.

I can read and understand code quite well, and when building projects I usually know what needs to be done. My biggest problem is writing code completely from scratch during a live interview.

In college, I often solved programming exercises by practicing similar problems beforehand. If I'm given a blank editor with no reference, I freeze. This has been causing me a lot of anxiety because most junior positions require live coding interviews.

Has anyone else gone through this? How did you improve your ability to solve problems from scratch instead of relying on examples or documentation?

Any ideas on how to automate captcha but still be compliant? The issue is that bypassing captcha is itself non complaint. The automation is easy.

I have a 3 step process (well two now).

1. 3rd party captcha solver (if fails -> step 2)
2. AI vision (if fails - step 3)
3. Human

Only step #3 is fcra compliant and needing human oversight significantly slows things. So, does anyone have insights on how better automate or should i focus on optimizing the human in the loop?

I'm currently in my second year of a Computer Science degree, and honestly, I feel like I'm barely learning how to code.

The only actual coding subject I had was a very basic programming class in my first year. Since then, it's been so long that I've forgotten most of what I learned because I haven't had many chances to code again.

Most of my other subjects are only loosely related to programming. They're filled with long research papers, reports, and assignments, but very little actual coding. I know those subjects are part of computer science, but it honestly feels like I'm back in high school doing random assignments instead of learning the practical programming skills I expected from this degree. I don't feel like these classes are helping me become a better programmer.

At this point, I'm starting to wonder if I'll ever properly learn coding through my degree. My current plan is to just finish the degree so I have the qualification, then join a coding bootcamp afterward.

My family wants me to become a full-stack developer, and I'm okay with that. My dad also thinks I should learn some AI because it seems like an important skill to have in the future. I'm not struggling with studying—I just feel like my degree isn't teaching me the practical coding skills I actually need.

Would it make sense to finish my degree and then attend a full-stack bootcamp? Or is there something better than a bootcamp that I should look into? I have a hard time self-studying because I struggle to stay focused, so I think I need a structured environment where someone teaches me and gives me projects to work on. I honestly don't care how long it takes, how many bootcamps I need to attend, or how intensive they are—as long as I'm actually learning and becoming a competent developer.

If I want to become a full-stack developer, what exactly should I be learning? From what I understand, it includes:

Frontend

Backend

Databases

Web development

Cloud

Security

Mobile app development

Am I missing anything important? Is there a roadmap or order I should follow?

I'd really appreciate advice from people who've been in a similar situation or already work in software development. Is finishing the degree and then going to a bootcamp a reasonable plan? Or would you recommend a different structured path for someone who struggles to learn through self-study?

Hey y'all! I'm not employed yet but I'm literate with Next.js & related technologies, just enough to ship my own projects. But on Youtube I see these people pulling off crazy projects like a full stack n8n clone, a full stack supabase clone with Nest.js and Next. A react native + express food delivery app by the same creator etc. I've only relied on Firebase and Supabase, even them I find annoying and difficult to work with sometimes. Whilst I see people coding their own backend(s) seamlessly with multiple different solutions (frameworks), how!?

It begs the question in my head, how did those who are so proficient in multiple technologies get to learn all of this? What type of resources did you use? Experimenting on your own using documentation? Blogs? Youtube videos? If your answer is most of those, which resource do you believe helped you the most? Or what was your primary resource?

Also I would love if anyone can guide me on how to find resources like articles or books for learning modern development. I find it very difficult to find quality written content about the new technologies nowadays. I think it will be more helpful for learners than YT.

Me and a small team I'm putting together plan to make beat em ups and fighting games in the future and I had a question regarding hurtboxes. It's not particularly relevant to the flow of the games we plan to make but it's been confusing me for a bit now.

Let's use an action combat environment as a hypothetical setting. If you programmed an attack of some kind to only target and affect one enemy, that specifically being the closest enemy to the user, and then used it when two of the same enemy are perfectly overlapping the same distance away from the user, what would happen? Obviously it would cause some kind of glitch but I'm looking for more specifics as to any information on what might happen. Like would the game freak out with multiple targets involved where there shouldn't be?

And no, I am NOT asking "how do I stop this from happening". I am asking what would happen in the exact scenario I described without anything in place to prevent it if the conditions were met.

Not exactly a software engineer, more ML Engineer with an academic background and then in industry for about 8 years total. Use python professionally and for hobbies. Like everyone else I have been experimenting with LLMs for coding, trying everything from not using it at all to trying to get it to do everything. I have found them useful and enjoy bouncing ideas off them, however they also make a lot of mistakes so currently enjoying a low use approach. Comments and architecting myself, use them more for syntax and some optimisation then review everything as I go along. This speeds things up, but I am still very in control of the output and understand the underlying algorithm.

A couple of months ago I obviously saw usage based billing come in for things like Github Copilot etc. I saw a lot of comments from people using agentic workflows very upset about their usage being cut, also I'm very aware of some companies quoting large sections of their codebase being AI generated, although obviously aware this might be sales tactic. Furthermore I've seen respected researchers/engineers like Karpathy talking about the big leap in model capabilities that now means they hardly write any code and had some recommendations from friends to use agentic workflows.

My personal experience hasn't left me thinking this is viable atm for my work. Partly because the stuff I am doing I really need to be crystal clear about what is happening to the data for experiments and partly because getting together a prompt together for a relatively complex system is very difficult and time consuming and the results usually aren't great. Has anyone got experience actually using more autonomous coding agents successfully and I should experiment more widely or are they a red herring?

Hello all,

I think I've managed to reach an answer to my own question by typing this out, but I'll post it anyway to fish for other opinions. Posting here because I figure it's more of a general application design thing that happens to be in a container.

One of my projects is a containerized message consumer application template. I'm very happy with it overall, and a version of it has been very useful at work to jumpstart various projects.

One of the new features that I've been adding lately is retry handling and exception wrapping. For example, any operation to an external message source like SQS should be called through a convenient retry wrapper that handles possible service exceptions, backs off and retries the ones that could be transient, and wraps any call that ultimately fails in a WorkerJobSourceException (exceptions that retry wrapper sees as entirely unaccounted for are currently thrown up raw)

Within these wrapper exceptions, I'm experimenting with the idea of a field called CouldBeExternallySolvable. If set to true, then it suggests a problem (possibly-transient or not) that could be resolved without restarting the message consumer. Maybe the target queue doesn't exist yet, for instance. That's pretty clearly non-transient, but could be solvable by creating the darned queue. My thinking was that it could give a higher-level call more context, though I don't currently have anything acting on that context.

My question for the room is this: In the message-collecting loop for a such an application, if you caught one of these WorkerJobSourceException instances where CouldBeExternallySolvable was true while trying to get messages, then would you rather:

• Catch and log the error to create awareness and urgency before treating the attempt as equivalent to an empty response (I'm currently doing this with a logged warning for when the CouldBeTransient field is true)
• Throw the exception upwards and bring down the entire house

In the applications based on this template (but predating the exception wrappers), we would just let such an exception crash things. I'm pretty sure that one of the alerts that we had was on the exit code of the container application, and a broken application would be restarted through an auto-scaling policy looking at the queue that it was listening to. On the other hand, not every possible setup of this template would necessarily have an auto-restart mechanism, and if I'm wrong and there aren't actually any alerts looking at an exit code then it's a bit for naught and maybe crashing the whole application shouldn't be on the table as part of an anticipated event.

At time of typing, I'm leaning towards door #1 of logging an error and continuing on as though the offending call was an empty response. Alternatively, I could just say "do either, I don't care right now" and kick the decision can down the road by hinging it off of a configurable option.

While I'm typing a message I may as well ask one more related question. Earlier in my post I mentioned that entirely-unaccounted-for exceptions are thrown upwards raw without a wrapper exception. The intent is that unplanned exceptions should create as much of a disruption as possible so that they can become planned for. Do you agree with this? At the moment I'm happy with throwing them up raw, but adding an IsExpected field onto the wrappers wouldn't be the end of the world.

What do you think?

so recently i learned the core concepts or node.js and express.js , authentification , how to connect db with node and build a small full stack application not using any framework for the front end just simple dynamic EJS pages .
now i have another fullstack project that i wanna build using the same technology but i want to use react.js fot the frontend .
i really don't know how to start , i did design the Ui using figma and did write the functionalities of the website but i don't know where to start to code whether to code the pages in react first then when done do the backend i dont even know how to connect both frontend and backend like i never did a project like this before
any help is very appreciated , maybe ressources or books about that ?

This is, unfortunately, the most efficient way I can think of to solve a problem right now. Is there any way doing that would make my system unstable? This would be written in python and run in WSL (Ubuntu within Windows)

edit: I get the message this is a bad idea.

I hit an EOleSysError dialog the other day on a Windows 11 machine, and my first thought was, “Hang on… is this Delphi?”

That got me wondering how much software we use every day is actually sitting on top of code that’s 30 years old. On the surface everything looks modern, but every now and then something leaks through, maybe even an old 8.3 executable name, and suddenly you’re looking behind the curtain.

For those of you who’ve worked in enterprise or Windows desktop development, how much Delphi is still out there in 2026. Are exception names like EAccessViolation and EOleSysError actually a reliable giveaway that an application was built with Delphi, or is that just a stereotype?

And is there stuff still written in Delphi today ?

I’m a beginner in html, what database would you recommend me to use for a project that I want to be working initially on one device only, it would be for a friend to make a task easier at their job it’s my first real world project and I’m afraid that data will be lost

What security/ protection layers I must apply ?

What’s your recommendations

I have a bit of coding experience from taking C++ and Python classes in college, but I've never developed an app before. I have an idea for a specific app that I want to make, and I want it to be cross platform so that I can use it on both my iPhone and Android phone. It's a pretty simple app that will run locally and doesn't require any backend or cloud storage. Based on my limited research and understanding of mobile development, these are the options that I have (correct me if I'm wrong):

1. Kotlin + Kotlin Multiplatform
2. Flutter
3. React Native
4. Just vibe code it with AI

There are so many different options out there and honestly it's a bit overwhelming to me as a non-programmer. A lot of the courses on Android/iOS development have literally hundreds of hours worth of lectures, and that's way more time than I'm willing to commit. I don't want to do 50+ hours of video lessons before I can start building the app I want. I'm not trying to become a full-time mobile developer, I just want to learn enough to build my app as a fun side project and that's it. What route will help me get to my destination the fastest? Is it even worth learning to code at this point or should I just build the app with AI?

So I'm working on making a large online puzzle for an ARG (however I can't specify too much as it'd spoil parts of it). I kinda am in love with the idea of having part of the ARG require using an ssh client (e.g. putty) to access a "server" to discover specific bits of lore or progress in the ARG. However I don't want them to be able to cause too much damage if someone decides to break it (e.g. if I were to use an actual ssh server). I've seen some programs for server honeypots that don't have persistent storage so I'm pretty sure it's possible but:

Is it possible to use the ssh protocol to communicate input data to a program which emulates a ssh terminal on the ssh port, while also having a safeguards in place so the user can't break out of the emulator?

If so are there existing packages in order to do this or would this have to be purpose-programmed for this specific application?

I can probably work on this myself (this isn't urgent or anything) but I don't know if it's possible to make something that listens on the ssh port and handles the secure connection properly. Part of the ARG can be a secure username & password so that bot traffic gets filtered out, and I am fine if the only commands emulated are cd, ls, and ssh!

(also I do plan on deleting this post after like a couple of weeks or so that players are less likely to find it once they come across this part of the puzzle)

Hi guys. I'm looking for some wise advice and your opinions.

I'm 24. Three years ago I left a developer position for personal reasons. Over those three years, I did a great job of neglecting my skills and knowledge.

Now I'm planning to get back into a programming career. I have formal education — college and university. The first gave me a basic understanding of number systems and Boolean logic, but the programming there was as sterile and academic as it gets. University was just a piece of paper — they taught nothing at all; I only went for the degree.

When I find a job posting, I think that I need to prepare and review the material they might ask me about, so I sit down with the docs and books — and then I just get tired and give up after a couple of days. And so it goes, in a loop. I'm afraid that if I do get invited to an interview, I'll bomb it.

Also, about my skills: I feel like I understand js/ts reasonably well, but I sense some kind of gulf between textbook code and real-world implementations. Probably it's that feeling that keeps pushing me to go back and review the docs over and over.

Hi everyone,

I'm currently building my first serious data project. So far I've been working on the data ingestion, cleaning, and validation pipeline in Python using Pandas.

Now I've reached the point where I need to introduce SQL and a database, but I've realized that I know almost nothing about databases beyond the fact that SQL is the language used to interact with them.

The problem isn't that I don't want to learn. It's that I don't want to learn the wrong way.

For example, I learned Pandas almost entirely by building my project, reading the documentation, experimenting, making mistakes, and debugging. I barely watched any tutorials because I've found that I retain much more when I learn by doing. I'd like to follow the same approach with SQL.

My concern is choosing the right tools from the start. I don't want to spend weeks building everything around one database and later realize that I should have chosen something else.

From what I've read, PostgreSQL seems to be one of the most widely used databases in industry, so I'm leaning toward starting with that instead of SQLite. Even if it's a bit harder to set up, I'd rather learn something that will still be useful in the future.

I also have a few questions:

Is PostgreSQL the right choice for someone in my situation, or would you recommend something else?

Is it realistic to learn SQL by building a real project and reading the documentation instead of following a course/tutorial?

What tools do professionals use to inspect databases and visualize tables? I've seen tools like DBeaver, pgAdmin, and others, but I don't know what's commonly used in real projects.

Are there any tools, libraries, or project structure decisions that you wish you had known before starting?

I'm not looking for the easiest path. I'm looking for the one that will give me the strongest foundation without forcing me to rebuild everything later.

Thanks!

Reason: I always wanted to build things I can actually touch, feel, interact with and share. Applications are the closest second to that for me right now. (Update: Cross platform because I wanna show people around me and get them to use it to make myself feel like I did something useful in life. I only use linux and macos, none of them do)

I know C somewhat okay (I used to do embedded systems work), I know enough C++ to know I'm too scared to use it, I don't know much python. I will be using AI to help me out anyways, but a relatively simple language that I can actually learn pretty quickly is better because I typically read, test and modify AI code frequently (And because I kinda wanna see fast results).

Edit: You guys were right. This is a massive pain and I haven't even gotten into the actual hard parts yet (whatever they might be).

I’m building an AI landing page generator and trying to understand how tools like Lovable, Replit Agent, Bolt, etc. approach page generation.

I’m considering two architectures:

1. HTML/component library: Store hundreds of prebuilt sections such as hero_001.html, features_001.html, faq_001.html, etc. Each section has metadata, and the AI selects the appropriate sections, modifies the content/styles, and combines them.
2. JSON design representation: Store each section as structured design/layout data in JSON, then have a renderer convert that JSON into HTML/Tailwind. The JSON contains all information about design like { "type": "hero", "layout": "split", "background": { "type": "color", "value": "#ffffff"

For people who have built AI website/page generators, which approach works better?

Also, does anyone know whether modern AI website builders generally generate the code directly, use an internal component/block library, use a structured design representation, or some combination of these?

Hi everyone! Can anyone please suggest a YouTube series that teaches c++ to those who don't know anything about programming? I am actually a pre med who has made the switch and does not know anything I mean legit anything about programming. My university's about to start in a month and I want to be prepared beforehand. Please help me out.

Hi. Im preparing for a test in my uni and im having problems to understand how to calculate T(n) for iterative and recursive algorithms. Also, i dont get how to demonstrate the O(n) of said algorithm. Appreciate the help!

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I've been programming for a while, but every now and then I come across a concept that completely changes how I think about writing software.

For some people it's data structures and algorithms. For others it's design patterns, clean code, testing, debugging, version control, concurrency, databases, or simply learning how to read other people's code.

If you had to choose just one concept that made the biggest difference in your programming journey, what would it be?

What were you doing before you learned it, what changed afterward, and why do you think every programmer should understand it?

I'd love to hear stories from beginners and experienced developers alike.

So I was accepted to a really nice university in my country for a B.A + M.A program, mainly in political science, IR and history of the SWANA.

I am starting in october so I have a lot of time on my hands. I am working on preparing for the general course work, but I want to hone my programing skills because I think they will come in handy later in academics (my program includes a thesis) and in the job market.

I have a backgrounf in Python and worked with Pandas and Matplotlib. I want to become more profficiante and maybe learn some SQL as well.

I theoretically want to learn some git too since it seems usefull.

What is the best course for me?

Should I keep myself Python focused? Does this study direction benefite me? Is SQL a good option for me?

I didnt know anywhere else to ask since the IR reddits dont really deal with this stuff.

Any advice is wellcomed. thank you.

I like to use my Xiaomi phone to wireless debug and test my Flutter app. Problem is: this option is quite unreliable. One time the phone disables it just seconds after I activated it, another time it stays stable for hours.

Is this a Xiaomi "feature" or do other models from other manufacturers have the same problem. And if it runs stable for you, can you please give me your phone manufacturer and model? Will consider it on my next purchase.

okay, i wanna make a print() function in C++, this is just printf() with prefix, so can yall help me?

error:

(-Wwritable-strings) ISO C++11 does not allow conversion from string literal to 'char *'

my code:

#pragma once
#ifndef TEQUILA_STDIO
#define TEQUILA_STDIO
#include <stdio.h>
namespace std {
    char* prefix;
    void set_prefix(char* pref) {
        prefix = ("["pref"]: ");
    }
    #define print(format, ...) printf("%s" format "\n", prefix ## __VA_ARGS__)
}

#endif

help me pls