r/techbootcamp

I started coding with just html, later discovered the thing ai coding , vibe coding agentic coding stuff. Tried to make a bigger project it sucks. Now vibe coding developed even better, people write several .md files to guide agent to do the work. But I was still ignoring it thinking why should recruiter hire non technical vibe coder than a technical guy. Cause a technical guy can easily vibe code.

Then recently I attended a mlh fellowship interview, I said the same thing. I am currently trying to avoid ai (agents ) for learning purpose just using ai for debugging , planning , guidence , testing codes. But the hr didn’t seems to be interested , she also asked technical questions like explain cascade delete all, I explained them well , but she mostly wanted to know show where you used ai. She wanted to know how I am using ai. Also in the rejection letter , it mentioned make complex projects. Assuming mine was a traditional SaaS project without any agentic coding.

So for my next interview preparation, what should I focus on? Those .md files for agents and write architecture there? Write several docs as par code? Don’t waste time on manual coding make big projects with agents ? No more SaaS , show them what I got with PaaS ?

Also I was about to start leetcode when I start college probably this January. Is grinding leetcode even worth it?

theres two different ways people use ai day to day either vibe coding, where you tell the ai what to build and never look at the actual code (in the case of a personal project or just training the AI and testing out), or regular engineering where the ai generates code but you still review and understand every part of it.

The thing is when an app gets complex enough. production apps depend on a lot of interconnected services, sometimes you have to fake account states or force certain code paths just to test something, and once multiple people are touching the same codebase at once in a team setting, its becomes hard to tell whats changed without actually reading the code, so past a certain complexity threshold, working at the code level directly ends up faster than clicking through the app trying to verify ai's work indirectly.

theres also pushback on the framing that code is an obstacle standing between you and the feature you want, the argument being that code is actually the value bc its precise, it tells you exactly whats happening instead of an ai generated summary that might not fully match reality, and its more concise than an ai over explaining some part of it.

Many people may have heard Nvidia's founder "ai wont replace you but someone using ai will" line that gets repeated everywhere, the take here is that this just hasnt played out, bc the software engineers who already have core engineering skills are the same ones learning to integrate ai into their workflow, so someone who only learns ai and skips learning to code ends up competing against people who have both skills, not just one.

Actually, ai researchers hype things up heavily on social media (I've already said this in somebody's post but founders of AI hype it so much for marketing, that's it), but the actual released models feel like incremental improvement day to day, not the dramatic leap the hype implies, with an honest disclaimer about not being qualified to predict how much better it'll get.

Personally, I don't agree with the idea that more efficient engineers just means needing fewer of them. People forget that tech companies are financially rewarded for growth, not for maintaining the same output with fewer people, so the incentive structure tends to push toward "same headcount, more projects" rather than "same projects, fewer people." and on the jobs narrative, theres a point about how layoffs get covered extensively in the news but rehiring doesnt get the same coverage, noting meta and google have both been rehiring for years after their layoffs and google's headcount is reportedly close to an all time high, which paints a less one-sided picture than what usually gets discussed.

To put it simply, learn ai and learn to code and learn to code before using AI or you'll pay for your lack of skill in other (perhaps more expensive) ways👍

There is this weird cultural myth in bootcamp and entry-level dev communities that "real developers don't write comments" and that all good code is somehow self-documenting. People that believe this often end up stripping their capstone projects of all comments in an effort to make their code look cleaner and more professional.

When in reality, lack of any context in your code is a huge red flag for any potential employer.

Code tells the reviewer what you did, but rarely why you did it

Hardcoding a 50 request per minute limit in your API without any comments is not a sign of a competent developer, it's a sign of someone that has no idea what they're doing. Having a comment in the code stating that you're limiting requests to prevent overwhelming the free tier DB by requests per minute shows business sense, it shows that you understand your own code. It would be like having a fully optimized and automated CI/CD pipeline with no documentation, it's just asking someone reviewing your work to waste time trying to figure out what you were thinking when you wrote it.

I have been using AI heavily for work, and at first it felt like a cheat code. I could get through tickets faster, automate annoying tasks, and spend more time on the actual engineering decisions. But now that the tools have gotten so good, a lot of my workflow has basically become "give Claude the docs, give it the ticket, hit enter." And because everyone has access to the same tools, the amount of work expected from us has gone way up too.

The weird part is that AI isn't just writing the code anymore. It's slowly taking over communication too. Requirements get turned into AI generated tickets, AI writes the implementation, automated tests check it, and then another AI summarizes what happened. Sometimes I’ll ask a coworker something and realize they just asked their AI, copied the answer, and sent it back. It’s efficient, sure, but somehow the whole process feels kinda soulless.

I never thought I'd miss sitting with another engineer trying to debug some cursed production issue or actually learning a system inside and out. Now I sometimes ship things that work perfectly fine but barely feel like I built them. I'm starting to wonder if we're optimizing software development so hard that we're accidentally removing the parts of the job that made people good at it. Is anyone else feeling this way?

I've been working in tech for a few years now. And one time, a younger dev on my team looked at my GitHub.

He asked why I don't have much personal projects there. I told him I don't code after work unless I need to. He looked surprised.

Some people are spending their evenings building SaaS projects, grinding LeetCode, or learning another programming language. But it's not in my vocabulary.

I used to feel kinda guilty about it, especially when I saw others posting their side projects and certifications.

I love coding, but I don't want to get my life revolved around it.

Maybe I'm just getting old where I just wanted peace after work. How about you?

I’ve been watching this for a while now. On Reddit, on LinkedIn, in job applications, in random conversations. There’s a whole group of people who proudly announce that they refuse to use AI in their work. Coding, writing articles, books, research, design — whatever. They say they stay “old school” because they want to remain original. They don’t want AI to “poison” their work. They write every line by hand. They do everything the pure way.

I used to find it mildly annoying. Now I just find it absurd.

A few months ago I posted a job looking for a coder, preferably strong in Python but open to other languages. One guy came in looking extremely qualified on paper — claimed he knew 15 languages, had a pile of certificates, the whole thing. So I asked him a simple question: do you know how to work with AI tools?

His answer came back almost offended. No. He is a real programmer. He writes every single line of code by hand.

I told him then I wasn’t interested. With AI I can get done in one hour what would take him a full day of pure manual work. I need efficiency, not some performance of purity. We didn’t work together. But the exchange stuck with me.

In 2026, if you work with code and you’ve never seriously used Cursor, Claude Code, Codex, local models through Ollama, or even just a strong chat interface with good prompting, something is wrong. Not knowing these tools is not a badge of honor. It’s a signal that you’re behind.

The efficiency reality most people refuse to admit

Take a concrete example. A complex landing page with HTML, Canvas, SVG, animations, responsive design — easily 2,000–3,000 lines if you do it properly. Writing that completely by hand takes real time. Hours. Sometimes a full day if you care about quality.

With a good model and clear direction, a solid draft can be ready in 10–15 minutes. Then you spend another 20–30 minutes cleaning, adjusting, making it actually good. Suddenly you can ship 8–10 of them in a day instead of one if you’re lucky.

That’s not a small difference. For freelancers, small agencies, or anyone running a real business, that difference is the difference between surviving and thriving.

The same logic applies to research. Doing a proper literature review or deep research the old way can easily eat two weeks. With the right tools and the right questions, you can get a strong first pass in under an hour. Then you still have to think, verify, and decide. But the “gathering straw” part is largely gone.

People still act like doing everything manually is somehow more noble. It’s not. It’s just slower.

The skill atrophy argument (and why it’s only half true)

I hear the counter-argument all the time: if you rely on AI, your skills will atrophy. You’ll stop understanding what you’re doing. You’ll become a prompt monkey who can’t debug anything.

There’s truth in that. If you just accept whatever the model spits out without reading it, without questioning it, without understanding the architecture, yes — you will get worse. Juniors who never struggle through a problem themselves are going to have a rough time later.

But the other side of this is almost never discussed.

I have never written a single line of code in my life from scratch the traditional way. Yet through working with AI I learned how to read code. I learned to recognize patterns, spot obvious errors, understand what a function is doing, and know when something looks off. AI didn’t make me dumber. It made certain skills accessible that previously required years of grinding.

I’ve also seen a 55-year-old man who barely knew how to turn on a computer. With AI he learned enough web design and e-commerce basics to take his old family business online. He built a shop. He started selling. Without these tools, that leap would have been almost impossible for him at that age and starting point.

So the real question is not “does AI risk making some people worse?” Of course it does — if used stupidly. The better question is: does refusing it make you better, or does it just keep you slow?

The hypocrisy is loud

Then there’s the pure marketing version of this.

You see authors on Amazon proudly stating “Written without any AI assistance.” Then you open the sample and the classic AI fingerprints are still there — the overly smooth transitions, the generic phrasing, the structure that feels a little too clean. Same with some “hand-coded” websites or “fully manual” research posts.

It’s the restaurant that advertises everything is made fresh to order… and then brings you a steak in five minutes. Everyone who has ever cooked knows that steak needs more time than that. The claim is just branding.

A lot of the “I don’t use AI” talk is the same thing. It’s a status signal. It sounds principled. It plays well in certain online circles. But dig a little and many of these people are using it anyway — they just don’t want to admit it because the pure image is useful.

The horse and the car

Refusing AI for daily productive work in 2026 is like insisting on traveling by horse when cars, buses, and planes exist. Yes, the horse still works. There are still situations where it makes sense. But choosing it as your default for getting from A to B is not a moral high ground. It’s just inefficient.

There are legitimate edge cases. Certain safety-critical systems. Certain artistic processes where the struggle itself is the point. Certain highly regulated environments. Fine. Those are exceptions.

For the vast majority of normal work — building websites, writing code for businesses, doing research, creating content, running a small or medium business, handling sales processes — treating AI as optional or somehow impure is self-sabotage.

I’m not particularly good at sales. So I’m building an agent to handle large parts of it. If I can’t do a task well myself, I can still design a system that does it. That mindset is available to anyone willing to use the tools instead of performing resistance against them.

The people still loudly rejecting AI are not protecting craftsmanship. In most cases they’re protecting their ego, their habits, or a marketing story. Meanwhile others are shipping ten times more, learning faster, and moving on.

The pure manual approach isn’t disappearing completely. But treating it as a superior default in 2026 is one of the more obvious ways to fall behind while congratulating yourself for it.

I’m reaching out because I keep hearing concerns about AI and what it means for the future of computer science and software engineering careers.

On one hand, we hear that AI will automate coding, reduce the need for developers, and fundamentally change the industry.

On the other hand, some argue that the demise of software engineering jobs has been greatly exaggerated—that AI will change the role rather than eliminate it.

So, what do you think?

Are we looking at the decline of traditional software engineering jobs, or simply the evolution of what it means to be a software engineer?

I’d genuinely like to hear perspectives from people working in tech, students, developers, hiring managers, and anyone currently building their career in this space.

For context, I am in the process of teaching myself Node.js. I stopped going to classes/dropped out of college in the middle of a semester at 20 for reasons unrelated to academics, and am now 24, regrettably with debt, so going back is not an option unless I am prepared to pay big money (based in US, sadly) *and* retake classes I stopped going to for the sake of my gpa (i am not.) At the same time, I am also not willing to change my desired career path. I am aware that, at this point in time, the web dev job market is extremely competitive- let alone without a degree. Let's say I go freelance, though- I make games, monetized websites, etc. I'd essentially be skipping the competitiveness of the field I may virtually have no shot at in one sense, though I understand that the consumer market can be incredibly volatile as well. Would it be reasonably more feasible than trying to go through the job market though? If not, is there a route I could take that will see this through for me, perhaps by means of creating unique and adequate enough portfolio projects that show my competence in order to stand a better chance within the job market?

Calling modern LLMs "glorified autocomplete" is like calling high-level programming languages "glorified assembly." You’re completely missing the forest for the trees. I keep seeing people in tech subreddits calling AI "boring" or "soulless" but honestly? It sounds like massive cope from engineers terrified of losing their edge.

AI hasn't destroyed the craft of software engineering. It just raised the baseline. If your entire identity as a developer was typing out boilerplate hunting down syntax errors etc. then yeah, you're going to feel threatened.

But for anyone actually building complex systems AI acts as a massive force multiplier for rapid prototyping debugging and automating the tedious parts of the job so you can focus on actual high-level architecture and system design.

The people whining about AI ruining tech sound exactly like legacy devs who complained that modern frameworks made programmers "lazy." It’s not going away and sitting around acting above it isn't going to save your career.

Am I the only one who thinks the anti-AI circlejerk is way more exhausting than the actual hype?

I’ve been working in software for a few years now, and AI has become such a normal part of my workflow that I barely think about it anymore, when I first started using these tools heavily, I was honestly impressed. They saved me hours of repetitive work and made it much easier to get through things like boilerplate, debugging, documentation, and small features. I got pretty comfortable with them and started building my own prompts and workflows around them, for a while, it felt like having a really good assistant.
But lately, I’ve been feeling pretty burned out by the whole thing.

I miss actually getting deep into a codebase. I miss arguing about implementation details with another engineer. I miss those random conversations where you learn something because someone has been dealing with the same weird system for five years or maybe I'm just burned out, but lately I've been thinking about doing something completely unrelated to software in my free time just to feel like I'm building and learning something again.

has anyone else reached this point where AI isn't making the job harder, but somehow it's making the job feel less satisfying?

The wages being offered for full-stack positions are getting downright insulting. Seeing listings offering $18 to $22 an hour for a full-stack engineer is absurd. I could literally go work at a local coffee shop or retail store for that same rate without any of the operational stress or technical headaches.

What pisses me off the most is the sheer breadth of skills they expect for peanuts. They want you fluent in React/Vue on the frontend Node or Python on the backend etc. basically doing the job of three separate people.

It feels like employers are intentionally exploiting desperate juniors and career changers who just want anything to put on a resume. If companies really think they can demand an entire engineering department out of one person for $20/hr they've lost their minds.

Is anyone else seeing these insulting offers?

Recently, computer science has been presented as an easy way to get huge profits, and an influx of people whose only interest in the field was their potential earnings occurred. Computer science used to be populated by people who enjoyed learning and creating things with technology and who were deeply interested in its development and principles.

As a result, the computer science job market now has an absurd amount of competition, which makes one wonder where all these people with a genuine interest, a serious foundation in CS theory, and actual projects to present came from

It is disheartening to see CS become so commercialized and competitive that one's passion for it no longer is the main factor in finding a job. It is easy to get caught up in the frenzy of trying to optimize your resume and to out-perform others in terms of buzz-word usage rather than simply enjoying the work you used to love.

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I’m a beginner trying to build a career in tech, and honestly, I’m extremely confused right now.

I’ve spent months researching what I should learn and which areas of tech actually have a future. I’ve watched countless YouTube videos, read Reddit threads, followed discussions on X/Facebook/Instagram, looked at job posts, and listened to advice from developers.

And somehow, the more I research, the more confused I become.

One person says learn backend development.

Another says software engineering is becoming obsolete because of AI.

Someone says learn Python.

Someone else says TypeScript/JavaScript.

Others say Go, Java, cloud, DevOps, cybersecurity, AI/ML, data engineering, etc.

Then I see posts saying:

«“Don’t get into tech.”»

«“Junior developers are finished.”»

«“AI will replace programmers.”»

«“There are no entry-level jobs anymore.”»

«“Software engineering is cooked.”»

After consuming all of this for months, I’m honestly getting frustrated and even somewhat discouraged.

But I want to know the reality.

Is the tech industry actually “cooked” for someone starting from scratch in 2026?

Or is the situation more like:

Tech is still a good career, but the easy path is gone and the bar for getting your first job has become much higher?

I’m particularly interested in hearing from senior developers, engineers, hiring managers, or people who have actually been working in the industry for several years.

I don't want another generic “just follow your passion” answer.

I want to understand things like:

- Is software engineering still a viable career for someone starting today?

- Are junior/entry-level opportunities genuinely disappearing, or is the internet exaggerating the situation?

- How much has AI actually changed the job market so far?

- If you were starting from zero in 2026, would you still choose software development?

- What areas of tech would you consider relatively durable over the next 5–10 years?

- What would you not spend time learning today?

- Is it still realistic to eventually work remotely for international companies, or is that becoming unrealistic for beginners?

- What should a beginner realistically expect in terms of time and effort before becoming employable?

I’m asking because I genuinely want to make a career in tech.

One of the things that attracted me to this field is that, compared with many other careers, you can start with relatively little money. With a laptop, internet connection, and enough time and effort, you can learn, build things, contribute to real projects, and potentially work for companies anywhere in the world.

That possibility still really appeals to me.

But I also don't want to spend the next 2–3 years learning something only to discover that the career path has fundamentally disappeared.

At this point, I don't need another list of 20 technologies to learn.

I need someone experienced to help me understand the bigger picture.

So, honestly:

If you were in my position — a beginner in 2026 with no professional experience who wants to build a serious career in tech — would you still go for it? Why or why not?

Please give me the reality, even if it's uncomfortable.

I would genuinely appreciate perspectives from people who are already working in the industry rather than predictions from people who are just watching it from the outside.

It's been incredibly hard to learn new things (not in the literal sense).

With the advent of LLMs and coding agents, it's become easier to get a grasp of something new—a new language, a new framework, a new tool.

But actually learning how these work, actually grasping the inner workings and knowing the how and why, is becoming more and more distant.

We all are working at a higher level of abstraction, which gives us a false feeling of competence.

I'm feeling very demotivated about learning new things. I start and pause, stop building new projects, stop learning new languages, stop learning system design, DSA, and everything else. Not because I don't feel they're important, but because I'm feeling utterly demotivated.

Do you guys also deal with this? If so, give me some advice on how to manage this.

Many rookies are put off by C ++, and this is unfortunate, because it is one of the best languages ​​to start with, even if you don't plan to be a C ++ programmer

Your understanding of what is going on at the machine level will allow you to write better programs in any language you choose. You will see that in languages ​​such as JavaScript or Python, memory management is handled for you, which means that you have to think about it less. However, the understanding of how things work will help you write better and more optimized code. It can be a steep learning curve, but once you've mastered it, you'll find that all other languages ​​are much easier to learn.

I finally signed an offer letter today for $60,000/year with full benefits.

Coming out of a tech bootcamp with no formal CS degree and only part-time blue-collar work history. I spent months feeling like I wasted my money listening to people say bootcamp grads are dead on arrival in 2026

After getting burnt out and grinding through dozens of applications in manic bursts only to face wall-to-wall denials having a young local company take a chance on me feels surreal.

If you’re a fellow bootcamp grad staring at a blank inbox please don't lose hope: target smaller, local growing companies where you aren't competing against the entire internet.

Anything I should know? Tips? From corporate culture to just what to expect from my first tech job? Any and all advice is welcome!

I graduated as a bootcamper 5 years ago before the AI craze and coding still had it's soul.

I used to genuinely love this craft. I loved the feeling of getting into a flow state wrestling with a complex architectural problem and writing clean, thoughtful code that actually solved something.

But over the last year or two the sheer saturation of AI into every single layer of this industry has completely sucked the soul out of the work.

I'm spending eight hours a day babysitting code generators prompt-engineering around bizarre edge cases and cleaning up subtle hallucinated bugs produced by tools that management thinks are magic.

Coding used to be about problem-solving and craft; now it's just endless mind-numbing code review for a machine that regurgitates slop faster than anyone can properly audit it.

To make matters worse, executive leadership has bought into the hype hook line and sinker. Expectations for sprint velocity have ballooned because "AI writes the code for you now," while code quality maintainability and actual system architecture are kicked down the road as technical debt for future devs to drown in.

I'm just exhausted. I didn't get into this field to be a human rubber-stamp for an LLM and for the first time in my career I'm seriously wondering if I even want to stay in tech long-term.

I’ve noticed a really frustrating trend during PR reviews lately, and it’s slowly driving me insane.

Whenever I leave a comment asking about a questionable design choice, a redundant loop, an unhandled edge case, or a blatant security risk, the response I get back half the time is literally: "Oh, Copilot suggested that."

As if that magically ends the conversation or absolves them of any responsibility.

It feels like people are completely turning off their brains, letting an LLM autocomplete entire blocks of code, and blindly opening a pull request without even reading what was generated. When you push code to a repository, your name is on the commit. You own it.

I DON'T CARE if the code was generated by Copilot, copied from Stack Overflow, or written by a senior dev if you open the PR, you are responsible for knowing what every single line actually does and justifying why it's there.

Copilot is a productivity tool, not a senior engineer you can hide behind when your implementation breaks down under review. If you can't explain why a piece of code is in your PR, it shouldn't be in the PR. Period.