not talking about the obvious stuff everyone already argues about, more like the thing that quietly bugs you when you're actually working in the industry. could be data privacy, ai replacing jobs, companies cutting corners, whatever you've noticed firsthand
Most AI posts here are either “AI will replace us” or “never use it, protect your fundamentals.”
But we also need to talk about the middle ground, which is what actually using it looks like on the job without losing your ability to think through problems yourself.
Here’s what’s worked practically base on exp:
•Use it to understand, not to finish When you’re stuck, ask AI to explain the concept behind the problem, not to solve it. You still write the solution. The understanding stays with you, the shortcut doesn’t.
•Use it for the boring parts, not the thinking parts Boilerplate, repetitive syntax, formatting, documentation. Offload that. The actual logic, architecture decisions, debugging your own code, that stays yours. That’s where the skill builds.
•Test it like a tool, not a source of truth AI gets things wrong, especially on newer libraries or edge cases. If you can’t read what it gave you and explain why it works, you don’t actually have a solution yet.
•Use it to get unstuck, not to skip being stuck Being stuck is where most of the learning happens. AI is useful for getting past a wall after you’ve actually sat with the problem, not as a first move the second something gets hard.
Junior devs who are going to struggle aren’t the ones using AI, they’re the ones who can’t work without it the second the internet goes down. Do not rely too much on a.i and make sure while using it u are still learning manually.
i'm starting to think that's the wrong question. AI can already generate code, explain APIs, refactor functions, and even fix bugs surprisingly well. but the more code we generate, the more we have to understand.
Someone still has to decide if the architecture makes sense. Someone still has to review trade-offs. someone still has to catch edge cases, think about security, figure out why production broke at 2 a.m., and decide whether the AI's solution is actually the right one.
in a weird way, AI doesn't just generate code. It generates more responsibility. The barrier to building software is definitely getting lower, and I think that's a good thing. More people can prototype ideas, learn by doing, and ship projects that would've taken weeks before. but lowering the barrier to writing code isn't the same as lowering the bar for good engineering.
Maybe that's the real shift.
Less time fighting boilerplate.
More time making decisions.
I'm curious whether other people are seeing the same thing, or if you've noticed AI changing the way you work in a completely different way.
I spent two decades in brand marketing at companies like Bacardi and Toyota. I cannot write a for loop from memory. Last year I decided to build my startup’s platform myself instead of hiring a dev shop, and today it’s live in production with paying customers.
The stack, all built through Claude Code and Replit: React/Tailwind frontend, Node/Express backend, PostgreSQL, AWS S3, FFmpeg, Sharp, OpenCV, TensorFlow.js, plus the Claude API in the product itself.
What actually worked for me:
Treat Claude like a senior engineer you’re managing, not a vending machine. My best sessions started with me explaining the business problem in plain English, asking Claude to propose 2-3 architectures, and making it argue against its own first suggestion before we wrote anything.
One feature per session. When I tried to do too much in one conversation, quality fell apart. Small scoped sessions, commit, new session.
Make it explain the code back to you. I don’t merge anything I can’t describe in a sentence. This sounds slow. It saved me weeks, because when things broke at 11pm I actually understood my own system.
Where it hurt: video processing pipelines. FFmpeg flags are a nightmare and Claude would occasionally give me confident answers that were wrong for my specific codec situation. I burned about two weeks on a memory leak in the processing queue that a real engineer probably spots in an hour. That was my tuition.
The uncomfortable truth: I still brought on a part-time CTO to review architecture decisions. AI got me to a real product, but I don’t pretend I have no blind spots.
Happy to answer anything about the workflow, costs, or the moments I almost quit and hired an agency.
I feel that over the next 10 years, as AI continues to advance, people in the tech industry will have greater opportunities. At the same time, AI may negatively affect jobs that can be easily automated or managed by AI, leading to fewer opportunities in those fields.
Any thoughts about this? Planning to explore my career in tech world.
i dont get it. this kind of tool seems built to let companies get more work done with fewer people. if one engineer can now do the work that used to take several, that doesn't sound great for headcount, salaries, or job security. it increases competition while giving companies even more leverage to expect higher output from everyone. i'm already feeling that pressure myself. what am i missing???
if your graduating from a bootcamp right now and just spraying 500 apps on linkedin hoping for the best your completely wasting your time. the market is way to brutal for that now since AI can basically write all the basic junior boilerplate code in two seconds anyway, so companies dont want to pay someone just to type syntax. if you want to actually get noticed you have to delete all those generic tutorial clones and to-do lists from your portfolio because hiring managers are totally sick of seeing them. instead you need to build one single app that solves a real world problem and actually document the friction in your readme file. talk about what broke, how you debugged it, and why you made certain database decisions because showing your actual problem solving process is way more valuable than just showing a finished app that looks like everyone elses.
find a few local compaines you like, look up their engineering leads on linkedin, and just ask them for a quick chat to get feedback on your code. when you show up looking for advice instead of begging for a job you end up building real human connections, and thats the absolute fastest way to bypass the resume black hole and actually get hired.
I'm 21 years old and planning to pursue tech with the goal of becoming a software engineer. Before I start, I'd like to prepare as much as I can. What subjects or materials should I study to help me catch up and build a strong foundation? Any recommendations for books, courses, or topics would be greatly appreciated.
I work at a VERY AI-forward company and our products exist at the forefront of the capabilities of current models. My total comp is probably around $200k, but I'm going to be giving all that up in order to land a career in a different field that has lower potential of AI taking my job.
Some of you might have differing opinions of how all this will shake out. To you, I would say until you've worked at the forefront pushing the limits of agentic AI everyday, you opinion will inevitably be skewed thinking "AI could never do my job." I have a feeling I'll end up having to argue my position regardless in the comments with those who are desperate to convince my their 80 IQ is more useful than Claudes 140+.
In any case, I went back and forth between career options. I didn't want to go back to school, but still wanted a high income potential. I also wanted something where I could work for myself at some point. Finally, it had to be something I was passionate about. I eventually landed on personal trainer.
I started my cert and will be finished in the coming weeks. Once I have that finished, I plan to use a portion of my savings to open a small studio in an affluent area.
To those of you worried about the longevity of the field, consider this: regardless of if the field continues to exist or becomes extinct, is it worth continuing in a job where all you're doing all day is telling a robot in plain english what to do? Personally, I find it extremely unfulfilling.
EDIT: To those claiming there won't be people to afford PT if AI takes white collar jobs, think again. Middle managers will be safe — they'll be the ones prompting. Blue collar jobs will be safe and will likely boom. Single-person businesses that were impossible before are now possible. Basically anything that requires any real person-to-person communication is safe (HR, sales people, etc). It's just us IC's that are going to be gone.
okay so Fable 5 is literally back as of today. July 1. three weeks offline and it's finally live again on Claude.ai, Claude Code, and Claude Platform after the Commerce Department quietly lifted the export controls yesterday.
here's the thing though. the reason it came back is just as wild as why it got pulled in the first place. Anthropic basically had to build a new safety filter that blocks the specific jailbreak Amazon researchers found, the one that let the model flag vulnerabilities and spit out exploit code. the downside is it'll also flag some normal coding and debugging work as false positives, so enjoy that.
and yeah Anthropic had to make some promises to get the keys back. earlier government access before future launches, proactive security monitoring, reporting any malicious use they spot, and working with Amazon, Microsoft, and Google on shared standards for rating jailbreaks. OpenAI did the same thing on their end, actually held back GPT-5.6 from public release at the government's request and limited it to vetted partners only.
the real reason Washington backed off though is China. Chinese models have zero export controls. they're open weight, they ship instantly, and anyone can use them. every single day Fable 5 stayed offline was another day companies had a reason to just switch to a Chinese model instead. the government did the math and decided that was worse. so this is just the new normal now apparently. frontier model launches aren't really launches anymore. they're negotiations.
A few years ago, I was completely at rock bottom. I was dealing with homelessness, had no vehicle, and was literally sleeping in my young niece's bedroom just to keep a roof over my head. I had absolutely nothing left to lose, so I decided to take an insane gamble on myself and enroll in an ultra-intensive tech bootcamp. To keep my head above water and pay for basic necessities while studying, I spent every single spare hour driving for Lyft, completely burning the candle at both ends just to survive the grind.
The program was a brutal, overwhelming sprint, but within just two months of finishing up, the hustle actually paid off and I managed to secure my first six-figure role in tech. Since then, that initial breakthrough has completely flipped my life script, my income has grown past a quarter-million dollars, I’ve upgraded to a luxury high-rise condo, and I finally have the financial security and the vehicle I used to only dream about. I wanted to share this because I know exactly how suffocating it feels to start from absolute zero, but it is entirely possible to change your reality if you treat the learning process like a literal rescue mission.
genuine question.
everywhere i look, it is always the same. ai is replacing jobs. ai is eliminating entry-level work. ai is making entire careers obsolete. every day there's a new prediction about which profession is next. i'm not even trying to argue whether those claims are true or not. i'm just tired of consuming endless doom.
if ai really is going to change the job market that much, what are people actually doing about it? how can we get ahead of it?? and i'm not looking for motivational answers like "just keep learning" or "humans will always be needed."
I’m currently grinding through an intensive coding bootcamp and I feel like tools like ChatGPT, Copilot, and Cursor are becoming a dangerous double-edged sword for my learning. On one hand, they are amazing for instantly unblocking me when I’m stuck on a weird framework error late at night; on the other hand, I can actively feel my brain getting lazy because it's just too easy to copy-paste an AI-generated code block without truly processing why it works. My main purpose for writing this is that I am genuinely terrified I’m destroying my core problem-solving fundamentals, which is going to leave me completely exposed and helpless when I have to face a live technical interview or a real-world on-the-job bug where I can't just blindly prompt an LLM for the answer. For anyone who has successfully navigated an intensive dev program recently without letting your coding skills rust, what strict boundaries or prompting guardrails did you put in place to ensure you were actually learning instead of just coasting on a crutch?
the tech roles holding up right now share one thing. they require judgment in situations AI has never seen before, accountability for real outcomes, or human context that can't be prompted into existence. cybersecurity is the clearest example since attackers adapt constantly with methods that didn't exist last month and you can't automate the intuition of someone who thinks like a threat actor. software architects and senior engineers aren't going anywhere either because AI can generate code but cannot decide whether your architecture will scale, whether the trade-offs you're making now become technical debt in two years, or whether what you're building actually solves the business problem. product managers sit in rooms with clients who don't fully know what they want and extract actual requirements from what gets said. that combination of judgment and human reading of a room is not promptable. AI and ML engineering is the fastest growing category with postings up nearly 60% from 2020 levels because someone has to build, audit, and improve these systems.
the salary data makes this concrete. workers with AI adjacent skills are earning more than peers in identical roles without them. AI integration specialists and trainers are pulling between $95,000 and $200,000. the highest paid aren't pure technologists, they're people who combine AI fluency with deep domain knowledge and the judgment AI keeps failing at. the pattern is consistent across all of these roles. if a job is predictable and rule based AI automates it. if it requires reading a situation that has never happened exactly this way before, the human stays.
Feels like something new drops every other day and half the stuff i learned last year is already outdated lol. Between AI tools, new frameworks, and whatever else is trending this week, it's basically a part time job just trying to stay in the loop. What's actually working for you guys, any go-to newsletters, youtube channels, or subreddits you trust? Or are you all just winging it like me and hoping you don't fall too far behind
unless you're working on the field right now, stop saying SWE jobs is over and that ai has replaced it. it feels like every discussion about AI eventually turns into a prediction that software engineers won't be needed much longer. it's a lot of help to ease work but it doesnt attend meetings and fix problems by itself. maybe ai can help write code faster, but writing code is only one part of the job. most companies are still dealing with complex systems, technical adjustments and years of accumulated decisions that cant simply be solved with a prompt.
Every time someone asks if bootcamp is still worth, most comments are saying market’s dead, 2023 ruined it, don’t bother. I wanted to actually address what changed and ask if the “it’s dead” take holds up.
Let’s talk abt it.
What actually changed since 2023:
The decline isn’t really a clean “2023 ruined it” story, it’s been compounding. Layoffs hit hard starting late 2022 into 2023, almost 263,000 tech workers lost their jobs in 2023 alone, which full the market with experienced engineers competing for the same junior roles bootcamp grads target. AI coding tools also progress into a lot of the simple boilerplate and CRUD work that used to be junior-dev bread and butter.
What hasn’t changed:
outcomes were never evenly distributed even back in the “good years.” The people who landed jobs fast were usually the ones treating the bootcamp as the floor, not the finish line, shipping extra projects, networking on top of applying, learning the parts of the stack the curriculum skipped. That gap between “finished the bootcamp” and “did the work after the bootcamp” mattered in 2021 and it still matters now, it’s just less forgiving of weak effort than it used to be.
So the real question probably isn’t “is bootcamp dead,” it’s whether the people calling it dead did the extra work or just expected the certificate to carry them.
If you went through one. what actually happened? Did the extra effort move the needle for you, or did it not matter either way?
I'm torn between committing the next four years of my life to a traditional Computer Science degree or just investing a few thousand dollars into an intensive tech bootcamp to get into the industry faster. I want to get a honest reality check from people who actually hold a CS degree to see if the formal route is still holding its weight in the current market. With the entry-level hiring landscape being as hyper-competitive as it is right now, and AI tools drastically changing how daily engineering workflows look, I am genuinely terrified of spending massive amounts of time and tuition money on a university track if companies are going to prioritize raw, practical project portfolios anyway. Would I be smarter saving the cash and sprinting through an immersive bootcamp instead
The hiring freezes, layoffs, and shrinking opportunities in tech aren't slowing down. If anything, things could get messier before they get better, and job seekers are starting to feel it. Companies that were aggressively hiring just a couple of years ago are now cutting headcount, tightening budgets, and leaning harder on automation to fill the gaps. Entry-level roles are nearly extinct, mid-level positions are flooded with applicants, and even experienced engineers are spending months in the job hunt with little to show for it. The optimism that defined the industry not too long ago feels like a distant memory, and for a lot of people in tech, the uncertainty isn't just uncomfortable, it's genuinely scary.
I'm on the absolute verge of pulling the trigger on a full-time software engineering bootcamp that costs roughly $10,000, but I am terrified of burning through my life savings for a piece of paper that the current job market might just instantly ignore. My main purpose for writing this is to get a brutal reality check from people actually working or hiring in tech right now, because the marketing pages still promise amazing placement rates, but the actual sentiment online makes it look like the entry-level market is completely underwater. With AI tools like Cursor and Copilot generating basic syntax and boilerplate code in seconds, I'm trying to figure out if spending thousands of dollars to learn traditional web dev frameworks is an investment that still yields a real return, or if I'm just paying an astronomical fee for an overhyped accountability group. Am I significantly better off saving my cash and fighting through the self-taught route or should I go through with this?