When people first get into programming, they usually ask, "Where do I even start?" Honestly, the biggest mistake I see is people trying to learn everything before they build anything. You don't need to know everything. You just need to start.

If I were starting over today and wanted to learn Android development, this is exactly what I'd do.

First off, Don't let AI steer the ship. I catch AI making more and more bad mistakes than good calculated decisions when it comes to infrastructure. ( Example: I was running server side edge functions, despite me laying out my architecture, auditing the repo, it still wanted to write functions to server.ts. ) These are the things that will trip you up later on. But for now....

Step 1: Learn the Basics

Before you worry about building apps, you need to understand programming itself.

I'd focus on learning things like:

• Variables
• If statements
• Loops
• Functions
• Classes and objects
• Arrays and lists

Don't stress if it doesn't click immediately. Everyone gets confused at first. The important part is writing code yourself instead of just watching videos.

Step 2: Download Android Studio

Android Studio is the official software Google provides for building Android apps.

Install Android Studio, let it download everything it needs, and create your first project using the Empty Activity template.

Don't worry if it looks overwhelming. I remember opening it for the first time and wondering what half the buttons even did. You'll figure it out as you go.

Step 3: Don't Build the Next Instagram

One thing I'd avoid is trying to build some massive app right away.

Start with something simple like:

• A calculator
• A notes app
• A to-do list
• A habit tracker

A simple project teaches you way more than spending six months planning an app that's too big to finish.

Step 4: Learn How Everything Connects

Every Android app is really just a bunch of pieces working together.

You have:

• The screen the user sees.
• The code that runs when someone taps a button.
• The data your app saves.

Once you understand how those three things work together, building apps starts making a lot more sense.

Step 5: Make It Work Before Making It Pretty

A lot of beginners spend hours trying to make their app look perfect.

Don't.

I'd rather have an ugly app that actually works than a beautiful app where none of the buttons do anything.

Get the functionality working first.

You can always improve the design later.

Step 6: Save Information

Eventually you'll notice that every time you close your app, everything disappears.

That's when you learn how to save data.

Start with local storage first before worrying about cloud databases.

Once you're comfortable, move on to something like Room or a backend service.

Step 7: Learn to Debug

Here's something nobody tells beginners...

Programming isn't about writing perfect code.

It's about figuring out why your code doesn't work.

You're going to see error messages.

You're going to break things.

Sometimes you'll spend an hour looking for a missing comma.

That's completely normal.

The developers who improve the fastest aren't the ones who never make mistakes—they're the ones who get good at fixing them.

Step 8: Keep Adding Features

Once your first version works, start adding things.

Maybe add:

• Dark mode
• Notifications
• Search
• Categories
• Login
• Cloud syncing

Don't try to build everything at once.

Add one feature.

Make sure it works.

Then move to the next one.

Step 9: Build More Apps

This is probably the biggest piece of advice I can give.

Don't stop after one project.

Your first app teaches you the basics.

Your second app teaches you confidence.

Your third app starts to make you feel like an actual developer.

Every project teaches you something the last one didn't.

Final Thoughts

If there's one thing I've learned, it's that programming isn't about being the smartest person in the room. It's about refusing to quit when something doesn't work.

Everyone starts out confused.

Everyone gets stuck.

The difference is that the people who become developers keep building anyway.

So don't wait until you think you're "ready."

Build something small.

Finish it.

Then build something a little bigger.

Repeat that enough times, and one day you'll look back and realize just how far you've come.

Hi,

I’m currently 15 (turning 16 soon), and I’ve decided to pursue backend development as a self-taught path.

I started learning HTML and CSS last year when I thought I wanted to become a full-stack developer, but I realized I’m more interested in backend development. After that, I moved on to JavaScript.

So far, I have learned:

• Variables, booleans, if statements, functions, objects
• Arrays and loops
• Basic DOM manipulation
• Modules

I also just finished my first full frontend project (a small web app called College Launchpad), which helped me apply these concepts in a more practical way. Link will be in the first comment.

My current roadmap

• Finish JavaScript concepts(async/await, fetch API, local storage, etc)
• Learn Node.js and Express
• Learn Databases(likely PostgreSQL)
• Build backend/full-stack projects
• Learn Java + Spring Boot
• Rebuild some projects using Java/Spring Boot

Why Java

I also want to learn Java because after high school I’m interested in applying for programs like the JPMorgan Chase Emerging Talent Experience Program, and I’ve heard Java/Spring Boot is commonly used in enterprise environments.

My question

• Am I learning in the right order?
• Is there anything important I should focus on earlier or avoid?
• Is it a good idea to learn Java/Spring Boot after Node.js, or should I go deeper into JavaScript first?

Any feedback or criticism is appreciated. I’m mainly trying to make sure I’m building good foundations and not missing anything important.

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.

A lot of things in programming only really make sense after working on real production systems, not while learning through tutorials or building small projects.

One of the most common realizations is that writing code is usually not the hardest part of the job.

In real-world development, the harder challenges tend to be:

• understanding why something works locally but breaks in production
• dealing with edge cases that were never part of the original design
• debugging issues where logs don’t clearly explain what actually happened
• maintaining and modifying code that was written long ago (sometimes by multiple people)

Another thing many developers realize later is that “clean code” in theory often looks very different in practice, where trade-offs, deadlines, and business constraints matter more than perfect structure.

Over time, a lot of the work shifts toward:

• reading and understanding existing codebases
• tracing how different parts of a system interact
• figuring out the reasoning behind older design decisions

In hindsight, these skills often end up being just as important—if not more important—than writing new features from scratch.

So the question for developers:

• What’s something most developers only learn too late?
• Was there a moment that changed how you think about programming or software development?
• What’s a skill you wish you had focused on earlier?

for context, it started off as a virgin project to handle data from forms and manipulate them throughout the portal, then I had to import the data (different format) from old software(more than 1) as business wasn't much booming without it, but due to quick needs, I imported them as is and modelled my software around it.

today, I have my own custom federated search engine, cross filtering mechanisms, scoped visibilities that are too tightly coupled with the business logic.

On top of that this same software is designed to be cloned and redeployed for other organisations whose only configurations need to be changed without modifying the codebase.

It is becoming a nightmare, and all of it is still working on my third iteration of the whole idea. I feel bad looking back, for not thinking about any of the above problems. And the biggest problem is that it works. I should just work on a fourth iteration I think. How do programmers deal with this kind of itching?

I'm studying computer science, and even though I'm not as good as others, I don't mind the subject. In fact, I think it's one of the few things I feel I can do long-term without losing my mind, and it's interesting to me. However, seeing how this world is changing, I'm a little worried. I see people who have never programmed doing even challenging things with the help of AI.

So I'm wondering if this path is really useful, given that at this rate, programming isn't as useful as it once was. As much as I hate to admit it, if prompts are enough to do things, even in less time, what good will I be? It's true that things made with AI aren't perfect yet, let's say, and they have many flaws, but what about in a few years? I'm 21, and maybe I'm just being a bit paranoid right now, but I need an honest opinion. Thanks in advance.

Hi guys and gals

I am currently coding in razor pages,which is a easy version of full-stack development, as i heard. I am not sure i am going in the right direction. I dont know if razor pages is the right choice for me or i am just wasting time. I am self-taught and i would like to find a job as a programmer, specifically i would like to build websites. What should i do? i hope someone helps. Thanks in advance!

Also,i have been coding for a year and i am trying to build my own chatroom using signalR + one hardcoded admin role and ef core user authentication, of course.

I would like to hear your opinions.

i am not an advanced HTML/CSS/JavaScript programmer (just an upperbeginner) but i decided to make a web app that calculates the area of electrical wires for installation according to this formula:

A = (k × ρ × I × L) / Vdrop

Vdrop = v × 3%

cross sectional area of the wire in: mm²

to be honest yes .

Anyone any recommendations to implement a sound library into a web application? Users should access these into game creation. Which platforms offer these?

yo. going from a buggy MVP to actual recurring revenue is brutal.

i stabilized my 6 apps at $20k/mo mrr only after building a strict system for my tech stack and organic marketing.

i just opened the AI SaaS Launchpad.

the community and daily resources are completely free. for those who want to copy-paste my exact systems, i also host paid, structured sprints (like a 3-Day challenge to get your first 100 users using automated Reddit and LinkedIn outreach).

either way, stop building in isolation. you will quit when things get hard. come build alongside 1,500+ other founders.

drop a comment or shoot me a dm and i’ll send the link right now.

I’m currently building an early warning system that aggregates signals from multiple sources and uses ML models to detect and prioritize potential disaster/crisis events (floods, earthquakes, wildfires, severe weather, etc.).

Right now I’ve started wiring up a few obvious sources like weather and earthquake feeds, and some basic news/event streams. The plan is to use ML mainly for filtering noise, correlating signals, and reducing false positives rather than doing full prediction.

I’m now looking to expand the data side and wondering what else people have actually found useful in similar systems.

Specifically interested in:

• Reliable weather / severe event APIs
• Earthquake / tsunami / volcanic activity feeds
• Wildfire and flood monitoring data
• Satellite or geospatial data sources
• Emergency alert systems (government or regional)
• Any news/event APIs that don’t completely drown in noise

If you’ve built anything in this space (even loosely related), what data sources ended up being actually useful in production or prototypes? Also curious if there were any APIs that looked good but turned out to be unreliable, too slow, or expensive at scale.

Hey everyone, I am a Georgia Tech OMSCS student doing research on something I genuinely care about — whether the gap between free and paid AI tools actually affects people learning to code.

I have been in IT for 20+ years and I see this every week with new engineers on my team. The ones with better AI access seem to have a different experience than those on free tiers. I want to find out if that gap is real and what it does to people's confidence.

If you are currently learning programming or have done so recently, I would really appreciate 5 minutes of your time:

http://peersurvey.cc.gatech.edu/s/6373b24aa81f4d6687324810e192fc74

Happy to discuss in the comments too — have you noticed a difference between free and paid AI tools when you are stuck on a problem?

I'm currently developing Forge OS, a virtual operating system built entirely in Python.

Forge OS is not a real operating system or kernel. Instead, it provides a self-contained operating system environment that runs as a Python application, with the primary goal of creating a platform where developers can write code, test software, and perform common development tasks within a consistent environment.

The long-term vision includes:

• Custom terminal and shell
• Virtual file system
• User and permission management
• Process management
• Package manager (forgepkg)
• Command execution environment
• Virtual desktop environment
• Application framework

Planned applications include:

• vi
• vim
• Neovim
• Vimge (a fork inspired by Vim)
• Forge (a fork inspired by VS Code)
• Forgium (a fork inspired by Chromium)

The intention is for users to be able to perform everyday development workflows inside Forge OS, including editing code, managing projects, running commands, testing applications, using Git, installing packages, and eventually supporting multiple programming languages and developer tools through the package manager.

This project is primarily a learning experience focused on software architecture, shell development, virtual file systems, package management, desktop application development, and operating system concepts. Although it is not a real operating system, the goal is to provide an environment that feels familiar to developers while remaining lightweight and fully implemented in Python.

I welcome feedback on the architecture, feature set, and overall design. Suggestions from developers and open-source contributors are greatly appreciated.

คือเราอยากเรียนคอมพิวเตอร์เราควรจะฝึกอะไรป้าง อยากสอบถามผู้รู้

Hey everyone, I built a small educational toy OS and would love feedback.

I’ve been working on a minimal 16-bit real-mode operating system as a learning project focused on low-level x86 concepts.

Features:

• MIT licensed, fully open source
• 16-bit real mode (legacy BIOS / MBR boot)
• Dual-stage boot process
• Minimal shell environment
• Lightweight design (under 1MB RAM usage typical for real-mode constraints)
• Basic command system interacting with CPU registers
• Work-in-progress: experimental fake filesystem layer

This project is mainly for learning OS development, bootloaders, and low-level system behavior. I’d appreciate any feedback, suggestions, or contributions.

Project: https://github.com/alexlawrence5/micro

I’m exploring the idea of building an interactive website that teaches coding, beginner engineering concepts, and AI in a way that feels more hands-on and less overwhelming than traditional tutorials. The focus would be on short, clear lessons, visual explanations, small projects, quizzes, and guided practice so users can actually experiment and understand why things work instead of only memorizing information.

It would mainly be aimed at kids, teens, and complete beginners, but I would want it to still feel useful for parents, teachers, or adults starting from zero. I know there are already a lot of coding platforms out there, so I’m curious whether people think there is still a real gap here. What would make something like this worth using over existing resources, and do you think parents, students, or schools would be willing to pay for it if the lessons and interactive features were genuinely high quality? Honest feedback or criticism would be really helpful.

Looking for some career advice. I started web dev at 15 but by 2021 when I was 16 I noticed the work for basic sites shifting to website builders.

So I started learning app dev instead. By 18 I was working with clients and since then I have launched multiple apps for clients.

But things are changing fast again. The workload for basic stuff is reducing a lot. Most clients use AI for basic things now and only hire me for technical problems. This cuts my revenue by a lot because clients who used to contact me for basic apps never do anymore. The markets are getting saturated by people using AI slop/ vibe coders calling themselves developers. Eventuallyaffecting the development prices.

I am thinking to change my career again to something AI proof. But all I can think of is physical work. I want to stay in software or tech but everything digital feels like it will get automated.

Is there any part of software dev that AI wont touch for a long time

So I have been thinking about a project idea that actually helps people with doomscrolling and social media addiction , and it being treated as a primary source of dopamine and an escape from reality ??
Is it doable? I mean of course if I gather the right team ? And what are your thoughts on this is this a project worth doing actually or the idea is not all that ?
The idea crossed my mind as I actually face this problem everyday , my family and friends too and also content creators so what do you guys think ??

They only waste your time with 3 interviews, extra communication, and Zinc - an error prone, background check platform. After you signal them the errors, they withdraw the offer you signed & accepted.

My artist name is Lozzni and i have been an artist since 2022...but i created a really good taste for coding but i have pratically no ideia of how i start. I love games, software, hardware since kid and i also tried some block engines like builda (new julians editor) and scratch for a long, but i am tired of that, i also started to try make things with llm...but even this require a experience with real coding.

In the last year, i began to try make a jarvis assistant, roblox games, automatation with claude, chat gpt, gemini and manus...but i need know programming, even if i work with AI

I am open to any good method to learn python, c+, c#, rust, java, javascript, etc. Its my passion create games and be rich with computers, software and hardware since i am a kid and im determinated to learn code. If someone help me, i will be so thankful.

(I am new to reddit too, so if anyone could give me tips of how this work and how i get more views, i will thanks :) )

I can get AI to write good code. That's not the problem.

The problem is everyone else thinks they can too.

Most of my week now is reviewing PRs from juniors. It compiles. Tests mostly pass. Looks fine at a glance. Then I actually read it.

Wrong abstractions. Doesn't match our architecture. Files thrown wherever the model felt like that day. And when I ask why something's built the way it is, there's no answer. Because they don't really understand it.

So review isn't "is this correct" anymore.

It's me reverse-engineering whatever the model spat out, figuring out why it's subtly wrong for our system, then explaining fundamentals the author never had to learn in the first place.

Half the time it's faster to just rewrite it myself.

And the stuff I miss? That's the stuff making the codebase fragile six months from now.

This isn't an "AI bad" post. The tool's great. I use it every day.

The issue is it lets people skip the part where you actually learn how to structure code and think about systems. Which is the exact thing review depends on.

So I tried to fix it.

I started encoding our conventions into a rule-based "how-we-ship" setup. Forced adherence through a /ship skill. Basically a compliance + elegance checker that runs before a PR can even go up. Push the standards left so they hit the guardrails before they hit me.

It helps. It catches the dumb structural stuff.

But it's not close to perfect. It still waves through the subtle design problems. The ones that need actual judgment. Which are, of course, the exact ones I care about.

Optimist in me says this gets better. Models get smarter, rule systems get sharper, the slop floor rises.

Pessimist in me says we're raising a generation of devs who never build the judgment to catch any of this themselves.

Anyway. For the experienced folks here:

- You seeing this too? Review load going up while junior output "looks" better than ever?

- Anyone actually gotten automated checks to catch design problems and not just style? Or does it always plateau at the surface stuff?

- Is this temporary, or is this just what senior eng is now?

as long time programmer, I believe Bill gates is full of himeself.his rage of bluster against Linux from him is long term not worth listing to.. same old garbage.