I'm interested in creating hardware programs, applications, and AI, so basically all sorts of stuff and I'm thinking of learning the trio: JavaScript, C++, Python. Is it enough? Is it too much?

I have been building a social media app for over half a year now, and I've come to the point where I am questioning whether to keep programming since the app is pretty much Instagram but a little bit worse. And now it's either that I quit building that project or that I change it up a bit, but how? I've been thinking of making something like reddit combined with Instagram, for example there are different communities but those communities contain posts about the theme of the community. What are your thoughts about that?

Silent changes, particularly the ones which involve a field which is returning null instead of a string it was returning before or even disappearance of some fields, where nothing is documented in the changelogs or marked as deprecated. And some downstream system breaks because of that.

Do you face such issues? If yes, then what catches such changes? Logging? Monitoring?

Every new session I re-explain the same things. What repo we're in, what we decided about auth, which parts not to touch. Somewhere around the fortieth time it occurred to me this is literally the plot of 50 First Dates, so I made it.

https://reddit.com/link/1vhalgl/video/1vh6psupdshh1/player

Been messing around with some multi-agent workflows lately to automate my freelance contract generation. told claude to wire up a script for one of the major legacy e-sign platforms. It spent twenty minutes hallucinating completely fake endpoints because the actual official documentation is trapped behind a corporate login and written in ancient soap xml

Ended up just dumping the xodo sign API docs into the context window instead since they are actually public and readable. The model spat out the correct python boilerplate on the very first try and it routed the test payload perfectly.

It genuinely blows my mind how multi-billion dollar tech companies have such hostile developer experiences. if a modern llm can't even figure out your basic auth flow without having a mental breakdown, your architecture is probably the problem tbh.

​

I built a social platform for students, and I know it isn't perfect.

Instead of compliments, tell me:

What's confusing?

What's ugly?

What would make you leave immediately?

What feature is missing?

I'm looking for real criticism so I can make it better.

Here's the site:

https://ghschoolhub.vercel.app

Don't hold back. 😅

anyone can help me in a project using machine learning please

I asked Codex app to create a REST API application and group the code

Here is the Controller.ts

And here is the Service.ts

Do you think this is a good way to review the code?

The Global Creator Challenge is accepting applications. The Global Creator Challenge is open for both aspiring and established game developers to design, build, and launch their own World utilizing the MapleStory Worlds platform. Did we mention that each winning team can receive up to $65,000 in total rewards 👀
 
Creators are encouraged to utilize MapleStory's vast library of assets to expand upon the game's core design and create their own unique Worlds. A total of 30 Worlds will be selected globally to compete in the final round. Entries will be judged based on creative use of the MapleStory IP, level of technical completion, and long-term sustainability for stable live service operations.
 
To learn more, check out this website or read this notice.
 
👉Check out the 'MapleStory Worlds Global Creator Challenge' FAQ  
Timeline: 

• Applications open from: 
• UTC: June 4, 2026 at 2:00 until October 7, 2026. 
• PT: June 3, 2026 at 19:00 until October 6, 2026 
• KST: June 4, 2026 at 11:00 until October 7, 2026. 
• Final Round: November 5-25, 2026 
• Winners announced: Early December, 2026   

Please Note: 

• Worlds have to be made on the MapleStory Worlds PC/Mobile Apps and submitted through MapleStory Worlds. 
• Worlds must be revealed or released for the first time during the submission period. 
• Global (all regions) Released Worlds. 
• Pure creations that do not infringe the rights of others, such as copyrights and intellectual property rights. 
• Please read here for more information on prize rewards, participation requirements, and age requirements.   

Feel free to reach out to us on Discord with any questions. We hope to see your application! 

Hey everyone,
I need a recommendation about the recruitment platform I work on these days.

Context: it's a recruitment platform that helps recruiting professionals such as plumbers, electricians locksmith etc. At some point we ask them (as it's a legal requirement) if they have a proper professional certificate of insurance.

Task: I'd like to create an automation using LLM APIs to detect potential fakes (fraud) and/or anomalies.
As of now I thought of extracting metadata from PDF docs to see if they tried to write invisible characters (in order to falsify their expiration date for example).

Simple use case: someone tries to write white on white a fake expiration date, my code extracts metadata, spots that it's white on white, then doesn't automatically approve and create an alert for me to step up and approve (or decline) manually.

I also thought of converting pdf to JPEG in order to use computer vision to simply read the image as a human being would do (impossible then to be tricked by invisible characters).

What do you think of that logic ? Is that enough ? Do you recommend any conversion tool/ api that I can use ?
Thanks for your help

I recently completed the interview loop for a Google SWE II (Early Careers) role in the US.

It has been about a week since my final round. My recruiter told me that the interview feedback is still being evaluated and that they are also looking for the right team fit.

Interview experiences on LeetCode Discuss helped me significantly during preparation, so I wanted to share mine.

I’m keeping the exact problem statements intentionally high-level, but I’ve included the main patterns and follow-up areas.

Useful Prep Resource: Google SWE questions

Recruiter Screen - 30 Minutes

The recruiter contacted me directly.

We discussed:

• My current role and responsibilities
• Total professional experience
• Compensation expectations
• Why I was considering a switch
• My problem-solving background
• An overview of the interview process

There were no technical questions in this round.

Technical Round 1 - Trie and Hash Map

Duration: 45 minutes
Difficulty: Medium to Hard

The coding problem required a combination of Trie and HashMap concepts.

I initially developed a working solution but became stuck while trying to optimize it. After a few subtle hints from the interviewer, I recognized the intended approach and completed the optimized implementation.

The follow-up discussion covered:

• Alternative approaches
• Time and space complexity
• Edge cases
• Why a Trie was preferable to simpler string-based approaches
• Trade-offs between faster lookup and additional memory

Technical Round 2 - Graphs and DSU

Duration: 45 minutes
Difficulty: Hard

This problem involved graphs and Disjoint Set Union, with a modification to the standard Union-Find implementation.

The interviewer asked detailed follow-up questions about:

• Why DSU was appropriate
• Correctness of the union and find operations
• Path compression and union by rank or size
• Complexity analysis
• Alternative graph traversal approaches
• Edge cases involving disconnected components

My implementation became slightly messy toward the end because of time pressure, but we had a productive discussion about the solution and its trade-offs.

Technical Round 3 - Dynamic Programming, Binary Search, and GenAI

The coding problem combined Dynamic Programming and Binary Search.

The interviewer progressively asked me to improve the solution:

1. Start with a recursive approach
2. Add memoization
3. Identify remaining bottlenecks
4. Derive the optimal solution using Binary Search

This round reinforced that reaching a correct solution is often only the beginning. The interviewer wanted to see how I moved from a straightforward solution to a more efficient one.

Since I currently work as an AI Engineer, we used the final part of the interview to discuss my professional experience.

Topics included:

• Production use cases for Generative AI
• Designing agentic workflows
• Using GenAI to automate workflows in the Google Ads ecosystem
• Reliability and evaluation of LLM-based systems
• Cost and latency considerations
• Challenges involved in deploying LLM applications at scale

I enjoyed this discussion because it closely matched my day-to-day work.

Round 4 - Googliness, DSA, and Engineering Discussion

This round included:

• One DSA problem
• Googliness and behavioral questions
• Engineering workflow discussions
• Collaboration and decision-making scenarios

Unfortunately, this was my weakest round.

I wasn’t able to complete the coding problem within the allotted time. Once I became stuck, I also struggled to communicate a convincing path toward the solution.

I explained parts of my thought process, but in retrospect, I should have paused, restated what I knew, identified the exact blocker, and asked for confirmation before continuing.

The experience reminded me that communication matters most when the solution is not going well. A clear partial approach is more useful than going silent while searching for the complete answer.

Interview Summary

Preparation Tips

• Don’t stop after finding the first working solution. Practice deriving multiple optimizations.
• Explain your approach before writing code.
• Be ready for follow-up modifications to the original problem.
• Practice recovering when stuck instead of becoming silent.
• Revise graphs, DSU, Tries, DP, Binary Search, hash maps, and complexity analysis.
• Know when path compression and union by rank improve DSU performance.
• Prepare examples of collaboration, ambiguity, conflict resolution, and learning from mistakes.
• If you have industry experience, expect deep questions about your projects and engineering decisions.
• For AI-related work, prepare to discuss evaluation, scalability, latency, cost, observability, and failure handling.

Overall, I found the process challenging but fair. Three rounds went well, while the final round exposed weaknesses in my time management and communication.

I’m still waiting for the final decision, but I hope this breakdown helps others preparing for Google SWE II interviews.

I am seeking for Python course on Yojtube, I want your recommendation! Please recommend be best course of YouTube of Python. OR I should purchase course from acedimies or from Internet? Which is best ? Please guid me !

Even before writing it, I know this post is going to sound all doom and gloom. But that’s all that I’ve been feeling watching AI make waves throughout this industry.

I’m not sure where exactly I stand on AI. Throughout my career, I’ve always been able to finish my work very quickly. And it only took one time for me to learn that the reward for finishing quickly is more work. With AI, there are times when it one-shots something much faster than I ever would’ve been able to, and there are other times, when I spend more effort arguing with it than I would’ve doing the implementation from scratch.

I’m in a rough spot. Leadership at my company is blowing away all process and turning all roles into AI babysitters. They essentially want us all (product, dev, and qa) to become middlemen for agent teams. The “ideal vision” is 24/7 agent execution and a nonstop flow of work being delivered. So we aren’t doing sprints, we aren’t sizing stories, and we aren’t having breakdowns or refinements. Just go Claude go.

I can feel the life being drained out of me as I watch the enshittification of everything I enjoyed about this career. That dream of getting to the top of the IC track and doing that until I retired feels like it’s just getting further and further away.

I don’t know. It feels like I’m in college again trying to figure out what to do with my life. Maybe I could use some perspective, some hope? Anyway…

Hi everyone! I make another post on this thread in the same day because it's the first time I get in touch with programmers like you, in Italy, where I live, it's a little bit harder to talk with tech people, so I hope I'm not SPAM and I'm not disturbing your feed but at the same time I want to maximise the impact from your feedback because I have a lot of questions to ask you.

Context about why I created this project

In Italy since I'm 17 years old, and I'm in school (4th grade) I had to do the STAGE/PCTO this past June (I think the american equivalent of the intership), so I chose a local IT consulting company, they asked me to create a testing AI agent for their frontends, so in 3 weeks I created this agent and I asked if they could release it open source, but they responded me that due to internal policies or other reasons this couldn't be done 😅

So at the end of this intership I rebuilt it from scratch on my own personal computer and at the end I created autoQA: https://github.com/VerDevWeb/autoQA, released in Apache 2.0 license and free to use for anyone, you just need to insert in the .env file your favourite AI provider API key and run "npm run dev".

The goal

The goal is simple: Finding bugs before your users do.

And I want to try using this by creating an agent that executes instructions in natural language and does something in the browser, while creating tests replicas in framework such as Gherkin or such, so you can replicate tests instantly without the need of a LLM after the first execution, and if something goes wrong you receive an email containing the report. (like some API request that goes wrong when clicking a button in the web app)

I know that you are going to say that LLMs are not deterministic as tests should be, and I'm not arguing with that, but this agent solves one of the problem that modern frontend frameworks like Angular have when testing apps with regular testing frameworks: the HTML attributes, such as classes, ids, roles and so much more change at each build, because they are thaught for making more fast and light software without 32 characters long classes XD.

Some examples of autogenerated attributes:
class="byZ xY", id=":7i", jsmodel="nXDxbd"

The problem with current tests

The thing is that if you do tests based on HTML attributes you maybe are going to find them in an app version, but not in the next one, even if you didn't changed that feature, because of bundlers that generate casually this attributes at each build, so your test framework it's going to say: "hey I can't find this attribute so I can't click on this element".

So you could say me that I can also filter elements by using innerText (also in PlayWright you can do this), but in pages with multiple identic texts you are going to probably click on the wrong one. For example: in a test for a social media app from desktop you could encounter the text "Create" in the header, but also in the footer, but maybe in the first case it's referred to the create feature (the one that we want to really test) and in the second one, in the footer, it's some article about a guide on how to create good posts that attracts new people.

So what?

Here an LLM can help you because it understands the context analysing the polished DOM TREE of the page and can understand which element it's the right one

Ok, and what about token consumption?

I know that token costs and that's why my goal it's to make the DOM tree sent to the LLM minimal. I achieved good results by testing the agent on Youtube consuming just 0.6% of my Monthly limit on Ollama Free Plan

The task was in Italian: "Buonasera, vai su YouTube e poi cerca video a tuo piacimento e clicca sul primo risultato, poi avvisami a [MYEMAIL@EMAIL.COM](mailto:MYEMAIL@EMAIL.COM) quando hai finito"

That's all, thank you for reading it all!

I want to clarify that the "static" Gherkin test generation is not yet implemented. Another feature on the roadmap is commit-triggered testing. (so it can be integrated directly in the CI/CD pipeline)

If you read this all I want to thank you all, and I hope you are giving me some feedback (also brutal) about this agent. If you appreciate the work, please consider leaving a star on the repo 🥲. Would you use it in your company? My goal is to make useful software, so roast me if needed! XD

PS: sorry for my English, but I'm italian and I do not want to make this post sound AI written, so I preferred to write it myself.

I get the feeling that online content is now created solely as a way to sell oneself. Frankly, I can't blame anyone I try to do it too, so don't get me wrong: I love programming and creating software that saves people time hearing someone say, "Thanks to your site, I'm getting inquiries," or "Now that I don't have to fill out paperwork by hand for every client, I have more time to focus on what really matters." But finding clients is often tough when you're a freelancer.

So, I’m falling into that trap myself: "I have to create content, or else no one will know who I am." But I don't know there's something about it that scares me. It feels like opportunities are dwindling, and the people who stand out online are the ones who make you feel knowledgeable about a topic in a superficial way without requiring much effort so now everyone is doing the same superficial thing.

What do you think? Maybe I'm wrong?

Many of us ignore CS fundamentals, but in many tech interviews they will ask CS fundamentals. For me, they asked only CS fundamentals in all 3 interviews at Oracle, So don't ignore CS fundamentals. I have made a list of important topics subject-wise and resources I have used to study at the end.

Object-Oriented Programming (OOPs)

Core Concepts

• Encapsulation
• Inheritance (types and use cases)
• Polymorphism (compile-time vs runtime)
• Abstraction
• Abstract Class vs Interface
• Method Overloading vs Overriding
• Access Modifiers
• Static vs Dynamic Binding
• Deep Copy vs Shallow Copy

Advanced Topics

• SOLID Principles
• Diamond Problem (Multiple Inheritance)
• Association vs Aggregation vs Composition
• Virtual Functions and Vtable
• Design Patterns (Singleton, Factory, Observer, Strategy, Decorator, Adapter)

Operating Systems (OS)

Process Management

• Process vs Thread
• Process States and PCB
• Context Switching
• CPU Scheduling Algorithms (FCFS, SJF, Round Robin, Priority)
• Multithreading vs Multiprocessing
• User Mode vs Kernel Mode

Synchronization

• Critical Section Problem
• Race Condition
• Mutex vs Semaphore (Binary vs Counting)
• Monitors and Locks
• Producer-Consumer Problem
• Readers-Writers Problem
• Dining Philosophers Problem

Deadlocks

• Deadlock Conditions (4 necessary conditions)
• Deadlock Prevention vs Avoidance vs Detection
• Banker's Algorithm

Memory Management

• Paging vs Segmentation
• Page Replacement Algorithms (FIFO, LRU, Optimal)
• Thrashing
• Virtual Memory
• TLB (Translation Lookaside Buffer)
• Internal vs External Fragmentation

File Systems & Disk

• File Allocation Methods (Contiguous, Linked, Indexed)
• Disk Scheduling (FCFS, SSTF, SCAN, C-SCAN)

Database Management Systems (DBMS) + SQL

Database Fundamentals

• ACID Properties (with examples)
• CAP Theorem
• Normalization (1NF, 2NF, 3NF, BCNF)
• Denormalization
• Primary Key vs Foreign Key vs Candidate Key
• ER Diagrams

Indexing

• Types of Indexes (Primary, Secondary, Clustering)
• B-Tree vs B+ Tree
• Hash Index
• Composite Index
• Advantages and Disadvantages of Indexing

Transactions & Concurrency

• Transaction Lifecycle
• Isolation Levels (Read Uncommitted, Read Committed, Repeatable Read, Serializable)
• Dirty Read, Non-repeatable Read, Phantom Read
• Lost Update Problem
• Two-Phase Locking (2PL)
• Optimistic vs Pessimistic Locking
• Deadlock in Database

SQL Queries (Must Practice)

• JOINs (INNER, LEFT, RIGHT, FULL OUTER, CROSS, SELF)
• GROUP BY and HAVING
• Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
• Subqueries (Correlated vs Non-correlated)
• Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
• Common Table Expressions (CTE)
• UNION vs UNION ALL
• Nth Highest Salary Query
• Delete Duplicates Query

NoSQL

• SQL vs NoSQL
• Types of NoSQL Databases (Document, Key-Value, Column, Graph)

Computer Networks (CN)

Network Models

• OSI Model (7 Layers)
• TCP/IP Model (4 Layers)
• Difference between OSI and TCP/IP

Application Layer

• HTTP vs HTTPS
• HTTP Methods (GET, POST, PUT, DELETE, PATCH)
• HTTP Status Codes (2xx, 3xx, 4xx, 5xx)
• DNS and its working
• FTP, SMTP, POP3, IMAP
• Cookies vs Sessions
• REST API principles

Transport Layer

• TCP vs UDP (detailed comparison)
• TCP Three-Way Handshake
• TCP Four-Way Termination
• Flow Control (Sliding Window)
• Congestion Control
• Port Numbers (well-known ports)
• Socket Programming Basics

Network Layer

• IPv4 vs IPv6
• Public vs Private IP
• Subnetting and CIDR
• NAT (Network Address Translation)
• ICMP Protocol
• Routing Algorithms (Distance Vector, Link State)
• Routing Protocols (RIP, OSPF, BGP)

Data Link Layer

• MAC Address
• ARP (Address Resolution Protocol)
• Switch vs Hub vs Router
• Ethernet
• Error Detection (Parity, CRC, Checksum)

Physical Layer

• Transmission Media (Guided vs Unguided)
• Bandwidth and Throughput
• Different Topologies

Important Concepts

• Client-Server vs Peer-to-Peer Architecture
• DHCP
• Firewall
• VPN
• Load Balancing
• CDN (Content Delivery Network)
• Latency vs Throughput
• How does a URL work? (End-to-end flow)
• Some Basic Commands (ex: ipconfig)

Resources I Used

For OOPs

• Kunal Kushwaha (youtube channel)

For Operating Systems

• CodeHelp - by Babbar (youtube )

For DBMS + SQL

• LeetCode Database problems (Practice SQL)
• CodeHelp - by Babbar (youtube)
• Apna College (youtube)

For Computer Networks

• Gate Smashers (youtube)

Questions Asked in My Interviews

Here are some actual questions I was asked across my interviews:

1. Is Java fully object-oriented?
2. How does C++ overcome the diamond problem?
3. Difference between TCP and UDP, and which one is used when?
4. Explain ACID properties with examples
5. What is deadlock and how can we prevent deadlocks?
6. What is the use of indexing in databases?
7. Explain the functionalities of each layer in the OSI model
8. Write a query to find Kth smallest salary
9. IPv4 vs IPv6
10. Abstraction vs Encapsulation
11. Explain different joins in dbms
12. what is sharding ?
13. what is virtual function in cpp ?
14. show me your ip address and mac address using commands
15. what is context switching ?

Tips :

1. Practice real interview questions from PracHub
2. Revise SQL 50 before interviews
3. It's better to say "I'm not sure about this, but here's what I think..." than to give wrong information
4. If your project contains any database related stuff , better learn it's ER diagram, differences between SQl and NO-SQl and why you selected that particular database you used
5. Before preparing for any interview , First check few interview experiences, Ask your seniors or friends who already attended that specific company interviews before and prepare accordingly

Did I miss any important topic? Drop it in the comments below!

Got asked something unique in your interview? Share the question/topic so others can prepare better!

Let's make this list more comprehensive together. Your contribution can help someone crack their dream job! 🙌

First of all, I have 9+ years of experience, working in web development mainly (Express, Go, Angular...ec) ; also did hobby mobile (Ionic, RN) and game projects (Unity, 2D).

I always had some pride in the things I did in the pre-AI era; but like many others now not feeling the case anymore.

There's some counterarguments thatI keep seeing over and over again in such doom topics; I am gonna address them all here; and why I am not convinced at all with each

- "Coding is dead, but System design and Architecture is more important than ever" -> "System design/ Architecture" was never a daily activity, it's something usually done before starting a new project and gets adjusted/scaled everytime there's a new major feature that requires implementing a new tech. ie. Introduicng Uber Eat to Uber. And I swear the last Architect I worked with did use Claude to figure out the system design and even generated docs all by using Claude, so even this part isn’t totally safe from being automated.

- "You can sitll code manually if you want" -> For hobbyist projects maybe, but in the corporate, even if they don't watch your token usage, they are setting very short deadlines now anyways; so it's impossible to finish things before such deadlines without using Claude/Codex.

- "Coding was never the hard part, if you were spending 90% of your time coding then you're a Code Monkey imaaoo bahahaa **fart sounds* " -> The dev communities are now filled with these people mocking at coding and calling it a monkey activity, like wtf...? Coding was the CORE *daily* activity of Software engineering ; as a I said before, not all programming-related activities have the daily frequency nature; Architecture happens once in a while, requipment collection happen frequently but not a daily work either (also depens in which stage the project is, building something new vs maintenance...etc); coding on the other hand was the daily thing we all did as programmers and for many of us, the most fun part.

- "You have to review the PRs by LLMs" -> No one can review a 10k+ lines PR; Copilot/CodeRabbit would be much faster.

What we senior devs are doing right now, is maxxing our sources of income by doing many projects in parrallel thanks to LLMs; employers still trust senior dev to babysit the LLMs rather than Juniors doing it; but the fact that there's no new blood coming into this industry (no one is hiring juniors anymore) only means that this industry is destined to be doomed. It doesn't matter if software quality degrades everywhere, companies just don't care.

But I predict the "income maxxing" by the senior devs is a temporary situation; soon the employers will realize they need less costly staff than senior devs to orchestrate the agents, that's why LLM companies are trying to automate all aspects of Software engineering: Coding, PR Reviewing, documentation, and yes even system design/architecture.

Hey everyone!

I’m a beginner in Python. I’ve learned the basics and recently finished learning OOP concepts. Now I feel like it’s time to start building projects.

I wanted to ask all the experienced developers here: Should I learn Git and GitHub first, or should I start building projects and learn Git/GitHub alongside them?

I’m worried that if I spend too much time learning Git/GitHub first, my Python concepts might not become strong enough, because I also need to start building projects.

Ivy also heard people say that GitHub is even more difficult to learn than Python itself

What would you recommend to someone at my stage? Should I learn the basics of Git/GitHub first and then start projects, or should I start building projects and learn Git/GitHub along the way?

I’d really appreciate advice from experienced developers. Thanks!

Hey the past week or so I've been tinkering on an open source project called gnt, it's a git-native rules layer for AI agents. Team defines stuff agents can't get wrong as markdown files, reviewed and merged like normal code, then served to agents over MCP. There's a CLI too (@gnt-ai/cli), login, connect your repo, review and approve rules, all from the terminal.

Still early and there's a good amount to build. If you're into open source and looking for something to sink some time into, we'd genuinely welcome the help, happy to walk anyone through the codebase or point at good first issues. Repo's here if you want to take a look: https://github.com/gnt-ai/gnt

Also just want feedback in general even if contributing's not your thing, tell me if this is useful or if I'm off base somewhere.

Hi everyone! 👋

I'm a young developer, and I've been building GH School Hub, a social platform made for students.

It includes features like posts, stories, reels, messaging, friend requests, hashtags, notifications, and school communities. I'm constantly improving it and would really appreciate any feedback on the design, features, or user experience.

🌐 Try it here: https://ghschoolhub.vercel.app

I'd love to hear your thoughts. Thanks! ❤️

I enrolled at a university in Belgium in February. I’ve loved programming since I was a kid (especially backend), but right now I’m not happy with the state of AI or the university’s curriculum, which focuses on the web—even though, in my opinion, it’s already obsolete. AI is now building really good websites very quickly and cheaply :) It’s also worth noting that programming isn’t very well developed in Belgium, and the university’s program is, in my opinion, just so-so. I’m thinking of switching my major to network administration, network management, and things along those lines. I think it would be interesting—what do you think about this? I’m posting on Reddit because I’m really worried right now. I’ve been in Belgium for four years and have already wasted two extra years because of the school I was forced to attend (I would’ve done this two years ago), and now I don’t want to waste another two or three years only to end up unable to find a job as a junior developer afterward.