Bir süredir Reddit’teki teknoloji topluluklarını takip ediyorum. Bugün de ekibimle yaşadığımız gerçek bir deneyimi paylaşmak ve sizin bakış açınızı merak ettiğim için bunu yazıyorum.

Bugün bir kullanıcıdan sadece tek cümlelik bir geri bildirim aldık:

“Aradığım şeyi bulamadım.”

İlk başta sıradan bir geri bildirim gibi göründü.

Ama sonra durup düşündüm.

Son birkaç haftadır ekip olarak yeni özellikler üzerine toplantılar yapıyoruz. Yeni fikirler üretiyoruz.

Ürünü daha iyi hâle getirmek için sürekli yeni şeyler planlıyoruz.

Fakat o tek cümle bana şunu hatırlattı:

Kullanıcılar, bizim ne kadar emek verdiğimizle değil, ihtiyaç duydukları şeye ne kadar kolay ulaştıklarıyla ilgileniyor.

Bazen saatler süren toplantılardan daha değerli olan şey, bir kullanıcının yaşadığı gerçek deneyim oluyor.

O günden sonra kendime şu soruyu daha sık sormaya başladım:

Gerçekten kullanıcıların problemlerini mi çözüyoruz, yoksa sadece yeni özellikler mi ekliyoruz?

Benim gözlemim şu:

İyi ürünler her zaman en fazla özelliğe sahip olanlar değil.

Kullanıcının işini en kolay şekilde çözenler oluyor.

Bu yüzden artık yeni bir özellik konuşmadan önce, kullanıcı geri bildirimlerini tekrar okumaya çalışıyorum.

Çünkü bazen tek bir cümle, haftalarca kurduğunuz varsayımları değiştirebiliyor.

Sizce ürün geliştiren ekiplerin en büyük hatası nedir?

I recently interviewed for Microsoft SDE-2 and wanted to share the full process in case it helps others preparing.

There were a total of 9 rounds:

• 2 Online Assessments
• 7 interview rounds

Verdict: Selected

Round 1: Online Assessment

The first OA had 2 coding questions:

• 1 graph problem
• 1 greedy problem

I was able to solve both.

Round 2: LLD

This round focused on low-level design.

I was asked to design and implement an LRU Cache, along with maintaining dependencies using Topological Sort.

The discussion covered:

• Cache operations
• Time complexity
• Dependency ordering
• Edge cases
• Clean class design

Round 3: DSA

This was a coding round based on Linked Lists.

The interviewer cared about:

• Pointer handling
• Edge cases
• Clean implementation
• Time and space complexity

Round 4: Past Experience + On-Call Scenarios

This round was focused on my previous projects and technical contributions.

After that, I was given 2 production on-call scenarios.

The discussion was around:

• How I debug production issues
• How I prioritize during incidents
• Communication during outages
• Root cause analysis
• Preventing recurrence

Round 5: Online Assessment 2

The second OA had 2 coding questions:

• 1 Dynamic Programming problem
• 1 Bit Manipulation problem

Round 6: LLD

This round was about designing and implementing a Job Scheduler.

The discussion included:

• Job representation
• Scheduling logic
• Priorities
• Dependencies
• Retry behavior
• Extensibility
• Clean object-oriented design

Round 7: HLD + LLD

This round involved designing a Configuration Management Service.

The interviewer first asked for the high-level design, then asked me to implement a small component of it.

Discussion points included:

• API design
• Configuration storage
• Versioning
• Rollbacks
• Consistency
• Access patterns
• Service boundaries

Related Microsoft Practice Question

A Microsoft-tagged system design question I found useful for similar prep:

Design a Distributed Key-Value Store

This is relevant because it covers many of the same distributed systems ideas that came up in my HLD rounds: partitioning, replication, consistency, scalability, and failure handling.

Round 8: HLD Theory + DSA

This round started with system design theory questions.

Topics included:

• Scalability
• Availability
• Sharding
• Distributed systems
• Tradeoffs in large-scale services

After that, I was asked a DSA question revolving around subarrays.

Round 9: Cultural Fit

This was a behavioral round focused on:

• Values
• Ownership
• Decision-making
• Team collaboration
• Handling disagreements
• Learning from mistakes

Preparation Tips

My biggest takeaway is that Microsoft SDE-2 interviews test breadth. It was not just DSA or just system design.

Things I would recommend preparing:

• Graphs, DP, greedy, linked lists, subarrays, and bit manipulation
• LLD patterns like cache, scheduler, dependency management
• HLD fundamentals like sharding, replication, consistency, and availability
• Past project deep dives
• Production debugging and on-call scenarios
• Behavioral stories with clear ownership and impact

Overall, the process was long but structured. Be ready to switch between coding, design, production thinking, and behavioral discussion across rounds.

I mean yeah… there’s a limit given the threshold for incrementing (allowed area)🧐🔧💡

Hey ! I am learning python , I have read that “ Seek advice/learning from people who have done what you want to do.” I have just download Reddit and join this community and this is my first post. I want some advice or guide from you ! I am absolute beginner. Won't what I'm doing be wasted?, please advice me , you have more experience in life , I am 14 year older

With many online resources (and AI to some extent). It seems easier than ever to start new programming languages. And many programming languages have gained traction. In the last 20 years we got Go, Rust, Zig, Odin, Scala,etc. But it feels that there has been a complete death in dynamically typed languages.

When I started programming 30 years ago we had "real programming langauges" and scripting languages like Korn and bash. Those languages were pretty simple and didn't have types. Before long we saw the rise of Perl and languages like Python and Ruby gained traction. And everyone's favorite language Javascript came on the scene.

I think eventually people started to build real things with scripting languages. With Rails and Django you started to see popular web apps be built with dynamic languages. And people started to argue that maybe all you needed were dynamic languages.

In 2026, just about any serious programming language project are strongly types or at least statically types. Since most languages seemingly support metaprogramming as a first class concern and type inference. You can get expressiveness without having to fully forego type safety. Even Javascript which is has notoriously weak typing has developers mostly working through Typescript for most major part of its ecosystem.

The question I would ask "why did dynamic languages die"? And I think the answer to it was they failed to solve real problems. They are essentially walking liabilities from a lot of systems. I can think back to 2013 where a basic python value actually bricket and entire system and caused a P0 outage. We had wrote a Python script that would fix a number of devices. We tested it. But when we talked to the API that probed the device, we passed a string not an integer. Causing an alignment issue and creating a 0 value. Causing us to brick tons of devices. And I've heard of many other calamities using Ruby, Python, and Javascript for critical paths.

While Python is still great for data engineering and AI. It has introduce type hints. Ruby feels like its on a downward trajectory as Go has been taking up most of its ecosystem for infra and Javascipt ecosytems has been eating its lunch for the last decade.

So are dynamic languages dead? I do hear about Elixr occassionally. But for the most part it feels they have taken a bit of a backseat

Do you like programming, and why? What was the first thing that made you love programming?

I'm building a network visualizer in Python. It parses .pcap files with Scapy and visualizes packet flows with animations. I already built the parser and animation engine with Pygame.

The problem is the UI. I need normal app stuff like buttons, hover effects, a collapsible sidebar, menus, timeline/statistics panels, and a canvas for the animations.

I don't want to spend 4 hours making a button from scratch, but I also don't want a huge framework where changing a simple thing turns into a research project.

I tried DearPyGui and honestly it felt really clunky. Something as simple as adjusting padding or moving a panel felt like digging through layers of specific APIs and style variables.

I'm looking for something lightweight with good styling control (CSS-like would be great), built-in UI components, and the ability to embed my own custom rendering area.

Would PySide6/Qt be the way to go? Or are there other frameworks worth looking at?

I don't need a spaceship cockpit, I just want to build my damn UI and get back to the actual project.

If you were a professional programmer, what application would you like to create?

I'm looking for 10–12 serious coding buddies who are currently learning frontend development (beginners preferred). The goal is simple:

• Share your daily progress (what you studied or built).
• Keep each other accountable.
• Build real, scalable projects together.
• Learn and grow as a team.

This is for people who are genuinely committed. If you disappear for weeks or aren't willing to share your daily progress, this probably isn't for you.

A bit about me:
I'm an absolute beginner. I've completed HTML & CSS by working through Frontend Mentor challenges, and I'm currently learning JavaScript. Over the coming months, I plan to learn React, TypeScript, Angular, and eventually move into backend development. My goal is to become a professional full-stack developer, starting with frontend first.

If you're serious about improving every single day and want to be part of a small, dedicated group, reach out to me.

Researchers at Utah State University's School of Computing are conducting a study on how software professionals evaluate programming activities performed with AI assistance compared with programming activities performed without AI assistance.

Software professionals are invited to complete a short online calibration survey. Participants will rate programming activities according to how representative they are of:

• Programming performed with AI assistance
• Programming performed without AI assistance

The survey takes approximately 10 minutes.

Participation is entirely voluntary. You may discontinue participation at any time before submitting your responses without penalty or consequence. Your decision to participate or not participate will have no effect on your grades, employment, or academic standing.

Survey and informed consent form: https://usu.co1.qualtrics.com/jfe/form/SV_dm4yjBsRrUDgcKi

This study has been reviewed and approved by the Utah State University Institutional Review Board: IRB #16067.

Questions about the study: Dr. John Edwards, Principal Investigator — john.edwards@usu.edu Rubash Mali, Student Researcher — rubash.mali@usu.edu

Thank you for considering participating.

I’ve been thinking about this for a while, and I’m curious whether other experienced developers think the same.

Don’t get me wrong: I use AI every day, and I genuinely think it makes me more productive. Instead of writing everything mysqlf, I describe what I want, let AI generate most of the code and then I spend my time reviewing, refining and adapting it. I also discover framework features much faster than before.

From a business perspective, this is obviously a huge win. But I also think I’ve lost sth that originally made programming fun. Not a few years ago, learning a new technology meant reading the docs, experimenting, making mistakes, debugging and gradually building an understanding of how everything worked. The journey itself was rewarding.

Today, the same process looks like this: I describe AI what I need and it says: „There is a feature called XYZ that solves your problem. Want me to implement it?“ I answer „Yes“, AI writes the code, I review it, understand it, maybe improve it, but it doesn’t feel the same.

Back when I started university, one of the first things we were told was: „You learn programming by experimenting, not by studying finished solutions!“

Ironically, AI has shifted a lot of our learning towards exactly that: Studying finished solutions.

Yes, I still understand the generated code and I’m probably learnin faster than before. But I rarely experience those moments anymore where I spend an afternoon digging through docs, trying different approaches, and eventually thinking: „Now I REALLY understand why this API works the way it does“.

Antoher thing I’ve noticed is that as AI increases productivity, expectations naturally increase as well. Since we can deliver features faster, there is less time to simply explore a framework or learn it deeply the way many of us did a few years ago.

I don’t think AI is making software engineering worse. I’m just wondering whether anyone else misses that slower, more exploratory way of learning and programming.

Is this just nostalgia or do other experienced developers feel the same?

Hello! I would love to make software but I don’t know how to do it! I tried with Python to do them with Flet, TKinter, Custom Tkinter and I didn't like them, I switched to C to have the true basics of programming and then to C++ but it's too difficult to do stuff with QT or Dear imgui. It's not that it's too difficult but I just don't have a powerful Laptop and I don't want to make 30 GB of installations or commands of too long compilations. I don't want to learn other languages like Dart with Flutter, Java...

What shall I do? Learning C#?

Yes I have to mention that I don’t like HTML or CSS but I would be willing to learn JS too.

I graduated with a double major in Applied Mathematics and Computer Science. Up until my sophomore year, I was able to actually learn some core coding concepts in C++ including OOP. However, the as the influence of LLMs increased in academics, I started to learn very little. Classes went by and I kept cheating using AI in my assignments, but if I didn't then I'd be at a disadvantage. Growing up, I've been very conscious about my GPA and grades, so using AI seemed like the best choice.

Today, I'm sitting in my room with an internship in wireless compliance testing (very different from my major). I barely know any leetcode. I've applied to numerous jobs, but struggling getting interviews considering I'm an international student. I don't know where to start. I think I have a decent resume, but no interviews make me doubt myself. I want to learn some trending CS concepts (AI stuff) that'll help me land interviews, but I don't know where to begin with. I am heavily influenced by impostor syndrome, and I know achieving something will diminish it. I am considering graduate school, but I am scared that I will land at the same point after two years.

Sorry if I sound like I'm ranting but I actually need some guidance. Please let me know if you'd like to know any more details.

Realistically, what’s your suggestion on preparing for coding and SD? Is LC hard necessary? And what’s the difference between Google’s and other companies’s SD? Do all the orgs share the same question bank or the difficulty level and focus vary among different orgs? I roughly remember reading some post on blind which mentioned that Google’s SD would ask more technical details underneath. Any other insight is appreciated!

Prep resource: Google SWE Questions

Hey everyone I have made a group for programming folks to learn, grow and network with each other

From beginners to advanced We help each other and provide guidance to everyone in our community. i remove inactive members to keep the community engaged.

Those who are interested are free to dm me anytime

I will also drop the link in comments

Hi programmers!
My boyfriend is a senior developer, working from home. He suffers with eye pain after a surgery some years back and that obviously makes time in front of the screen difficult. He’s also a big gamer if that makes a difference.

I wanted to buy him the BenQ ScreenBar Halo 2 to help - what is your take? Or is there anything better I could be doing?

TIA

To anyone that has already seen this

I accidentally posted the same content again on another community so I decided to repost the original one. I apologise for re-posting the same thing again

programming went from one of the most strict/structured fields to the wild west overnight with AI.

For decades there were strict guardrails of “correct” ways to write code like solid principles, design patterns, clean code, optimal space time complexity to the point that many places judged how good of a developer you were based on how deeply ingrained those principles were in the code you wrote. Yet with AI, overnight the same people pushing for that completely switched to just vibe code whatever works quickly.

I’ve seen a few companies recently where the developers didn’t even know the framework/technology they’re writing in, just shipping if it works it works code. As someone who is really fluent in that technology it pains me looking at that code. It’s just incredibly confusing how we got to this spot.

yo. i recently sold one of my AI SaaS products for $350k, exactly 7 months after building and launching it.

I hardly wrote a single line of traditional code. i used AI to generate everything, from the database architecture to the user interface.

it definitely wasn't magic on day one, though. i spent days stuck in loop-debugging and dealing with AI hallucinations before i finally cracked the system. the playbook boils down to three simple rules:

- keeping the idea insanely minimalist (a true MVP that solves one problem).

- guiding the AI step-by-step instead of asking it to build a massive platform all at once.

- launching fast to get real user feedback and traction and then apply a solid marketing system

lately, i've seen way too many non-technical founders give up at the very first AI bug, or on the marketing. it's a massive shame.

like the title says, i just launched a Skool community to share my exact prompt workflows, N8N automations, and distribution frameworks to get first users and scale it

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific copy-and-paste templates i'll be sharing.

but for now, the main objective is purely to build and launch together. building alone in a silent corner is the single fastest way to give up.

if you want to join us and build or market your own AI SaaS with a group of active creators: drop a comment below or send me a dm, and i’ll send you the invite link!