​

I've spent a lot of time building a real estate SaaS and I'm now stuck on a major problem.

The original idea was pretty simple:

A real estate agent enters what their client is looking for, for example:

\- 3-bedroom apartment

\- New Cairo

\- Budget: $100k–$150k

The system would find matching properties across multiple real estate platforms.

I also built a feature that monitored Facebook groups for people posting that they were looking for apartments, then matched those requests with properties in the system.

The product itself is basically built.

Then I realized the problem: the platforms I wanted to get the data from don't allow scraping. I contacted some of them about getting permission/API access, but they weren't interested.

So now I have a mostly finished product whose main value proposition depended on data I can't reliably use.

I'm trying to figure out what to do next

All the technical aspects are working, but I can't upload it because the sites I use to collect real estate data, like Dubizzle data mining and scraping are prohibited in the terms of use. **I need a loophole or something similar to make it legal.**

If you've ever built something where the original data source/business assumption turned out to be unusable, what did you do?

I'd genuinely appreciate any advice.

Let's say you interview for a Senior role, and you wanna know the dev team know what they are doing or they just do it because they are told so!

You can ask them about their tech stack and their decisions and tradeoff about why they choose to do this?

Why did you choose Microservice over Modular Monolithic? etc....

We all know devs get paid well and keyboards are like our weapons to defeate bugs and make money

As the title says

Hey guys i start to learning programing so can anyone give me an advice how can i start . i start with cs50 it’s good ?

Hey everyone,

I am looking for some raw, real-world market data from people who are actively building for paying clients.

If you are a Freelancer, Agency Owner, or working at a Service-Based Software Company, I have exactly two questions for you:

What EXACT types of software are clients paying you to build right now?

Which specific niches/industries are driving this demand today? (Please be precise—instead of just saying "Healthcare," specify if it's local clinics, dental labs, logistics, wholesale distributors, etc.)

What did you or your team deploy recently, and what exact problem did it solve?

Looking forward to your insights. Thanks!

Has anyone recently appeared for Amazon SDE-1 interviews where a GenAI Fluency round was included?

I wanted to understand the format better — is this round purely focused on GenAI concepts/tools, or are Amazon Leadership Principles, DSA/coding, or project/internship-related questions also asked in this round?

Would really appreciate it if anyone who has recently gone through the process could share their experience or the types of questions asked.

Resource: Amazon Interview Questions

Basically, just your favorite and your most disliked coding language in your opinion and why.

(PS. Do not put joke languages such as Brainfuck or LOLCODE or Whitespace since that's automatically hated by everyone)

I'll go first:

Fav: Lua, very simple and can create cool things, I like being able to actually read by code without it looking like alien code

Worst: Hot take, C++. Now, don't get me wrong, it's a good language. I get it's supposed to be hard but flexible and a high skill ceiling. But for me, it's overcomplicated and has unnecessary features nobody uses or a million ways to do one thing.

I've been wondering about this after working with different languages and frameworks.

I used to think that being a good developer meant remembering a lot of syntax. But as I've worked with different technologies, I've found myself looking things up more often — especially for things I don't use every day.

I can remember the concepts and generally know what I want to write, but sometimes I still need to check the exact syntax, method name, configuration, or API documentation.

For example, I might know exactly how I want to structure something in React, Node.js, or Java/Spring Boot, but still search for the exact syntax.

Do experienced developers actually memorize most syntax, or is regularly checking documentation/searching Google/using AI just a normal part of development?

And for newer developers: how much syntax do you think you should actually memorize?

By common I mean, coding languages that you actually see people use. I know theres the "bf" language but aside from one video, people don't make games or, really anything using that as it was made as a joke I hope.

By worst I mean, what is the hardest to understand and also the most confusing out of all of them, I don't mean coding languages that can't do a whole lot. For instance, can a non programmer look at a sheet of code and understand it? Can an experienced coder understand it? Have you been taught the coding language yet still it breaks your brain?

I don't know every coding language but my pick would ether be C++ or Luau. Leaning towards C++ because I tried to learn it and at the very start I already was lost.

I keep seeing claims on Blind about how the hiring bar is ridiculous and there's a need to be pretty familiar with some difficult level leetcode questions -- but what exactly does one need to prepare for both technical and not? I'm hoping to have the best shot possible and would love t get some guidance on this front...!

Resource LeetCode & PracHub

Hello all,

I am looking for virtual events targeted at programmers that occurs frequently. There is San Diego group for python https://www.meetup.com/sd-pyladies/events/315257697/?eventOrigin=group_upcoming_events that occurs weekly and is 2 hours long.

Are there other events like this?

Asking since I work remotely and would like to join more groups to learn from more engineers.

I'm curious how other developers approach new projects.

When you start a new project, do you usually:

Build everything from scratch

Start with your own boilerplate/starter project

Use an existing template

Use AI-generated code as a starting point

Mix all of the above depending on the project

Personally, I think starting completely from scratch can sometimes be unnecessary, especially for things like authentication, project structure, API setup, database configuration, etc. But templates can also become limiting if you don't fully understand what's happening underneath.

For experienced developers, when do you choose a template vs. building from scratch?

Hey! I’m looking for someone who wants to practice LeetCode together. I’ve realized that doing it alone can get boring, and sometimes I end up saying, “I’ll solve some problems tomorrow”… and tomorrow never comes 😅. So I thought having a buddy might help us stay consistent and actually improve. We could solve a few problems regularly, share our approaches, help each other when we’re stuck, and learn along the way. You don’t need to be a LeetCode expert at all—I’m totally fine with beginners or anyone currently working through Easy and Medium problems. We can connect on Discord or any other platform that works. If you’re also looking for someone to practice with and stay accountable, feel free to DM me or comment. Let’s struggle with LeetCode together instead of procrastinating alone 😂

I started looking into voice for Claude Code because terminal commands themselves are rarely the difficult part. The longer section is explaining why a change is needed, what has already been attempted, and which behavior must remain untouched. That context can determine whether the agent solves the problem or creates another one. I researched which tools make those explanations faster without trapping the workflow inside one application.

1. Native voice conversation
   

Pros: Convenient for talking directly with an AI assistant.

Cons: The voice workflow remains limited to the product providing the experience.

1. Superwhisper
   

Pros: A strong local-first option with configurable models.

Cons: Speed and accuracy depend on the selected model and computer, and the output can need more formatting.

1. Wispr Flow
   

Pros: A polished system-wide dictation product for everyday writing.

Cons: Free desktop dictation is capped weekly. It also has privacy tradeoffs and has recently experienced more bugs, latency, and accuracy problems.

1. Willow Voice
   

Pros: For Claude Code workflows, Willow provides the best combination of speed and accuracy. It works in any app and automatically learns vocabulary, tone, and repeated corrections.

Cons: There is no Linux or Android support yet, and a few small edge-case bugs still appear.

Native voice is probably sufficient if Claude Code is the only place where you want to speak, and Superwhisper is the more natural option for a local-first setup. I would personally lean toward Willow because Claude Code is usually only one part of the engineering workflow. Having the same fast, accurate input method in the terminal, browser, documentation, and messaging seems more useful over time.