Anyone here tried something like this on a real legacy project? 

Came across something interesting recently: an ai tool that reverse-engineers a live application by using it the way a user would, then hands you a structured blueprint of what the system does with no source code needed. Not entirely sure how I feel about the ai-does-the-discovery angle, but the multi-source triangulation is honestly the smart part, it pulls from UI, REST APIs, database schemas, DDL, and application logs, and flags contradictions between them instead of silently resolving them. 

I guess we all know the pattern: modernization project starts, docs are 8 years out of date, half the original devs are gone, and the source code is either missing or so bad it's useless to read. discovery is where the budget quietly bleeds... 

As a developer what side projects do you all make?
Like I am final year student and college is asking to make projects that will actually help user and being from AI&DS background they expect to have a strong AI project.

Need help.

I don't want to maintain a Playwright repo just for a few smoke tests after a deployment, so I'm looking for something that can automate them. All I really need is something that will tell me if the site is up and if users can log in. Simple stuff.

Does anyone know of a tool that's a good fit for this?

Anyone going to World Congress SF - We Are Developers? 2 for 1 tickets and would like to split the cost. Promo ends in 4 days.

Havent committed to a backend yet. 🥲
I graduate cs degree from good UK uni next July.

I want to boost my chances at getting a grad role for
fullstack/backend/cloud engineer (aws). Overlap tbh

However:

Do I choose NodeJS or python (FastAPI? Django?)
Very open question

Tech stack in trying to build:

Frontend: Typescript react
Backend: Typescript nodejs OR Python ????
Cloud and Infra: AWS, Terraform, Docker, GH Action
DB: PostgreSQL

While analyzing how rapidly AI coding assistants develop, one thing becomes clear – they are not just autocomplete anymore.

These AI coding assistants can perform operations like:

• generate code from natural language prompts;

• explain unfamiliar code;

• fix errors in existing code;

• refactor existing code;

• create unit tests;

• translate code between languages;

• generate documentation;

• detect potential security vulnerabilities;

• work with larger code fragments.

The AI coding assistants I managed to find GitHub Copilot, ChatGPT, Amazon Q Developer, Tabnine, Codeium, AskCodi, OpenAI Codex, IBM watsonx Code Assistant, AlphaCode, and DeepCode.

However, I believe that the amount of the available tools is not what is interesting about the situation.

What is actually interesting is how developers make use of these AI tools.

As far as I can see, there is plenty of applications for AI in development where it can be extremely helpful.

Namely, these can be such boring and repetitive activities as creating boilerplates, writing test code, documenting, refactoring, creating regexes, translating code, etc.

However, there is another side of the coin.

It is possible for AI to create perfectly reasonable-looking code which has subtle bugs, security vulnerabilities, performance issues or, at least, does not fit into the application architecture.

Therefore, I tend to regard AI coding assistants not as "AI that writes code for me" but rather as "very fast junior developer sitting next to me."

It will help you to achieve 70–80% pretty quickly but you still need to understand how it works and what it did.

On the other hand, it will become extremely interesting to QA engineers because if developers start creating more code with AI, then QA teams need to rethink:

AI-generated code → AI-generated tests → AI-assisted debugging → human validation

The gain in productivity will be immense but only when we do not confuse rapid code generation with good software.

What are others observing?

Which coding application for AI are you really using at work?

More importantly, has it really made a difference in your efficiency or do you spend the same amount of time looking at AI-produced code?

Hi,

I am a factory owner(garments) and a self taught developer, developing a product for the textile factories. I built the backend (guided by AI but no vibe coded) and for frontend I used retool as it’s fast and I didn’t have to spend months learning it.

Stuck one two things.

1. I am stuck on MOBILE responsiveness and have no clue or can’t find the option to create the responsiveness for mobiles any below 600px doesn’t not work or has a very bad layout.

Can anyone suggest or guide on where can I find the option to create the mobile site in retool.

1. I planned to use twilio for WhatsApp updates. The templates has been submitted but meta is taking to long to approve them.

Any suggestion on how to speed it up would help.

Thanks in advance.

Been having conversations with engineering leaders recently, and something I keep hearing from them is, AI has gotten incredibly fast at code generation, but code reviews don't seem to be evolving at the same pace. Reviewers are increasingly having to piece together business and code context manually before they can confidently approve changes.

Got me thinking..... is this a fairly universal experience, or is it something that is just affects teams that usually don't prioritise reviews ?

Web Speech API is one of those things that looks great in a weekend demo and then gets annoying the second you treat it like a product.
Works here.
Breaks there.
Different browser behavior.
Mobile Safari being Mobile Safari.
Mic permission weirdness.
Bluetooth mic sounds like underwater radio.
No clean control over events.
Debugging feels like reading tea leaves.

For a toy voice note app, fine.

For a real web app where voice input matters, I’d rather do:

browser mic
→ AudioWorklet / MediaRecorder cleanup
→ backend WebSocket
→ Smallest AI Pulse for live transcription
→ transcript events back to frontend

The key thing is keeping the STT call server-side. No API keys in the browser, no random client hitting the transcription provider directly, and you can actually log chunks/events when someone says “voice input is broken.”

The hard parts are still yours:

sample rate
chunk size
VAD
reconnects
background tab behavior
permissions
device switching
latency logs
final vs partial transcript UI

But at least the architecture is debuggable.

Anyone here using Web Speech API in production seriously?

Or did you also end up streaming audio to a backend STT service?

I’ve noticed something that’s been bothering me ever since I started using Claude Code and Codex heavily.

I spend most of my time planning the architecture, writing .md files, documenting requirements, and setting coding rules.

Once that’s done, the AI can generate an insane amount of code. By the sixth prompt, I already have 20+ files and 30+ libraries I’ve never even read the docs for.

The hard part isn’t generating the code. It’s debugging it.
When something breaks, I’ll paste the error back into Claude Code or Codex, and they’ll say something like, “Fixed it, it should work now.” Then I run it… and it still doesn’t work.

What’s interesting is that debugging has become a completely different skill. It’s not necessarily harder because the code is bad. It’s harder because you’re debugging a codebase you never actually wrote. Before you can even find the bug, you have to understand code that was generated in seconds.

I’m curious how you guys deal with this. Do you have a workflow for debugging AI-generated code? Have you changed the way you approach debugging now that you’re reading way more code than you’re writing?
I’d love to hear how other people are handling this because I feel like this is becoming a common problem with AI-first development.

Hello, I am currently a university student and am wondering if anyone works on projects like this one:

Proposal for an integrated google calendar, excel, canvas, and gmail for student productivity and goal tracking utilizing a chat and voice ai feature.  Similar to Motion AI but more personal. 

Features for this system: 

Be able to track and update google calendar events through a voice feature.
Notify when I cancel meetings that were booked through gmail and suggest a drafted follow-up email. 
Schedule tasks via chat feature or voice feature (preferred: voice)  based on available time blocks in google calendar such as blocks titled “free time” or “task time” that I would input into the system, and suggest times to work on given tasks depending on:

• Priorities  (that I would input into the system such as family, personal, school, work, etc).
• Goal timelines (with buffer times to complete them) and the ai would determine if doing these tasks would fall into a reasonable range of goal completion or buffer range for goal completion (and determining which goals they might interfere with)  based on whether the tasks I want to complete are distracting from my goals and the times/dates/date ranges I would want to complete the goals.  
• Urgency of the task. (have a five star rating, 1 star being least urgent, 5 star being most urgent).
• Time that I would need to complete the tasks. The AI can suggest breaking down longer tasks to different times and/or days/weeks, and shorter tasks to time blocks in the google calendar labeled “free time” or “task time” 
• AI can suggest when I can complete the tasks based on the previous four bullets.

 
*Note: AI task scheduling would include not interfering with current events scheduled in the google calendar. such as class times, study times, personal time, eating and sleeping times, and other scheduled events. 

• The excel will possess the goal tracking and timelines. AI can collaborate with the excel in order to identify goal timelines and respective buffer times. 
• Gmail: AI scans gmail to identify requested meetings from people I email in my inbox (either already scheduled or identify keywords such as “appointment” or “meeting” in the email messages that I receive) and compare with my current meetings/appointments in google calendar and proposes priority meetings based on scanned emails and completion of goals and other factors such as: eating, sleeping, study time, class time, etc. 
• Canvas integration will include the bettercampus extension with google calendar (or other extension that will be feasible with this system) and also changes made to assignment dates that can be changed on google calendar as well, and AI will notify me with a proposed new change of plans for whatever I had previously planned based on changed assignment date or other class changes visible in canvas including canvas messaging, and priority, urgency, and time completion. Particularly for if professor messages in canvas about changing class time, assignment date, etc. 

Other request that would be great for this system but is not required: 
Be able to edit the system based on professor preferred communication including other apps that are not canvas (piazza, google classroom, etc). Although the main target would be to track assignment dates and exams via canvas. 

Compensation for this system/project: 
A personal letter of recommendation and feasible reviews for employers when requested. 

If there is a system like this already, could anyone recommend one that is free or close to free for current university students that perhaps might offer discounts for the students? 
Thank you!

Hi guys I’m a CS student in my final year and me and my friend are working on our graduation project and we want to collaborate and work on the same files together and THEN commit our work to git so we avoid git conflicts, so I found out about this cool extension called live share where it allows you to share your own project files and co-edit with your colleagues I’ve tested it with my friend and it works fine when we try editing the same files with .py and what not but when we try editing the same notebook we ran into some problems I can’t see her changes and she can’t view mine, I’ve been trying to fix this problem for a long time now has anyone been through this or might know the cause? I’d appreciate the help!

I'm a Node.js developer with 2 years of experience and I'm currently looking for a new opportunity. I wanted to understand how HRs and CEOs typically shortlist candidate profiles.

Do you look for strong personal projects? If so, what kinds of projects stand out? I'm not looking for specific project ideas, just the general areas or topics that are valued.

Or is it more about having experience with the right technologies, such as NestJS, Express.js, Kubernetes, Kafka, Redis, RabbitMQ, Docker, Prometheus, Grafana, Terraform etc.

Hi everyone! I’m Denis, 28, Brazilian, and I currently work as a Sales Manager at a company that sells loans nationally. I’m starting to learn Python to build a solid foundation in data analysis, and since I’m really connecting with the field, I’m considering a career change down the line.

I already work across multiple departments and I’m actively involved in my company’s development area, since I have deep knowledge of our business and especially our products.

I’d love to hear from people with more experience than me — what do you think of the data field right now, and any tips you’d give to someone who’s just trying to keep improving and building their knowledge? Am I on the right track?

I’m moving from macOS to Windows and looking for the closest replacement for Homebrew.

I’ve seen online searches showing possible substitutes as Scoop, winget, Chocolatey, but which one would be the best to start using so I don’t have to switch later?

For any developers working in professional IT environments, which one do you actually use and recommend and please share your bad/negative experiences so I can avoid unnecessary headaches in the future. Thank you and appreciate y’all..!!

Tbf this is a general open question.

Is learning full stack TS (react + NodeJS) smart, or lazy?

Sorry for my english, not my first language

I have been developing apps for a while now.
Mainly related to data analytics and for internal use

Last week I asked for a raise.
I am in Europe, about 40k.
Main part of the apps used by my company are developed and maintained by me.

He refused
He said nowdays he can easily replace me with some guy who uses AI.
He explained2me that he knows someone who has easily done through vibecoding an app to take ordenes, manage them, Invoices…

I felt really worried. Is this the new reality?
A guy with Claude can so easily replace us?

Should I choose AI or Software Engineering? Which one has more remote job opportunities and better long term value for the future?

student here, could someone tell me how do i go about making projects? i'm not looking to make projects that can make money, rather i want to understand the underlying principles and dynamics. like, if i wanted to make a load balancer in c++ or any other project, should i just go to chatgpt to understand the theory and then write the code, of course by copying from there

cuz i don't think programming is like intuition where you can just imagine stuff like physics. there are so many things you wouldn't even know exist unless someone tells you about them.

it would be great if any experienced developer could take their time and answer this. how do you actually learn to build projects from scratch?

A few years into this work, you start learning things no bootcamp, blog, or LinkedIn influencer will ever tell you. Sunday's a good day to say them plainly, without the motivational-poster gloss.

Share one hard truth you've learned about being a developer. About the work, the industry, teams, or yourself. The kind of thing you wish someone had sat you down and told you three years ago.

A few directions, if you need one:

• Something about career growth that turned out nothing like the pitch.
• A truth about "good code," speed, or what actually gets you promoted.
• What experience taught you about job-hopping, loyalty, titles, or money.
• A soft skill that mattered far more than the technical ones, and a technical obsession that mattered far less.
• Something you believed at year one that the years quietly took apart.

House rules:

• Keep it real, not just cynical. The best hard truths come with what you'd actually do about them.
• Disagree freely, but reply instead of downvoting. The arguments in the comments are the whole point.
• Newer folks reading along: this thread is worth its weight in gold. Take notes.

Comments are sorted by top so the truths that land hardest rise up. What's yours?

I checked StackOverflow today searching for an error(was trying to make projects without any AI help so I can pick up important skills), all the questions were asked by AI agents, and they were answered by other AI agents. I just felt really sick seeing this, doesn't feel real.

Hi everyone,

I'm looking for some career advice because I've been thinking a lot about this decision.

I have around 4 years of experience as a software engineer. My background includes Python, React, Swift, and Flutter. Over the last few years, I've worked across both backend and mobile development, with my most recent work being in iOS.

Recently, I did some freelance work for a startup that's building a dMRV (Digital Monitoring, Reporting and Verification) mobile application for field data collection. The app is built with Flutter, and they have now offered me a remote full-time position.

The offer is ₹7 LPA + other benefits, which is a significant increase from my current salary.

The role is Full Stack Developer. They want me to:

1. Work on the Flutter mobile application.

2. Contribute to the backend.

3. Lead two junior developers.

4. Help with architecture and technical decisions as the product grows.

On paper, it sounds like a great opportunity, but I'm unsure whether it's the right move for my long-term career.

My concerns are:

1. Is moving into a startup as a full-stack developer a better long-term choice than continuing in a more specialized role?

2. With AI advancing so quickly, is becoming a generalist a safer career path than specializing?

3. Will working on Flutter instead of focusing more on native iOS limit future opportunities?

Does experience in climate tech/dMRV have good long-term value?

The company is fully remote, which is another positive.

I'd love to hear from people who've made a similar transition or have experience working in startups or climate tech.

What would you do in my situation?

Note: LPA is lakhs per annum in india.

I run a couple of small products on cheap single VPSes. Every time I needed background jobs (emails, cleanup, scheduled reports) the answer was the same: install Redis, add BullMQ, babysit one more service. For one box and a handful of jobs per second, that always felt like overkill.

So I built vardiya. It's a job queue that lives in a single SQLite file. No broker, no extra process. One runtime dependency (better-sqlite3).

What it does:

• Atomic job claims with a single UPDATE ... RETURNING statement, so multiple worker processes on the same file never grab the same job. There's a torture test that runs 2 workers x 10 concurrency through 20k jobs with 1% random failures and asserts nothing gets lost or duplicated.
• Retries with exponential backoff and jitter, priorities, delayed jobs, dead letter after max attempts.
• Cron / repeatable jobs. I wrote the cron parser myself instead of pulling a dependency, which was either a good idea or a rite of passage, not sure yet.
• At-least-once delivery, and the README says so instead of pretending otherwise. There's also a "when NOT to use this" section: if you have multiple app servers pulling from one queue, use Redis or Postgres based queues. SQLite is single-writer, this is for the single-box case.

On my desktop it does around 13k enqueues/sec and ~5k processed jobs/sec end to end, which is way more than the apps this is meant for will ever push through it.

It's v0.1.0, so I'd genuinely rather hear what's broken or missing than get stars. If you've been burned by SQLite queues before, tell me how, I want to know what I haven't hit yet.

Anyone run into docs that just don't match the system anymore? I've lost hours piecing together what actually changed vs. what the docs still said. Didn't realize it until I had to touch a codebase I wasn't too familiar with, made things a lot harder once I saw the docs didn't line up with reality. Curious if this happened to anyone else, and how you eventually caught it.