We had a fun one on a mobile banking support project. Not fun at the time, obviously.

About 40 minutes after a release, transfers started slowing down. Then came the 502s. It was payday too, so traffic was already higher than normal.

First reaction was to restart the services.

Bad call.

Every restart dropped the warm database connections, and the load spiked again. We were basically making things worse while trying to fix them.

Turned out the release had changed the DB connection pool settings. Once we found that in the deployment logs and rolled back, things settled down within a few minutes.

The other mistake was communication. The engineer working on the incident was also trying to answer questions from the bank's operations team, which had support lines filling up.

We changed that afterward. One person handles the incident, another handles updates. Even if the update is just "still investigating."

Curious if anyone else has had a seemingly harmless recovery step make an outage worse.

I'm a software developer working at a bank, and I feel like we're way behind when it comes to AI adoption.

Every time AI comes up, the conversation is mostly around security, compliance, data privacy, etc. I understand these are important, especially in banking, but it feels like we're moving extremely slowly.

For example, our bank deployed a GPT model through Azure AI Foundry and built an internal ChatGPT-like interface for employees. That's pretty much the extent of AI adoption I've seen so far.

Meanwhile, I keep seeing people talk about using Claude Code, Cursor, AI agents, and building AI-powered features using LLM APIs.

I'm curious how things work at other companies.

• Are you actually building AI-powered features using APIs from OpenAI, Anthropic, etc.?

• How does your company approach new AI initiatives? Do developers get to experiment and propose ideas, or does everything have to go through multiple approval processes?

• How are you handling security and compliance concerns when integrating AI into existing applications?

• Are companies actually using AI agents and automation in production, or is most of it still experimentation?

I'm especially interested in hearing from developers working at banks, fintech companies, or other large enterprises.

I want to understand what real-world AI adoption looks like beyond just building an internal ChatGPT wrapper.

How is your company approaching this? Are you seeing meaningful AI adoption, or is it mostly hype and internal chatbots?

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Hi everyone,

I'm looking for a project idea that solves a genuine problem faced by developers, engineering teams, or businesses.

I want to build something beyond a standard CRUD application, with a strong focus on backend engineering.

I'm interested in exploring areas such as:

- API design and reliability

- Distributed systems and event-driven architecture

- Database performance and data consistency

- Developer productivity tools

- Monitoring, debugging, and automation

I'd particularly appreciate suggestions based on problems you've personally experienced at work or in your own projects.

Three questions:

1. What repetitive or frustrating technical problem do you face regularly?

2. What tool or workflow do you wish existed, or worked better?

3. If someone built a small, reliable solution to this problem, would you actually use it?

I'm open to using Java or another language if the problem calls for it.

Thanks!

With the recent PHP security vulnerability making headlines, I'm wondering how much impact this could have on the PHP job market in the long run.

I'm currently working as a PHP developer, and with all the AI disruption already happening in IT, news like this makes me question the future of the tech stack even more.

Could this push companies towards other technologies, or is it just another security issue that will eventually get patched and forgotten?

Would love to hear from experienced PHP developers and people involved in hiring. Are you seeing any changes in demand for PHP developers? Is it still worth investing in PHP/Laravel, or should developers seriously start preparing to switch stacks?

Hi builders,

I m a software engineer with 25 years coding experience, so i guess i have a deep understanding of software. Recently i start using claude code and cursor ai, it is amazing and give me 100x productivity, and i never need to code by hand anymore, and it open an opportunity for non technical users to start building thing, which is awesome.

Then i start wondering, is backend and database really necessary? I mean yes of course you need data, then you need backend logic to handle data, provide APIs or handling OAuth. But do we really need backend and database ?

Lots of vibe coder are not technical to handle server and database setup, https, ngnix….etc. And i think the current cloud services are built for scalability and still require infrastructure knowledge to setup and management , by eliminating backend and database we can make vibe coding more easy and enable more non technical users to deploy their project to live.

hi all! I am interested in becoming a backend dev as I like the logic side and problem solving aspects.

Is learning the JS, MySQL/PostgreSQL (or MongoDB), and Node/Express enough to get started in that field?
I have taken a bootcamp for full-stack web development and I really liked the backend side of things and would like to pursue that but I am not sure with junior roles becoming more scarce.

Thank you!

Hello, I'm confused on what type of projects a beginner should begin with and to continue the journey of learning backend dev.

Is there any good reliable roadmap of projects to follow, which will allow me at the end of the day, to gather the experience to land a job?

Especially the link I provided, since I cannot be the judge of deciding is it actually worth following it.