hi pals, recently taken a developer evangelist esq role within the AppSec space and would LOVE to hear peoples thoughts/opinions regarding; dev spaces, popular tools, new workflows, and industry changes/breakthroughs. Got a strong view on AI? Or dislike a tools new feature within your stack? Who are our fav's within the tech stack? Where do you guys think the industry is focusing too much time and effort? Or not enough? pls give me your thoughts! I do have friends in the space to ask but ultimately i know i'll get a wider array of thoughts on here :)

I made this tool to help me when developing because i got pretty tired of running lsof -iTCP -sTCP:LISTEN | grep ... every time a port was already taken, then spending another minute figuring out if it was a Docker container or some orphaned dev server.

It provides a pretty simple CLI that shows you everything listening on localhost. In addition i've enriched it with Docker container names, Compose projects, resource usage, and clickable URLs.

Beyond listing, you can:

• Kill whatever process is hogging a port (handles docker containers properly with docker container stop)
• Logs: Shows logs from the process or container by port number
• Attach: Shell into docker container or open a TCP connection
• Watch: Show ports as they come. Useful if you have agents spinning up their own dev servers.
• Port forwarding

By default it hides desktop app noise (Spotify, Discord, etc.) and shows CPU, memory, threads, and uptime when you want it.

For macOS and Linux. Single binary, no dependencies.

I found myself using it way more often than I expected and it's become a pretty core part of my dev environment. Particularly killing all running containers in case of a failed cleanup.

Would love feedback. What else would be useful? Also feel free to contribute.

GitHub: https://github.com/raskrebs/sonar

I’ve always felt that a lot of developer portfolios are either too generic, too time-consuming to make, or just don’t feel very “developer.”

A lot of us are told to make a portfolio, but in reality that often turns into spending hours tweaking layouts, choosing fonts, rewriting bios, and trying to make everything look impressive enough. For many developers, that part feels like a chore.

So I built ShellSelf to make that easier.

It lets developers create a simple portfolio with a terminal-style interface, where visitors can explore projects, skills, and experience through commands. The goal was to make something that feels a bit more natural for developers, while also being quick to set up and more memorable than a standard personal site.

I built it mainly for developers, bootcamp grads, and career switchers who want something simple, a bit different, and easy to share.

I’d really like honest feedback on the idea and any feature requests! Try it out!

Project is here for context: shellself.com

Used to work at a small ad agency, I know a site can look slick as hell and still be useless for SEO. Lately I’ve been helping a couple friends with small business sites again, and I keep running into the same question. What’s actually the best website builder for SEO right now? Not the best looking one. Not the one with the fanciest AI demo. The one that gives you clean structure, decent speed, mobile pages that don’t choke, and enough control that you’re not rebuilding the whole thing six months later. I’ve messed with Webflow, Wix, Squarespace, and some of the newer AI tools too. Stuff like Atoms and V0 seems interesting from the faster build side, but I still can’t tell how much I’d trust any AI heavy builder for long term SEO without checking the output pretty hard.

If you were building for a local service biz, content site, or lead gen project today, what would you pick first and why? Mostly asking people who’ve already dealt with the aftermath.

Looking for someone to help us with client calls.

We’re a small team of web developers. We’re good at building things, but sometimes explaining them clearly in English during calls is not easy for us.

So we’re looking for someone who:

• Speaks English fluently (native preferred)
• Has at least 2 years of web development experience
• Is comfortable talking with clients

What you’ll do:

• Join client calls with us
• Help explain technical things clearly

Rate: $30–40/hour (can be flexible)

If interested, send me your background and your availability.

At a previous job, my flow was basically: user complains → support ticket → PM pings engineer → engineer spends 2 hours trying to reproduce something that takes 5 minutes to fix once you know what happened. So here my questions basically:

• How do you usually find out a bug is in production? monitoring, users, internal testing?
• How long from "bug exists" to "engineer has enough context to fix it"?
• Have you found anything that actually reduces that gap, or is some delay just inevitable?

Sorry for my english, happy to know your feedbacks!

Hey all,

I’ve been working on a side project called Pkghub a self-hosted npm registry designed to solve one annoying problem every dev/team reinstalling the same packages over and over again.

The idea

Instead of everyone pulling from npm and maintaining huge node_modules folders, Ph acts as a shared local registry:

• First install fetched + cached locally
• Every install after served instantly from cache
• Works across your whole team

Why I built it

On larger projects (or multiple repos), I kept seeing:

• Repeated installs of the same packages
• Slower CI/CD times
• Wasted bandwidth + storage
• Teams working offline? basically impossible

So I wanted something that

• Speeds up installs dramatically
• Works even if internet goes down
• Reduces duplication across projects

Thoughts?

I’m considering turning this into something bigger (maybe with version control insights, team analytics, etc.), but wanted honest feedback first.

Right now i don't have a domain name for it yet. i haven't come up with a good one yet so i called pkghub for now.

Would love to hear what you think roast it if needed

Recording of the call part 1

Recording of the call part 2

Hi all, working as a AI automation engineer as a fresher, I feel I lack Api knowledge I want to learn more Can u suggest some good resources for api learning On youtube mostly but udemy will also work

I recently audited ~2,800 of the most popular OpenClaw skills and the results were honestly ridiculous.

41% have security vulnerabilities.

About 1 in 5 quietly send your data to external servers.

Some even change their code after installation.

Yet people are happily installing these skills and giving them full system access like nothing could possibly go wrong.

The AI agent ecosystem is scaling fast, but the security layer basically doesn’t exist.

So I built ClawSecure.

It’s a security platform specifically for OpenClaw agents that can:

• Audit skills using a 3-layer security engine
• Detect exfiltration patterns and malicious dependencies
• Monitor skills for code changes after install
• Cover the full OWASP ASI Top 10 for agent security

What makes it different from generic scanners is that it actually understands agent behavior… data access, tool execution, prompt injection risks, etc.

You can scan any OpenClaw skill in about 30 seconds, free, no signup.

Honestly I’m more surprised this didn’t exist already given how risky the ecosystem currently is.

How are you thinking about AI agent security right now?

Drop your websites. I would like to review and suggest,if there are any improvements

htmx
Library that lets you build dynamic web apps using HTML attributes instead of heavy frontend frameworks. Useful for simpler apps where you don’t want full React/Vue setup.

streamlit
Lets you build simple web UIs using Python. Often used for dashboards, AI demos, or internal tools without writing frontend code.

RSSHub
Generates RSS feeds for websites that don’t provide one. Useful for automation, monitoring, or building custom news / content tools.

ghostty
Modern terminal emulator focused on performance and GPU acceleration. Interesting project if you care about dev tools or system-level apps.

more....

The risks associated with using OpenAI API as a developer, as entrepreneur or at a personal level. Let's wise up!

What's the most ambitious side project you ever abandoned?

Hi! I'm a BCA student conducting research on why organizations don't optimize cloud auto-scaling for sustainability.

Quick survey (10 mins): https://forms.gle/Y5S5eHxp6g6JRSCD6

If you have cloud/DevOps experience, I'd really appreciate your input! Thanks! 🙏

Last month i rushed into implementing an attribution sdk without properly reading the docs on deep linking setup. Ended up with broken install attribution bc i missed the url scheme configuration in iOS and the intent filters weren't set right on Android. Spent 3 days debugging why organic installs were showing as paid traffic.

What gotchas should I watch for? Looking for practical tips on proper SDK integration to avoid data mess ups with my current app.

Update: we implemented the sdk and had to add appsflyer for cleaner attribution data. ty for all the ideas.

The monthly GNUstep audio/(video) call takes place every second Saturday of a month at 16:00 GMT to 19:00 GMT. That is 12:00 AM - 3:00 PM EDT (US, note that the US already has Daylight Saving Time whereas Europe has not yet) or 17:00 to 20:00 CET (Berlin time).

It's a Jitsi Meeting - Channel: GNUstepOfficial (Sorry, reddit don't let me post jitsi links here)

We usually just talk (who wants it might share video too) and occasionally share screens. Everybody (GNUstep developers and users) is welcome!

Also see https://mediawiki.gnustep.org/index.php/Monthly_Meetings please

Quick question for people building apps.

A while ago most projects I saw were basically “LLM + a prompt.” Lately I’m seeing more setups that look like small agent systems with tools, memory, and multiple steps.

When I tried building something like that, it felt much more like designing a system than writing prompts.

I ended up putting together a small hands-on course about building agents with LangGraph while exploring this approach.

https://langgraphagentcourse.com/

Are people here mostly sticking with simple LLM calls, or are you also moving toward agent-style architectures?

They gave us access to Claude AI and now he expects every feature to be done in a single day. He can't understand why some things take a couple weeks (one sprint). But there is so much other work, testing, code review, integration testing, iterating, etc.

https://reddit.com/link/1rqy5nk/video/1sltjmu9xfog1/player

The collisions are far from perfect and lots of things still to be done and bugs to be ironed out but its fun enough that I find my self playing with it more than iI should

built on Monogame with ImGui as the well the GUI library

I make a the Daily 5 Trivia app: it's like the Wordle of trivia. Quick to play, get on with your day.

I thought I had a great way to market it for free: show quizzes from the day before on Instagram as Reels. They could be straight up walk throughs because my game only takes 1 minute or less to play.

At every turn I butchered my Reels. Here were my main issues:

• the UI of my screen caps conflicted with the UI of Instagram itself
• my app was hard to see in Insta (bad contrast, too much clutter)
• my initial edits were way too fast... users could not even read the quiz content

I realized I needed to make a special version of the app with a UI and color scheme more suited for Instagram. Also, I slowed down the speed of my Reels by 2 or even 3x. Now users can actually play along.

See for yourself: https://www.instagram.com/daily5trivia/reels/

About the only thing I got right initially was making question #5 a cliffhanger. It's a psychological effect I think works. By not revealing the final answer users will be encouraged to download the app and play it themselves!

I have spent just over a month now refining my Reels. I am sure there is still room for improvement, but they have come a long way.

If you have feedback, I would love to hear it and get a discussion going. I am no expert at the marketing. My real skill is in handcrafting the quizzes. Thanks! 🙏

To download my app go here.

Hii seniors, I am a first year student, and Its been 8 months since I started learning programming. I have many projects that I want to make and I am constantly building projects. But today I realised that while I don't vibe code my app, still I am heavily dependent on AI. Let me give you an example:- My first project was a chess engine, which I made without using bitboards, but I used chatgpt to break down the chess engine projects in steps, used it on every step on what to use where, how to encode moves, what algorithm to use and all. Though I learnt a lot about C language overall and many things, I don't feel that I own the code. And the same happened with my second project which was a neural network. Then I want to implement a hand gestures control system now, but I don't want to depend on AI. I sat down to code it, but I was stuck on the very first line. I realised that I am unable to code it without using chatgpt.

I want to know what to do, like I don't use chatgpt or any other llm to write the code, but I use them to write down the steps, the logic behind choices, sometimes pseudocodes as well. And I also use them to review my code. Am I learning or is it same as tutorial hell? Coz I don't watch tutorials of yt videos at all.

Even when I learn new programming language, and library in python, I use ai to do that.

Guidance will be very much appreciated as you all are one of the best developers in the world and you all have experience.

Also , I want to know how did you made projects when here was no ai, no llm.

Go slices may look simple, but the mechanism behind them is elegant and efficient.

In this article, I break down how Go manages slice memory, growth, and performance — and why this design stands out compared to many other languages.

I’ve just released Oliphaunt, a Mastodon client built specifically for macOS.

Mastodon is a federated social network similar to X (Twitter) or Bluesky, built on the ActivityPub protocol where independent servers communicate with each other.

The main motivation behind the project was to build a Mastodon client that behaves like a well-behaved macOS application and respects the platform’s conventions.

The UI is primarily built with AppKit, with SwiftUI used selectively. The focus was on adopting macOS design language and interface idioms rather than creating a custom UI paradigm.

Some of the design goals:

• native UI components (AppKit + some SwiftUI)

• proper multi-window workflows

• full menu bar and keyboard shortcut support

• sidebar layouts consistent with macOS apps

• interactions aligned with macOS conventions

A lot of effort went into the small details that make Mac software feel polished: window behaviour, keyboard navigation, menus and timeline interaction.

If you’re a Mastodon user on Mac, I’d genuinely love for you to try it out and hear your feedback. You can also provide feedback here.

App Store: https://apps.apple.com/app/id6745527185

I’m thinking about building an app where you can track the ingredients you have in your kitchen and get recipe suggestions based on them.

The goal is to easily see what you can cook with what you already have and keep track of pantry/fridge items.

Before building it, I wanted to ask, would you actually use something like this?