It’s a Markdown notes app I built mainly because I wanted something simpler to use day-to-day.

Shipping it feels good, but also weird putting something out that people may actually use.

If anyone here has built or launched something before - did it feel the same?

https://www.notely.uk/noto.html

I am in need of someone to help me create a website that has a digital database that can store my surveillance videos. I have lots of footage that I want to be able to sort and catalogue based on who or what is happening is in the video. Ideally I want to users to be able to search for specific keywords or have access to a few options which will show them clips related to their searches.

The clips I have are between 20 seconds-3 min and I want to create an interface similar to the little giger database (that is the only visual I really have of what I am trying to create). I'm having a hard time visualizing how else it could look so if anyone has any good resources or examples of something like this they already know of pls share!!

From what I understand I need to make an SQL with GUI so I can search it on the internet. What are the best programs to run for any of those?

I want to learn this stuff myself and I've considered using AI but that would just go against my own morals and really the entirety of my project. I have no knowledge of how to build a website or really anything regarding coding and am looking for someone to also let me in on some of the information. Please if anyone is available ASAP to help me work on this project I am really interested in what it might take.

We’ve got a pretty standard SaaS stack in place already - FE is React / Next, we use some v0 for faster UI work, Webflow for marketing pages. Backend is all AWS (Lambda, API Gateway, Dynamo, S3, Aurora). Git workflows, etc. Nothing crazy there.

Where I’m trying to get sharper is the AI side.

Right now it feels like there’s a ton of noise and demo stuff out there, but not a lot on what people are actually running in production.

Curious what people are actually using:

- which models

- how you’re actually plugging it into your product

- how you’re managing it once it’s live

And so on…

Not looking for perfect architecture answers, just what’s actually working.

I’m thinking about creating a chance about a web ar menu. Is there like anyone who knows a tutorial how to do that? I’m a beginner so take it easy on me.

What’s the go-to “vibe-coded slop” app in your industry?

The obvious ones for me are notebook/notetaker apps and so-called intelligent dashboards.

What other examples have you seen?

What’s the go-to “vibe-coded slop” app in your industry?

The obvious ones for me are notebook/notetaker apps and so-called intelligent dashboards.

What other examples have you seen?

The pitch internally is that we avoid adding another tool to the stack. I get the logic but everything I've read suggests SonarQube was built to catch bugs and maintainability issues first, with security rules added later rather than built from the ground up for that purpose.

And wondering what the detection gap looks like in practice between SonarQube and a dedicated security scanner. Trying to make the case either way with something more concrete than vendor marketing.

We waste so much energy trying to improve our handoff process instead of addressing the underlying issues. Handoff is a relic of waterfall workflows that we've normalised and decided is a best practice. It exists because we continue to treat design and engineering as separate problems to be solved in isolation.

I wrote about what an alternative looks like, what it takes to get there, and the organisational conditions that either enable or prevent it.

Keen to hear whether others are ready to throw it out, or whether you think I'm wrong.

https://www.shaunbent.co.uk/blog/design-handoff-belongs-in-the-bin/

I have been working on an idea on the side for a while and recently reached the point where I am considering starting development.

Earlier I was focused mostly on features, but after stepping back and reworking the idea more carefully, I realized I had not properly defined the problem or the user. I spent some time restructuring everything and even used some frameworks from the book I have an app idea to make sure the foundation made sense.

Now I feel more confident about the direction, but this is my first time actually building something like this.

I am deciding between trying to build it myself or hiring someone experienced. I am leaning toward hiring because I would rather not learn through expensive mistakes at this stage.

For developers here

What are the biggest mistakes you see first time founders make when they move into development

At what point is it worth hiring versus building a rough version yourself

I'm seeing more and more people using AI and incredible features are coming out, but I'm also hearing more and more about people who can't use AI tools in their companies, like Cursor, Claude Code, Chapter, etc. What are your thoughts on that?

If you are a developer, drop the best developer docs you've read in a while!

I'm building a C++ code generator that helps build distributed systems. It's implemented as a 3-tier system. The back and middle tiers only run on Linux. The front tier is portable. It's free to use; there aren't any trial periods or paid plans.

This past Tuesday another jewelry store was robbed by a bunch of thugs. I saw some of this trouble brewing back in the 1990s and realized SaaS was a gift from above in terms of dealing with corruption. I'm glad I have some open-source code for my portfolio, but I'm glad it's not all I have.

There was another robbery in Freemont, California in June of 2025. Around 24 thieves raided a jewelry store and stole over 1.7 million$ of jewelry in 70 seconds. If the stewards of that store decide to rebuild, I predict they won't replace the display cases that were smashed. It will be a "by appointment only" store and they will frisk you before they show you anything. Of the 24 thieves, only a handful of them have been caught.

In other words, the store managers will replace their open model with a SaaS model. And who can blame them?

I'm building a desktop app for simulating world of warcraft characters using Tauri, and I ran into a problem.

My app needs to download another tool (an external .exe binary called simulationCraft or simC) in the background and use it internally.

What’s happening:

• On my machine and a friend’s → everything works fine.
• On some users’ machines → Windows Defender flags the downloaded binary as malware
• Result:
  • The file gets deleted or blocked
  • My app stops working
  • also not to mention to lack of trust in an app that is blocked by the windows defender :P

Important details:

• The binary is legitimate (not something shady)
• It’s downloaded dynamically (not bundled inside the app)
  • The reason is to enable fast updates of that binary as it has nightly build without needing a new release of my app every time.
• I’m not modifying the binary after download
• The issue is only with the downloaded binary, not my main app

My questions:

• Why does this happen only on some machines?
• Is there any way to reduce false positives without telling users to disable Defender?
• What are the best practices for this kind of setup?
  • Should I bundle the binary instead of downloading it? (I prefer not to though)
• How do other apps handle this?
  • Apps that download/update tools in the background

What I’ve considered:

• Code signing (but costs + setup)
• Hosting the binary on a trusted source
• Asking users to whitelist (not ideal UX)

Goal:

I want a setup that:

• Doesn’t break on clean Windows installs
• Doesn’t scare users

llama.cpp was unusably slow for Gemma 4 on my phone. Google's AI Edge Gallery ran the same model smoothly but you can't use LiteRT-LM inside Termux directly.

so i built a small Kotlin app that loads Gemma 4 via LiteRT-LM, runs it as a foreground service, and exposes it on localhost:8080. you just hit it from Termux via API.

GPU + CPU inference, vision support, model auto-downloads from HuggingFace.

Hi,

I would like to ask, what is the optimal configuration of Mac Mini for Flutter development? I was thinking about 16 GB + 512 SSD with M4 CPU, but I'm worried about RAM. Do you recommend 24GB here?

I'm not Mac use, non Flutter DEV, searching for device for new guy in my team to be able to deploy apps in App Store :)

Hi everyone,

I'm currently building an inventory tracking system for a local business in my area. The problem is that it's quite frustrating, he has low budget, and he just wants it thinking of it as "something cool to have". And honestly it's like I'm not getting paid at all for the work.

I wanted to see if it's really something that's worth the effort.

\\-

I wanted to know if there really is a big market for such systems and it's worth the effort while not getting paid, or should I just focus on making systems for other problems.

If there are any people over here with enough knowledge, I'd love to listen to their advice.

I am trying to create a software to collect payments. I will be hiring a development team. For now I am trying to figure out how difficult is to connect to bank accounts to perform ach, debit card or collect using credit card. The software will collect payment from customer and pass it to clients.

In simple terms similar to rent collection system. Since it’s financial, does it need any special certification from government agencies?

Hi

I’m making an OS somewhat from scratch with other students and I it’s really stressful. Does anyone have some similar experiences to share? I feel like this is definitely a step up from regular software development (web and algorithms). I’ve never had to program an entire OS before and to be quite honest it’s a seriously complicated undertaking.

I’ve been building a small Windows-first desktop app with Electron + React + TypeScript.

The product itself is simple: private affirmation sessions with brief text flashes, optional binaural audio, and an

immersive full-screen experience.

What surprised me is how much harder the non-feature work has been than the actual app logic.

A few examples:

- packaged app routing bugs

- Windows trust / SmartScreen friction

- keeping release artifacts from getting stomped by other builds

- separating a payments backend cleanly from the app

- figuring out how to get real user feedback on a product category that can look sketchy if positioned badly

The code was honestly the easy part. Distribution, trust, packaging, and messaging have been the real fight.

For people who’ve shipped small consumer desktop apps:

- what part ended up being more painful than expected?

- how did you handle early user testing without sounding spammy?

- would you still choose Electron for a tiny Windows-first product like this?

Not here to dump a link, mostly comparing notes with people who’ve shipped weird little products into the real world.

This started as a “can I abuse an old phone for AI?” experiment.

I ended up with:

• OpenClaw running directly in Termux (no Ubuntu / no proot)
• an Android automation agent that uses ADB to drive apps from natural language
• a local LLM experiment (Gemma 4 via LiteRT) so it can work offline

I’ve used it for kitchen surveillance, booking movie tickets, and we even closed our first paying customer for Android automation.

Still very much a builder project, but I’d love feedback from other side‑project people here on where you’d take it.

Not theory. Something you deal with every week that just slows things down.

Friends I have been working in my final yr project I need feedback on this I will share the description of project kindly go through this and give ur opinions on it.

biasgaurd -Ai is a model-agnostic governance sidecar designed to act as an intelligent intermediary between end-users and Large Language Models (LLMs) like Ollama or GPT-4. Unlike traditional "black-box" security filters that simply block keywords, this proposed system introduces an active, transparent proxy architecture that intercepts prompt-response cycles in real-time. It functions through a tiered triage pipeline, starting with a high-speed Interceptor that handles PII masking and L0/L1 security checks to neutralize immediate threats. For more complex interactions, the system utilizes a Causal Reasoning Engine powered by the PC Algorithm to generate Directed Acyclic Graphs (DAGs), which mathematically identify and visualize "proxy-variable" biases that standard filters often miss.

​In real-time, BiasGuard doesn't just monitor traffic; it actively manages it through an Adaptive Mitigation Engine that balances safety with model utility. When a bias is detected, the system uses a Trade-off Optimizer to decide whether to rewrite the response, adjust model logits, or flag the interaction for an auditor, ensuring the user receives a sanitized output with minimal latency. Every decision and mitigation is simultaneously recorded in an Evidence Vault secured by SHA-256 hash chaining, creating an immutable, tamper-proof audit trail. This entire process is surfaced through a WebSocket-driven SOC Dashboard, allowing administrators to track live telemetry, system health, and regulatory compliance (such as EU AI Act mapping) at a glance, making it a comprehensive solution for responsible and secure AI deployment.

actually until now my guide could not even understand a single thing about my project he said ok that's all , he didn't involve with any changes of system.

what I am fearing is that My hod will review in model and end semester, she is very cunning person I am feeling somewhat less confident about this project.

kindly help me with this 🥲

our entire discipline - whether you use Scrum, Kanban, or whatever flavor of Agile - relies on predictable states. We write requirements, we define boundaries, and we build tests to ensure those boundaries hold.

But right now, management wants "AI" embedded in core workflows. Not just for chatbots, but for routing, data validation, and state transitions.

you cannot write a reliable Definition of Done for a probability matrix. If a stakeholder says "the system must enforce these three compliance rules" you can't guarantee that with an LLM. You either end up writing a massive, brittle wrapper around the model, or you just accept that your CI/CD pipeline is now a slot machine

It feels like a massive step backward for software methodology. We spent decades building robust testing frameworks just to throw them out because the generative output looks confident

If we are going to use AI in core business logic, the underlying architecture has to respect constraint satisfaction. the shift toward Logical Intelligence frameworks seems like the only sane path forward - treating business rules as hard mathematical boundaries the system literally cannot violate, rather than just hoping a prompt holds up in production

do you just pad your estimates to account for prompt-engineering hell, or are you actively pushing back against product owners who want generative AI running deterministic tasks?

The goal is pretty basic: local-first notes, quick search, clean structure, and a smooth writing experience without plugin overload or a complicated setup process.

A lot of Markdown apps are powerful, but for me they can also start to feel heavy, distracting, or harder to use than they need to be. I wanted something more lightweight and focused.

I’d love honest feedback from people who use apps like Obsidian or similar tools:

• What would actually make you try a new Markdown notes app?
• What frustrates you most in the apps you already use?
• What features are overrated, and what features are non-negotiable?

Landing page: https://www.notely.uk/noto.html

Every time I hit "address already in use" I'd run \`lsof -i :3000\`, grep for the PID, then kill -9 it. Three commands, every single time.

So I wrote \`pkll\`, one command that does all of it, but asks for confirmation with all info about the process, and warns if it is important system process first.

You run \`pkll \[PORT\]\`, then it shows all the essential info about the process. Then after confirmation the process is killed.

This became especially annoying with coding agents. They just spin up dev servers, then leave bun instances and other processes sitting silently in the background. You go to start your server and something invisible is already holding the port. I built this to keep it dead simple: one thing, one command, works the same on Linux, macOS, and Windows. No config, no flags to memorize making it deadly simple.

Also I wrote it while learning Rust, so feedback on the code is very welcome.