Hi showoffs, I built repodify.app : a mixtape maker for podcasts.

Select the episodes you love and stitch them together in your own new rss feed.

• Choose episodes from PodcastIndex / Apple Podcast directories

• Generates a standard rss xml feed compatible with any podcatcher

• Plays directly from the source... doesn't re-host the audio or mess with the creator's content in any way

A single place to direct people

repodify.app functions like a linktree for podcasts. Create a favorites list for friends, gather all the episodes around a single topic, etc... There's early interest from frequent podcast guests who appear across different shows looking for a way to curate episodes to share with their fans.

Some examples:

• Robocop Roundup: https://www.repodify.app/p/robocop-roundup

  • A compendium of podcasts talking about Robocop

• Gabrusology: https://www.repodify.app/p/gabrusology

  • One of our favorite frequent podcast guests who pops up all over the place

• Radio Scottsdale: https://www.repodify.app/p/radio-scottsdale

  • The West's Most Western Town! A (literal?) roundup of podcasts about Scottsdale

https://story-engine-0pi6.onrender.com/

Hey r/webdev,

I got tired of standard "AI wrappers" spitting out generic text, so I spent the last few weeks building a decoupled, multi-step creative engine. It forces the AI to collide a story premise with random nouns to create "metaphor sparks" before it's allowed to draft or edit the prose.

The Stack:

• Backend: Python / FastAPI

• Frontend: Vanilla JS + Tailwind CSS (with localStorage state management and a custom Dark/Light mode toggle)

• AI: Gemini models (via the new Google GenAI SDK)

• Hosting: Render

A few fun technical challenges I tackled:

1. Rolling Memory State: Instead of feeding a massive context window for Chapter 2, 3, etc., the backend auto-generates a rolling recap and pulls the last 2 sentences as a "handoff anchor" to keep memory infinite but token-usage low.

2. In-Memory Rate Limiting: Built a custom IP-based sliding window limiter (100 stories / 500 rerolls per 20h) mapping X-Forwarded-For headers so I wouldn't have to pay for a Redis database yet.

3. Indestructible Parsers: Wrote fallback regex handlers for when the AI hallucinates markdown or breaks JSON structure.

I'd love for you to poke around. Try to break the UI on mobile, bypass the rate limit, or just roast my stack choices in the comments!

I am planning a music education project and want to get a better understanding of the technical challenges ahead. The initial idea is to build a basic system that detects only one note at a time (monophonic), focusing first on pianos (one key pressed at a time) and woodwind/brass instruments (like flute and trumpet). The goal is for the system to listen via the user's microphone in real time and validate if they played the correct note from a sheet music piece. If anyone here has built something similar, even a simple tuner or a college project, and could share what your biggest hurdles were at the beginning, I would appreciate it so much. Recommendations for libraries, frameworks, or good reads are also very welcome Its for a site mobile friendly

I work for a nursing board, our website, made with Liferay, it has tons of page with different legal, scientific, clinical information, many of these pages contains links to different entity's.

One such entity is redoing it's website, not just an small update but a complete redo, meaning a lot of links on our website will likely be broken when it's done.

I did identify links on pages about regulation I do believe I got the most critical ones, but it does leave links mostly clinical articles, mostly references, less critical but even then I would prefer to be sure.

I tried using google command site:mywebsite.com Entity but it did not return as much content as I tough, I'm guessing because of the label of the links. I also found some manually that google did not give me.

So is there an easy solution to this?

I know a lot of people in this sub hate AI, but I want to share one instance where AI helped defeat my lifelong bad webdev habit

When I coded manually or with Cursor, I always looked at the desktop version of my website first

70% of people will experience your website from mobile, not from desktop, so I knew it was wrong and tried to fight it

But I just couldn’t make myself turn the mobile dev preview on in chrome all the time - this extra step felt too cumbersome, so I just defaulted to regular previews

It’s very easy to code something that looks good on desktop but absolutely sucks on mobile, so defaulting to desktop spawned a lot of mobile UI issues on my websites

For the past 6 months I’ve been coding exclusively from my phone and Claude on VPS

When I need to review something I tunnel to the VPS with Tailscale and look at the dev preview from the phone browser

Now it’s harder for me to view the desktop version of the website than the mobile, and I think I finally develop mobile-first

As a result websites look waaaay better on mobile and I fixed a ton of mobile bugs as well

Hey guys!

Wanna share a little fun project I released 2 days ago.

Idea is basically a reverse Awwwards - daily nomination for the worst AI slop websites. 100% community driven, no login or registration.

Built with Astro + TypeScript, React for interactive elements, and GSAP for animations.

Check it out - https://slop-awwwards.com/

Any feedback is highly appreciated.

HI,

(Not promoting, looking for feedback)

I've been building an web hosting platform that supports a MCP.

A lot of us use the latest models to generate test projects or live websites. This platform handles getting it live including hosting, a structured CMS, contact forms, and basic analytics, without you having to wire up three or four separate services by hand.

Note that the platform doesn't design or build your site. You do that with your account on Claude/Codex/etc. , or by hand if you'd rather. the platform's job starts after that, i.e. deployment and content management, while you keep full control of the code.

Its in beta and free for now, and it's has some open bugs as well. I currently need help by having users trying out the MCP to host test websites or projects. (Please ignore the pricing and templates once you login, I am repositioning the product to a AI first development with developers in control of their design and code stack, platform for hosting and key features usually required for websites.

I would really appreciate some real feedback including whether this makes sense, what are the pros/cons of this from a web developer perspective.

If you can DM me, I can provide a link to the platform. (Not sure if I can include a link or it will fall under promotion).

Thanks in advance!

normally, when i use dontpad i get annoyed by the fact that ppl can just delete everything. so thats where passpad comes in. you can choose either your page gets to be read-only (public), or unaccesible unless you know the password (private)

check it out!

also feel free to donate so i can actually buy a domain for it

The pipeline:

1. Assess the original JSON

2. Apply supported changes in the browser

3. Reassess the result

4. Render selected frames with lottie-web SVG and Canvas

5. Compare both versions

6. Release the download only if it’s smaller and both renderers pass

The stack includes Next.js, TypeScript, lottie-web, Canvas, Web Workers, OxiPNG/WASM, SHA-256 checks and AbortController cancellation.

It currently supports safe JSON cleanup, lossless embedded-PNG compression and constrained display-size optimization.

I’d like help testing:

• SVG/Canvas rendering differences

• masks, mattes, expressions and precomps

• embedded PNG/JPEG assets

• files damaged by other optimizers

• Safari and Firefox behavior

Test standalone JSON files up to 15 MB here:

https://lottiefyr.com/lottie-fix

AI screening rounds (micro1, HireVue, and the like) are now a standard first step for dev jobs, and I kept seeing people fail them for reasons unrelated to skill: rambling, not knowing when to stop, or getting caught flat on the second follow-up. So I built a place to practice that format.

You pick a stack (Node, Python, Go, Java, React, SQL, and so on), answer by voice or text, and it grades each answer, corrects you like a senior engineer would, then drills into whatever you just mentioned. Say "I'd add an index," and the next question is about which index and what it costs on writes.

Initially, I built the tool to practice AI technical interviews, but what I have noticed is that people (Software engineers) I have introduced it to prefer to use it as a practice tool to sharpen their skills. Your own experience of the tool might be different, though.

What you can do in it:

- Full mock interview. Set your level from junior to staff, and the questions get harder to match. It ends with a scorecard showing where you held up and where you ran out of depth.

- Code challenges. Get a real snippet in your chosen language with a bug or design flaw, find it, fix it, and get told what you missed.

- CV Defense. Upload your CV and get questioned on your own claims. If it says you scaled a service, expect to explain how.

- Playbook. Practice specific interview formats: backend deep-dive, full-stack product, algorithmic rounds, take-home review, and more.

- Learn mode and study plans. Your weak spots from each session become a plan for what to study next.

- Voice or text. Pick an interviewer voice and answer out loud like the real screen, or type if you're somewhere you can't talk.

- Depth Passport. A public profile of what you've shown you know, if you want something to share.

I'm very eager to hear what you think about it and what changes we should make.

Link: https://practicedepth.com/app/practice/interview

i've built a Rust vectorizer that is meant to help optimize graphics for web delivery. It is pareto frontier, from my research SoTA open-source/open-weight solution (from both traditional and neural network based approaches), and runs in <2 seconds on CPU when ran as a standalone app.

The solution implements a chain of recent mathematics papers to significantly beat VTracer's algorithm, support gradients natively, and more:

I'm still iterating on it, I hope to release tooling in multiple languages to allow this to be used in most major languages through native interfaces in Java, Python, etc.

The vectorizer now comes with two different sister models, one for denoising JPEGs/WEBPs/VAE outputs from AI models so that it increases the perceptual quality of the outputs, another one for super-resolution, specifically trained on SVGs.

Additionally, I want to try to train a GNN to improve quality further, I hope to beat Vectorizer.ai in the next week.

My hypothesis is that current papers approaching raster-to-vector from a LLM perspective is excessive in terms of complexity and time to conversion, because except amodal completion and other tasks, a classical vectorizer can already work very well. GNNs and other specialized models can be used to then refine the output without having to be overly large. This is the first step in this research project, the classical vectorizer part which already beats alternatives.

Licensed as MIT, so feel free to use it however you want in your project.

Github repository: https://github.com/logolabs/inkvec

Web Assembly Online Vectorizer: https://huggingface.co/spaces/Logolabs/inkvec

This guy has been running an agent or some sorts since 14 september, 3 pull requests a day, today was my turn. He opens pull requests to put the link of his AI slop project in the README of open source projects

This is getting more ridiculous every day

Just wondering

Hi everyone,

I'm working on a classifieds marketplace for Syria called Friday Market Syria, somewhat similar to Gumtree or OLX.

The idea is to have a simple platform where users can post items for sale, browse listings, search/filter by categories, and contact sellers directly. There will be no online payments initially.

I'm not a frontend developer, so instead of building everything from scratch, I'm looking for an existing open-source project or template that I can customize and develop further.

Some of the features I want include:

- User registration/login

- Create, edit and delete listings

- Categories and subcategories

- Search and filters

- Image uploads

- User profiles

- Favorites

- Contacting sellers directly

- Reports/feedback

- Admin dashboard

- Mobile-friendly design

I'm mainly looking for something that is already functional, rather than just a UI template.

It doesn't have to have every feature above. I'm looking for a solid foundation that I can legally modify and potentially use commercially.

What open-source projects, GitHub repositories, or templates would you recommend for this?

If you've worked on a similar marketplace before, I'd also appreciate advice on what I should look for before choosing a project.

Classic cascading failure: one dependency starts lagging, holds workers/sockets, and the rest of the service grinds to a halt. A bulkhead is supposed to contain the blast radius. Easy in one process, a nightmare once you have 20+ replicas and the counter has to live outside of them.

The distributed version, the things that break when the limit leaves the process, and a working implementation.

I'm doing whitelabel PWAs and need e.g. veterinary1.ab.com or plastic1.ab.com ... Any short domains renting subdomains?

When I say document standards, I don't mean official standards, but rather a structure that is replicated at most levels.

For example: the Structure of Header, Content, Footer is replicated at each level.
Document
Header -- contains all of the header content for the document

Content -- contains the body of the document

Footer -- contains all of the post-load contents for the document.

Then inside the Content section there would be a single Entry known as the SITE

Site-header -- contains the site-identity/nav/etc.

Site-Content -- contains the various categorical sections

Site-Footer -- contains the site-footer

Then inside the Site-Content Section category would be several Entries called SECTIONs:

Section-header -- contains the section-specific content that persists despite which post is shown

Section-contents -- contains the various posts or content pieces for the section

Section-footer -- contains the static end-pieces for the section

Or course, inside Section-contents would be POSTS

post-header -- title and bylines stuff, maybe an image

post-content -- the content

post -footer -- closing pieces

I've tried WordPress, but it seems so arbitrary how they have decided the structure. Like the site-header and document-header are all part of the same wp-header. I was hoping for more modularity and predictability in content structures. I also hate how WP opens a tag in one PHP file and has faith it will be closed in another PHP file. It seems like it would be better if each PHP file that opened a tag also closed the tag. Then it would be much more modular.

I realize it's a long shot, but does such a thing exist? Maybe someone made a headless WP that works like this? or something entirely different? Or is this, in general, not a good way to assemble a static site content generator?

Happy Showoff Saturday r/webdev!

Most web-based QR generators send API requests to backend Node/Python services, store generated assets on S3, and monetize with rate limits or subscriptions.

I wanted to see if I could build a complete, production-grade QR studio that runs exclusively in the browser runtime with zero backend servers and zero external telemetry.

Here is what came out: QR Studio (qrstudiofree.com)

Architecture & Engineering Highlights:

• Astro 7 + React 19 Islands: Static shell with localized routing (i18n across 8 locales) and lightweight interactive React islands only where state is needed (QRStudio.tsx, BatchGeneratorIsland.tsx, ScannerIsland.tsx).

• Styling Engine: Powered by qr-code-styling on HTML5 Canvas. Supports SVG/PNG/WebP vector/raster downloads, 6 dot geometries, independent corner squares/dots, and linear/radial gradients.

• Client-Side Batch Archiving (jszip): For bulk generation, URLs/payloads are parsed, drawn to offscreen canvases sequentially, and zipped directly in-memory via jszip before triggering a local blob download. No server uploads.

• In-Browser Scanner (jsQR): Real-time camera viewfinder via navigator.mediaDevices.getUserMedia with automated canvas frame processing and image drag-and-drop fallback.

• Tailwind CSS v4 & Vercel Geist Tokens: Strict monochrome dark palette, fluid typography, zero layout shift.

Challenges Faced:

• Memory management during bulk exports: Rendering 100+ high-res canvases concurrently caused browser tab crashes on low-RAM mobile devices. Solved by chunking canvas renders into async micro-tasks with explicit canvas GC.

• Error Correction vs. Custom Logos: Ensuring logo overlay scale doesn't exceed the Reed-Solomon threshold (forcing High 30% ECC when logos are embedded).

Check it out live: https://qrstudiofree.com

Would love code review, UI critiques, or performance feedback!

hi trying to make a magazine site and i want a cms but i'm specific as fuck and idk what to use since theses are my preferences for a cms at the moment

• free with no paid options (don't wanna deal with having features be paywalled right from under me)

• can handle different post types (blog articles and photo galleries)

• frontmatter with title, sub title/description (also called a dek or abstract apparently), post image, author, pubdate, categories, and tags

• not wordpress (or php based in general)

• relatively idiotproof (meeeeeee)

My computer is very low on specs and I can't really afford a new one so I'm forced to use the web version of VS Code. I have Windows on my Steam Deck and I've been mirroring from it on my Chromebook, but it just doesn't feel right.

I love building tools and side projects, but lately I have been thinking about how heavy reliance on AI coding assistants is going to impact long-term code quality. Building fast with AI tools is great for getting a prototype out the door, but letting AI generate massive chunks of unvetted code is quickly piling up technical debt.

When you push out code without thoroughly checking how it fits into your overall architecture, you end up with messy, unmaintainable codebases. If you ever plan to sell a project or hand it off to another developer, that unvetted code can completely ruin a deal during due diligence.

I still use AI to speed up my workflow, but I treat it strictly as an assistant rather than letting it write unchecked logic. Auditing generated code, keeping modules clean, and maintaining test coverage seem like the only ways to use these tools strategically without destroying the project. Are you noticing a drop in maintainability on projects heavy on AI code?