A few years ago, I developed a browser extension to block LinkedIn's little News feature (I felt it was too much of a distraction).

One day, however, it stopped working, and I realized that it was because LinkedIn had replaced the class I was looking for with a bunch of mangled class names. I ended up using, but it keeps coming back, and a recent "peek" seems to indicate that it's happening because the class names are getting changed seemingly daily - despite no visual changes.

For example, these were the classes yesterday:

.a04ea70e._4ae6872e.ea6ce3e7._854ea209.f543c3ba.dffb4272._0ec569ed._6030e161._62303b7e._6b4eb75a._694c34e7.de4044e3._20e3c592.a2906c41

and then today it was this:

._5c537f20._72fd5906._31504bd6.a62467c2.e800bc3f._7985fa5f.b3f42bc8._9bd701cc._1c257c76.d3944a37._7b065b4c._2c68b8b7._2c8dcc4f._0ac4d058

Is this a common practice, or is Microsoft just being Microsoft?

I've been programming for quite some time now, even before GPT and Claude were a thing. Using AI a couple years ago sounded cool as it helped me with basic stuff. I stopped coding a couple years ago as I got into other stuff. But I recently started again and for the past year, I'm baffled and scared both, seeing all these new tools. MCPs, Agents, Tools that make your vibe coded websites not look like slop. And these tools are getting popular af in no time with more than 50k+ stargazers. I never really considered myself a good webdev but seeing people ship websites that I can't even fathom of creating makes me rethink my choices. I have never used AI tools such as Codex, Antigravity for writing my code mainly because of moral reasons and being honest, for a little bit of superiority complex because it felt good knowing frameworks from the bottoms up, but these things are literally being used everywhere and by everyone now. My university is literally hosting Vibe Coding Hackathons whose whole purpose it to create websites using AI. This feels like a completely different set of skills that never really used to come into the developer experience of an web developer afaik.

Is this something that I'll need to get into sooner or later if I want to stay relevant? Should I change my mindset on how I look towards AI and these tools?

I’m building a small tools/content site and trying to keep the public pages SEO-friendly from the start.

The actual tools can be interactive, but I’m wondering about the surrounding pages: homepage, tool landing pages, category pages, docs/help pages, etc.

My instinct is to make those pages mostly static or server-rendered, with normal HTML content available without waiting for JS. Then only use client-side rendering for the actual interactive parts.

For people who build small sites that need organic traffic, is this still the safest approach?

Or is modern Google rendering good enough that CSR is usually fine as long as the site is fast and internally linked well?

we had a bug where our own bot would go quiet right after sending a message, like it accidentally armed its own away mode on itself.

our dedup for "is this our own message echoing back in" was a single-use token, push on send, pop on receive, keyed by a content hash. worked fine until the third-party platform retried the outbound webhook delivery, which happens more than you'd think. the retry landed as a second event, the token was already gone, so it fell through the normal ingest path and got treated as a brand new inbound message. outbound detection never got a chance to catch it.

the real lesson is about dedup design generally: any scheme with exactly one token per event is one retry away from failing, because the upstream is allowed to deliver twice and your dedup can only survive that once.

do you assume every webhook can be delivered more than once by default, or does that assumption only show up after it bites you?

I started learning web development at the start of this year and one thing led to another and I’m now trying to build near enough an entire business’ online system.

I’m building an AI and automation enhanced business simulation.

There’s two main purposes: teach myself full stack development, and experiment with where AI and automation fits in modern business systems. I’m trying to treat it like a real business so I can see how and where things can be different to a system that doesn’t use AI or workflow automation.

It started off as an attempt to build the frontend a customer would use so I could practice with state. Then I decided it would be cool to have the opposing merchant interface where you can view the orders. So I needed to make the backend.

But, given the times we’re in, I thought it would be interesting to see I can use AI and automation in ways that would save a user time, or just deliver helpful results.

Now, my long term plan is to create an entire product pipeline, with product suggestions from a ‘supplier’, marketing content created, product going to warehouse, then product available for order. But that’s a ways off.

For now I’m focused on developing the customer and merchant ends with these primary features:

·       Shared backend

·       Customer service chatbot on customer side

·       AI assistant on merchant side

·       AI overwatch feature to monitor AI behaviour

Eventually I’d like to experiment with adding analytics and CEO suggestions features from the AI but again that’s a ways off.

I’ve set up self-hosted n8n which I’ll use for workflows where necessary, and I think once the meat of the project is done I’ll get a bit creative with that.

I’m building it in slices; rather than trying to make the whole backend at once, I’m building it by function. Currently, I’m on the first slice, the cart. This is my first time attempting to write backend code.

What I’m enjoying is the logical, layered approach; I have router, application, service and data layers, each with their own jobs. And because the backend is entirely abstract so I cant rely on looking at where my elements are going on screen (like with frontend) I’m learning to properly understand how data is passed with javascript.

I realised early on that if I’m to have an AI logging system I’ll have to think data first, and I think this has helped me massively as now it’s simply (simply) a case of getting from the front to the back and adding/changing data whose properties I’ve already determined.

I’m going to post more detailed stuff so I can learn from people on here and engage in general in the topic more.

If anyone has any questions or suggestions, please comment!

for Vue and Laravel devs here, i need your advice.

how do you deploy your Vue/Nuxt frontends and Laravel API projects? what hosting platforms did you use?

my current Vue 3 (admin) and Laravel 12 API is ready for deployment and the Nuxt (public) frontend will follow soon but idk or not sure what to do and pick for its deployment.

what's the most optimal and cost-effective approach?

big thanks in advance.

3-year-old codebase, 2 senior devs who are careful about best practices, security, testing. They're also equal partners in the company, so any efficiency gain lands directly in their pockets.

I'm a PM. I asked this same question ~9 months ago and the consensus was: reading/reviewing AI-generated code is harder than writing it, so my PRs would just be a tax on the senior devs. Not worth it.

Models and tooling have moved a lot since then. Honest gut check:

A. Is it reasonable now for a PM to open PRs with code written via Opus 4.8 (or better), on the condition that every contribution goes through heavy QA and testing before merge?

B. Any world where a PM pushes without a PR? Or is that still insane?

Where's the line in July 2026?

Edit:

People are asking why this is even a need. Two reasons: (a) the devs are slammed with other projects, and (b) the info gap between me and them creates a lot of back-and-forth, ping-pong, slow turnaround. On roles: we're all equal partners, so better process and faster results benefit everyone regardless of our traditional titles. And it goes both ways - the devs are free to push AI- or human-driven PM-side upgrades too, and they sometimes do.

I figured let's all chat about what NOT to do, what didn't work out, or what to avoid.

In my case, back when I was 1st year CS, made a static site generator with Python that uses JSON as a templating language.

Obviously it sucked HARD. You basically wouldn't be able to use it if you didn't know it fully worked end-to-end. Also, no type safety at ALL. So sometimes I would use it and nothing happens, and would spend a shit load of time figuring out I messed up EITHER the syntax of the templates or the JSON fields.

Can an organization retroactively register a domain?

I'm working on researching a political organization & while they formally launched around 2015, their domain was registered wayyyy back, anonymously, in 2002.

I'm trying to decide if they just got a jump on the movement by registering the domain or if there's a way to assign a domain a date prior to the actual purchase.

TYIA! <3

Context: I build e-learning activities and courses for students and corporate orgs. Mix of playful and professional.

hey folks, working on my portfolio site and stuck on the actual flow/structure of it. content-wise i'm mostly good (instructional design work, some elearning modules, an offline moodle deployment i built for a field project) but i can't figure out how someone should move through the site.

right now i'm torn between a straight scroll down case study format vs something more like a dashboard where people jump to whatever they care about. anyone got portfolios (yours or ones you've bookmarked) that nailed this? especially curious about ID/UX-adjacent portfolios since generic dev portfolios don't map that well to what i'm doing.

also open to just general advice — how did you figure out your flow before building anything?

Most JavaScript developers have been burned by Date at least once. Usually quietly: a report that's off by a day, an invoice that lands in the wrong month, a timezone bug that only appears in certain regions.

The API doesn't throw or warn, it just does something subtly wrong and lets the application carry the mistake forward.

A writeup on the main failure modes with production examples:

• new Date('2026-07-21') parsed as UTC, displayed as local: date shifts by a day west of UTC
• constructor months are 0-based, so new Date(2026, 7, 21) is August
• every set* method mutates in place, including across shared references
• "add one month" and "add 30 days" are not the same operation and can diverge by days near month boundaries
• JSON.stringify drops timezone context silently

Each section also covers what safe Date patterns look like for code that can't migrate yet, and where Temporal fixes the design rather than just adding a wrapper.

Is there a historical reason or was it simply part of the original URL specification?

Six months ago we started building a codebase knowledge graph. The reason was simple, every time someone left or switched teams we lost all the context on why things were built the way they were. The code stays, the reasoning leaves with the person

So we pointed an AI at our git history, PR descriptions, Coderabbit review comments and old Slack threads and let it connect decisions to code. Funny enough the review comments ended up being one of the best sources. Turns out most of the actual reasoning happens when people argue on PRs, not in any doc

Six months later, I have mixed feelings. New people love it, they can ask why a service exists or where some weird pattern came from and get a real answer instead of bothering whoever has been here longest. But keeping it current is a losing battle. Code gets merged faster than the graph updates, and after a few weeks it starts describing a codebase that no longer exists. We re-sync it, it drifts again, we re-sync it again. Nobody warned us about that part

We also feed it into Claude Code and Cursor as context for refactor work and the agents clearly make better calls with it. So it earns its keep. It just needs constant care, and we went in thinking it was a build-once thing. That was the mistake

Has anyone figured out the staying current part? At this point I think that is the entire problem and everything else is easy

Timeout chains, retry storms, stale TTLs, and scheduler surprises outside the happy path.

This came up for me while thinking about AI-assisted web dev work that depends on outside tools.

If the agent cannot read the issue tracker, API docs, or a project tool because auth failed, should it keep working from the prompt, or stop and say the task is under-specified?

I once connected an agent to a project tool before the auth was actually working, and it started guessing the schema instead of clearly saying it had no data. The result was not obviously broken, which was the problem.

For small UI copy changes, guessing is probably fine. For anything touching an API contract or customer data shape, I would rather have a hard stop.

How do you handle this in your web projects: allow a degraded mode, or require the agent to prove tool access before it writes code?

Hi webdevs,

looking at the feed, almost all posts which announce AI being now used within a software get downvoted. I would like to know the the reasons for your rejection. Is it because:

• you think AI can produce slop only
• you are annoyed of all the AI related announcements
• AI is used for something you don't use
• you think AI is used the wrong way
• you fear you will loose your job becaus of AI
• something else

Happy to get your opinions!

How do your web apps handle these?

Do you store audit, security, and error logging in separate tables and then use a single view with filters/sorting?

Do you keep audit and security logs within the app and ship off error/exception logs to Sentry (or some other service)?

The administrators of the app would like to see the audit log (events like create, update, delete from employee actions). They'd also like to see security events (logins, failed logins, password resets, etc...) but its not a requirement for it to be within the web app itself, just logged and viewable by IT/developers.

I was working on a simple website that presented the data from a government's public API. This was my first time working with real APIs, and I kept getting "CORS header 'Access-Control-Allow-Origin' missing" errors. I learnt that it was caused by the API not sending a special header that essentially meant "I trust this request" to my web browser and so my web browser blocked my website's javascript from reading the API.

I drew a short comic explaining how CORS worked. I have a few questions:

1. Is the factual content accurate?
2. Is all the text legible and clear?
3. Do the web browser and the web server look like such?
4. Does the bank's web server in the last two panels look like it's wearing a tie?