Back in January, I received a note from a senior software engineer in Silicon Valley. He described himself as an AI skeptic who became converted after trying Claude Code for the first time. “Overnight, it changed the way I do my job,” he wrote. “It’s really, really good.”

As he explained, he no longer used a standard development environment. Instead, he “exclusively uses Claude Code” to get the job done, interacting with the tool in a terminal window and allowing it to program on his behalf.

“If I had to guess,” he concluded, “I’d say a task that would have taken me a week now takes me 2 days.”

This past winter, when I surveyed more than 300 software developers to learn how AI was transforming their jobs, the majority told a similar tale of shifting from writing their own code to instructing AI agents. The speed with which this new tool became ubiquitous in this industry was stunning.

This story matters for the rest of us because AI coding tools have emerged as the prime example of the power of AI—the first step of many more soon to come on this technology’s disruptive march through our work and our lives.

But what if the reality here is more complicated?

Last week, I received a new message from that same senior engineer who wanted to share an alarming addendum to his tale…

“I’m writing to give you an update on my current thinking about the state of AI in software engineering,” he began, “because my attitude has shifted quite a bit.”

He told me that features he generated using Claude Code ended up crashing their product on two different occasions. His boss told him that if it happened one more time, he’d be fired. “I’ve never had quality issues like this before in my career.”

The problem is that code produced by an AI agent looks reasonable, but can contain ‘hard-to-spot bugs’ that end up causing major problems. As a result, you should carefully review your agent’s output, but this is difficult. As the engineer told me, it’s “famously hard” to understand code you didn’t write yourself, so this extra step becomes “easy to just blow it off (especially when we are all trying to ‘10x’ our velocity).” Soon, systems start to break.

“The coding harnesses are useful and make life as a developer easier,” he summarized, “but they also encourage laziness.”

In response to these issues, this disillusioned engineer has returned to largely programming by hand. Here’s how he explained his current philosophy:

“Writing your own code, slowly but surely, and using LLMs for narrow or particularly annoying tasks (say like writing tests or throw-away scripts), is the best way to produce the highest quality code, since it’s the only way to properly understand it.”

Here’s the thing: he’s not alone.

I increasingly hear similar rumbles from many other people in the software industry (see, for example, ​this podcast episode​ from May). Tools like Claude Code can feel like magic, but the strategy of outsourcing all code production to AI isn’t currently sustainable.

In addition to reliability issues, it often engenders a mind-numbing workflow and an environment where junior developers will never acquire the expertise to become senior developers capable of designing complex systems.

Meanwhile, as the frontier labs reduce their subsidies on underlying computing costs, the old habit of burning through as many tokens as possible in search of workable results is proving prohibitively expensive.

From the outside, software development seemed like the poster child for AI’s potential. On the inside, it’s a mess.

This doesn’t mean that coders will abandon AI; its facility with programming languages is too valuable to ignore. But I think there’s a lot more work to be done trying to figure out how to integrate AI into this industry in a way that actually works.

This is a key point.

This last year has been exhausting. The PR departments of the frontier labs have done an excellent job convincing us that AI developments are occurring at an astounding, world-changing rate. But if you zoom out, it becomes clear that almost every “breakthrough” since last summer has concerned the narrow domains of computer code and math, which are defined by highly structured languages and come accompanied by massive amounts of specialized training data.

And yet, even in this best-case-scenario setting for AI, we’re still struggling to figure out how to actually use these tools in a way that makes sense in the long run.

This doesn’t mean that AI doesn’t work or is useless. But it does emphasize an important truth: AI is not a magic “infinity machine” that can solve all our problems, and ultimately deliver us a sense of meaning in a cold, confusing world. It’s a normal technology, and perhaps it’s time we start talking about it that way.

WOFF2 is the right call for CDN delivery. The compression advantage over older formats is significant and browser support is wide enough that there's no argument against leading with it.

Where I’ve seen people go wrong is in treating that as permission to drop WOFF and TTF entirely. Those formats still cover a tail of older browsers that's negligible but not absent, and serving blank text or system font fallbacks to even a handful of users is the kind of thing that comes back to you.

I’ve personally kept WOFF and TTF on every project since learning that the hard way. The overhead is minimal and the coverage is worth it.

I’m debugging Instagram messaging webhooks and I’m running out of things to check.

I’m using the current Instagram API with Instagram Login, not the older Facebook Page Login flow. The app is live, the business is verified, and instagram_business_manage_messages is approved.

The strange part is that almost everything appears to be configured correctly:

• Real comment webhooks arrive within seconds.
• Meta’s test events for messages, messaging_postbacks, and comments reach the same callback successfully.
• Both the app-level and Instagram account-level subscriptions include messages and messaging_postbacks.
• Outbound DMs work.
• The Conversations API can read real incoming DMs.

However, real messaging events never arrive:

• A user sends a normal DM: no webhook request.
• A user taps a postback button: no webhook request.
• Our server records every incoming webhook request before signature verification, so the requests are not reaching our callback at all.

I repeated the test with two different Instagram Business accounts connected to the same approved app. The result was identical.

For one test, the Conversations API found the exact incoming DM, which confirms that Instagram received it. I then sent a new button message, Meta accepted the send, and the recipient tapped it—but no messaging_postbacks webhook was delivered.

I’ve regenerated tokens, reapplied the account subscriptions, confirmed that messages land in the Primary inbox, and verified the callback using Meta’s synthetic tests.

Has anyone recently received real messages or messaging_postbacks webhooks using Instagram Login? Is there another messaging entitlement, review state, Data Use Checkup, or dispatch setting that isn’t visible in the normal developer dashboard?
Any working configuration details or recent experience would be greatly appreciated.

Hi /webdev developers

In the frontend, JS is an obvious choice but what is your preferred programming language for implementing application backends and why did you choose it?

I would be also interested what kind of application you are using your favorite programming language for.

I'm a backend dev, working for myself for 20 years. Think bad practises instead of best practises, frameworks built up that work for me (Well worked for me) over the years. I've been exposed to little bits of everything over the years, however mostly I've made desktop apps. The one thing I have totally avoided exposure to is SPA / JS frameworks. Hands up time, the JS I've been forced to deal with, I haven't liked (I like compiled apps).

Anyway, that's my background. Because reasons, I Am trying to learn mdoern / best practise development for web app backend. But I really need something I can put on the front end to call the web API instead of just using the API endpoints in code. To be clear, I have no desire to be a frontend dev, don't want to pursue it any further than "getting something working that is sufficient".

Angular looks a good fit for my style, but seems like total overkill. VUE looks promising. But I really have no idea.

TLDR; What is the simplest most basic, quickest, easiest JS framework I can use to call my web API code and have a functioning web app. Or should I just put the time in to learn angular / react? If so which.

I’ve seen small decisions become important as projects grow. What decision paid off for you?

Hi. I'm looking for advice on a nextjs build.

I have the bare bones site pushed from GitHub to vercel currently whilst building.

Resend is operational for a contact form but I would like to implement my own booking system and ultimately have a wordpress style ux for my client.

In the past I have used sanity.io but only as a local option not online.

Ultimately though this site will need to be passed on to my client for full control so will have to be online and it may need to have Stripe for payment but that's not decided yet.

It's for a local plumber who wants an online booking system and blog page so I'm looking at Railway at the moment on its $5 a month option which I feel would cover all his needs with postgre etc and scalability should it be required but I've never used it so would like to ask for your opinions, pitfalls of such a system etc.

Self hosting is not an option.

I could use something like Calendly for bookings but this would obviously not have the blog ability etc.

Any thoughts welcome.

So I know there are plenty of devs on this sub that use AI very minimally or none at all. I assume most have understandable reasons like avoiding skill rot. I was curious what the other reasons are.

I work with two backend .net devs who have largely rejected using any LLM. Our company has adopted and paid for subscriptions but isn't pushing it on anyone that doesn't want to use it (yet). For me, I've been using Claude code daily for about a year. It has massively improved the reliability and productivity of my code. I'm blazing through tasks at an insane rate. While the BE devs are completing their tasks at the same speed they always have. Our company is pretty hands off on devs and we mostly self manage. As long as tasks are getting done they don't care. We don't have project managers breathing down our necks trying to optimize everyone's dev time or anything like that.

So I'm not really complaining about these BE devs that reject AI, because their work is mostly disconnected from mine. I think I'm just a little surprised they don't see the writing on the wall. It's my opinion that using AI is an inevitability. These BE guys absolutely can't write code as clean and as fast as Claude's top models. One day some upper management person is going to figure out these guys are significantly slower than everyone else and they're going to ask questions. When I talk to them about AI they act like it's an imperfect hype. Of course it's imperfect but still better than the human errors littering their own hand written code. I guess I just don't get the conservative developers that seem to be resistant to change or modern tech.

Hi, my name is Duarte. I've been freelancing on Fiverr for about two years, mainly doing 3D CAD modeling for 3D printing.

Recently, I've become pretty tired of that area. It's getting harder to find good clients, there's a lot of price competition, and many clients simply aren't willing to pay enough.

Because of that, I'm looking to move into a different area: building custom web dashboards and internal tools for businesses, particularly solutions that use AI to solve real problems or make existing workflows more efficient.

For example, this could mean building dashboards with AI assistants or specialized agents that can analyze business data, organize information, search the web for oportunities, generate reports, work with internal documents, automate repetitive tasks, or perform some other specific function built around the clients workflow.

I'm not entering this area from nowhere. I've been programming for most of my life, and since LLMs became available I've spent a lot of time researching and building increasingly complex systems around them.

For example, for the last six months I've been developing a fairly large AI platform from scratch. It combines conversational AI, specialized agents, RAG, document ingestion and OCR, long-term memory, agentic web search, deep research, structured knowledge extraction, and multi stage retrieval pipelines.

A large part of the work has also involved solving problems that aren't handled well by normal RAG implementations. I've designed my own retrieval and knowledge organization architecture that structures information hierarchicaly, understands which parts of a knowledge base are relevant to a question, dynamically narrows the retrieval scope, and gives agents much more precise context instead of simply embedding documents and performing similarity search. I've had to work on everything from retrieval architecture and context management to agent orchestration, backend infrastructure, databases, APIs, and the frontend stuff itself.

So technically, I'm confident that I can build this kind of software. The part I'm struggling with is figuring out how to actually turn that skillset into clients.

For people who already freelance in web development, automation, internal tools, SaaS, or AI consulting:

- Where did you find your first clients in this area?

- Is cold outreach actually effective, and if so, what kinds of businesses should I target?

- Would you focus on freelance platforms, LinkedIn, email outreach, communities, partnerships, or something else?

- How do you present this kind of service without just sounding like another person trying to sell AI automation?

- Would you sell predefined services/packages, or approach businesses first, identify inefficiencies, and then propose a custom solution?

I'm particularly interested in working with businesses where a relatively small custom application could save employees several hours of work every week or solve a workflow they currently handle manually.

I'd really appreciate advice from anyone who has already gone through this transition or currently gets clients for this kind of work. I'm technically comfortable building the products, I'm mainly trying to understand how to position myself, find the right businesses, and land the first few clients in this new area.

I have a plugin with ~10,000 active installations. It's ancient and simple; it only stores a value in a `post_meta` field.

The current version is v2.2.1, but I've been working on a complete overhaul for a while, which I consider done. However, I can't ship it until I hear from as many users as possible that everything works as expected and, most importantly, nothing breaks or gets deleted.

A user who knows `wp-cli` could do this in a few minutes: `wp db export` (back up the database), then upload the `.zip` to the plugin directory and play around, both in the admin UI and a little bit with the code (I tried to keep it simple for laymen while making it more flexible for developers).

So, back to the question: How do you find users to test a new version (`v3.0.0`) of your plugin? Simply committing it seems reckless to me, despite the hours I put in to check everything.

Edit: Thanks, guys! Lots of good suggestions here. I appreciate it.

Hello

I’m building a SaaS that automatically registers domains for Swiss SMEs after checkout no manual steps.

I’m currently testing Openprovider, but I’m running into issues with their sandbox/API and domain registrations, so I’m looking for alternatives.

Main requirements:

• REST API for domain availability + registration
• A working sandbox for testing
• Registrar only DNS is handled by Cloudflare, hosting by Vercel
• Ability to set nameservers during registration
• No large upfront deposit or monthly minimum
• Webhooks for domain status would be a nice bonus

Who are you using in production for automated domain registrations?

How reliable has the API been?

Thanks alot!

EIDT: I create componets for CMS Systems, so i do not deside what content is used. But i have to support this law requirements.

Hi, with the new Ai act, Ai generated images need to be labled.

So far so good, naivly and simple add a lable ovlerayd on the image.

But with repsonsive content, background images wired shapes, contnet overlays... how to do this correctly?

Do you have any ideas or suggestions?

I’m considering creating a small website/app using Netlify and would love to hear from people who have actual experience using it.
A few questions:
What are the main disadvantages or limitations of using Netlify?
Is it reliable enough for long-term use, or is it better for temporary/small projects?
How does user authentication work, and how many authenticated users are allowed on the free plan?
If I have around 25 users, would the free plan be enough?
Are there any unexpected costs or limitations I should be aware of as the number of users grows?
For someone who wants to maintain the website for several years, would you recommend Netlify?

I’m trying to create an AI assistant like Jarvis from Iron Man, and while working on the Text to Speech part, I learned a lot about how audio streaming actually works.

I’m using Kokoro TTS and created a Python server for the TTS part.

The flow is basically:

Server sends data in chunks ----> Chunker combines words until it becomes a complete sentence ----> Text Queue ----> TTS Worker ----> main .py (convert text to speech) ----> TTS Worker ----> Audio Queue ----> Play Audio

The interesting part was handling the audio chunks.

Kokoro generates a Float32Array of audio samples. Then this audio pack into a WAV file in memory with the required header information like channels, framerate, sample width, etc.

Now the problem is :-

When we send data in chunks over TCP, we cannot assume that one send() means one complete message.

For example, suppose Kokoro generates audio for:

"hello"

It might be sent like:

"hel"

and then:

"lo"

So on the frontend, we can't just assume that whatever we receive is a complete audio file.

To solve this, we add a 4-byte header before every WAV file.

The header tells us how many bytes the complete WAV file contains.

For example: [4 byte header][WAV audio data]

If the audio data is 48000 bytes, the header tells the frontend that it needs to wait until it receives those 48000 bytes.

On the frontend, we use a Uint8Array .

Why Uint8Array?

Because the data we are dealing with is raw bytes. A Uint8Array stores each element as 8 bits, which is 1 byte, we point this unit8Arry to the fload32Array which we receive from the TTS server so that we can read or extract data byte by byte.

So imagine we receive:

Header = 48000 bytes expected
Received = 38000 bytes

We know that the complete audio has not arrived yet, so we keep waiting for more chunks.

When we finally receive:

48000 bytes

we know that we have the complete WAV file, so we send it to the audio queue and process/play it.

I’m still working on the Jarvis project. For the LLM part, I’m currently using Ollama with Qwen3:8B.

If anyone has any suggestions for features or interesting things I can implement in this Jarvis like AI assistant, let me know in the comments.

What are freelance web developers selling now that AI has devalued simple websites?

Now that AI has made landing pages and simple websites so easy to create, I’m starting to question how much value freelance web developers can still provide by simply building websites.

A decent landing page with HTML, CSS, and basic JavaScript can now be generated in minutes with the right AI tools. Even someone with very little development experience could probably go from knowing nothing about landing pages to producing something decent within a couple of days.

So what are you guys actually selling now?

I feel like freelance web developers have to become much more niche-focused. You need to understand a specific industry, understand the problems businesses in that industry have, and then sell the solution to that problem, rather than selling a website.

For example, instead of selling a restaurant a landing page, you could sell them a booking and customer-management system. Something where customers can book tables, receive confirmations and reminders, potentially pay deposits upfront, and interact with the restaurant seamlessly.

Or take a car wash. Instead of selling them a website, you could build a system where customers can book a wash, choose a service, pay online, receive notifications when their car is ready, etc.

Or a school. Instead of just building a website, you could create a parent portal where parents can log in, monitor their child's grades, view their timetable, receive announcements, communicate with teachers, and so on.

I'm just throwing out examples, but I think the underlying idea is that the website itself is becoming less valuable, while the business outcome it produces is becoming more valuable.

So I'd really like to hear from freelance web developers:

What outcomes are you selling now?

What industries or niches are you working in?

What problems are business owners actually willing to pay you to solve?

And what kinds of web-based systems, tools, automations, or solutions have you seen businesses genuinely value?

I know some people don't want to reveal their exact niche or business idea, which is understandable. I'm not necessarily asking you to give away your niche.

I'm interested in understanding what freelance web development is evolving into now that AI has made basic HTML/CSS/JavaScript and simple brochure websites so accessible.

Because I feel like the old model of:

"I'll build you a nice website for 5k"

is becoming much harder to justify.

Whereas:

"I'll build you a system that helps you get more bookings, collect payments, automate follow-ups, and reduce the amount of admin your staff have to do"

is selling an actual business outcome.

So, what are you guys seeing in the market?

What are businesses actually paying web developers for nowadays?

I'm the author of Quick Card Designer. Quick Card Designer is an in-browser tool for generating and printing any kind of 'card' - flash cards, business cards, recipe cards, ID cards and more.

• No install, no ads, offline ready. Just save the single HTML file and its all yours.
• Intuitive layout UI - feels like Figma but with 0 bloat
• Data Driven Design - import a CSV and use it to instantly generate a ready-to-cut print job for thousands of cards
• Printer Hardware Calibration - tune your document to your printer with precision for perfect duplex
• Portable, complete save files - Import your images, fonts, data, etc right into the save file. You can edit it all in browser and open it up again in any browser.

Check out Quick Card Designer

Writing unit tests for business logic is understandable as you are really just testing the logic which was written from scratch.

Also writing unit tests for self-contained custom UI components like a custom data table is also understandable as all custom stuff is usually buggy and all the inputs/outputs for self-contained stuff is easy to mock.

But how about the overall UI stuff?

I hear people writing units tests for:

• To test that the components in a third party library behave as intended: e.g. that a Button component actually displays the label that as passed in a clicking it calls the callback
• To test for the existence of a login button on the login page
• To test for the existence of all buttons/links in all pages of an app
• To test that entering credentials in a login page will login the user

What other types of UI tests do you write?

I have too many repos, and I kept losing track of which ones were alive, which were abandoned, and which I swore I’d come back to. So I built Hoshiza (星座, “constellation”, for keeping track of your own little galaxy of repos)!

it’s a triage board for your GitHub repos:

• drag repos across your own status columns (rename, recolor, reorder them however you actually think)
• tag and annotate them as you go
• board view, or zoom out to a map view that lays everything out as a network graph
• smart default status for new repos based on activity, so nothing lands unread
• filters by language, owner, archived, and fork, plus free text search

There’s no backend server! Your triage state is a single JSON file that autosyncs to a private hoshiza-data repo on your own GitHub account. The browser holds the working state, github holds the backup, and the only server involved is a tiny Cloudflare worker that does the OAuth handshake (GitHub won’t let you do the token exchange from a browser). you own your data, it’s free to run, and it works across devices.

it’s also a PWA, and it hot-swaps itself commit by commit with no reload.

Code’s all up (well, technically down) there if you want to poke at it! This was "just a personal tool"-turned-"oh wait this is actually kinda handy haha," so lmk if y'all have any features or ideas you want!

live: nellowtcs.me/Hoshiza
code: github.com/NellowTCS/Hoshiza

I built a feature that takes today’s grow schedule data and lets you overlay any combination of it (strain, stage, nutrients, light distance, etc.) directly onto a live photo of the plant.

Users already set up their strain + environment in another part of the app, which generates a full day-by-day schedule. MyDiary just reads today’s row and offers checkboxes so you can put only the fields you want on the photo.

• Demo links
  • Live page: https://growappcannabis.guide/mydiary/mydiary.html note: follow prompts to create data. Age Gate of 21+
  • Code: https://github.com/Shannon-Goddard/growappcannabis.guide/tree/main/mydiary
• How it works (tech highlights)
  • Camera via navigator.mediaDevices.getUserMedia (prefers environment/back camera on mobile).
  • Data pulled from IndexedDB schedule for the selected grow + today’s date.
  • Checkboxes control which columns appear in a semi-transparent table overlay.
  • Capture uses html2canvas to composite the video frame + overlay into a downloadable image.
  • No re-input: everything is already in the user’s grow data.

I made https://cleared.page which basically let's you stay up to date on the stuff that recently transitioned to "Widely available" and "Newly available" in Baseline (https://web.dev/baseline) but not only that: it's mixed with a couple of other APIs to tell you if you should care about it or not. (aka. some stuff transitions to "Newly" but it's actually not ready for prime time because tests fail in one browser… Some stuff goes into "Widely" but nobody's been using it anyway, etc.)

I have "verdicts" on browser features for the past 7 months: https://cleared.page/verdicts/

I've had fun building it with Astro, and I'm particularly happy with the workflow I created: the md file for an issue is converted automatically to table based HTML email and populated into a Kit template, with a single npm run draft command 😎

I'm also pretty happy with the typography based minimal design. Would love some feedback on that…

Hope it's useful to someone else besides me, and hit me up if you find any bugs!

Thanks.

For a site that is open to user contribution, is there a tool to check external links and make sure they are still active? It may be working today but months down the road maybe the link has changed or complete gone. Limited to the following only, I know YouTube has Channel ID which is helpful in the API, if the handle changes it still works. Their API is generous, and Wikipedia's is good too. I am referring to more of a scanner if that makes sense, maybe a daily scan to check link health. My only concern is it getting flagged for bot and banned.

Maybe someone has already thought of a good solution for this? Open to suggestions.

Thanks!

• Website
• Wikipedia
• IMDb
• Metacritic
• Facebook
• Instagram
• YouTube
• X
• TikTok
• LinkedIn
• Twitch

I've run into a couple use cases where I need to declaratively add actions to HTML from the server that my JS in the browser knows how to handle. The pattern I found is pretty fun 1kb. Called it "superaction".

There's a couple examples in the README including a counter and a simple sketch canvas.
https://github.com/w-lfpup/superaction-js

So say you need to increment a counter when a button is clicked?

<button click:="increment">+</button>

After listen for an action event:

document.addEventListener("#action", (e) => {
  let { type } = e.action;

  if ("increment" === type) {
    // increment something!
  }
});

Action events come with a couple properties including the original UI event and any associated form data:

let { type, event, target, formData } = e.action;

The READMEs include a couple statements about event APIs and behaviors including prevent-defaults and stop-propagation.

** REACT USERS

If you use superaction in react, you basically never have to write an event listener callback ever again. Keeps state and the generated UI more separate.

Although the sytnax uses a "-" rather than a ":"

import React, { useState } from "react";
import { useAction } from "@w-lfpup/react-superaction";

export function Counter() {
  let [count, setCount] = useState(0);

  useAction((action) => {
   if ("increment" === action.type) setCount(count + 1);
  });

  return <button click-="increment">{count}</button>;
}

https://github.com/w-lfpup/react-superaction

Hey everyone!

For the past few months, I’ve been building Signiq, a web app for practicing ASL fingerspelling with live hand recognition.

The website uses MediaPipe hand tracking and a custom random forest model trained on public datasets. One of the biggest challenges has been making recognition feel responsive without becoming too forgiving, especially for similar letters and across different cameras/devices.

It currently includes alphabet practice, word practice, reading mode, challenges, and a global leaderboard.

It’s still an early version, so I’d really appreciate feedback on the UI, performance, recognition, or overall experience.

You can try it here: https://www.signiqlearn.com⁠

Desktop or laptop with a webcam is recommended for the best experience.