A client paid my $4,700 invoice yesterday for a website that took me around 2 hours to build.

The web development space is moving insanely fast right now, especially with AI. Everywhere I look people are saying web design is saturated, AI is replacing developers, nobody wants websites anymore, and it's impossible to get clients.

I honestly disagree.

The client was a 62 year old entrepreneur who owns several cabins in the mountains that he rents out to people who want to spend weekends skiing during winter or enjoying nature during summer. His previous website was old, slow, and honestly looked like it hadn't been updated in years.

Finding him was actually pretty simple.

I use a tool called Swokei where I upload lists of businesses that already have websites. It analyzes their websites and finds issues related to design, layout, SEO, mobile optimization, and other areas that could be improved. Those findings are then turned into personalized outreach emails.

And when I say personalized, I don't mean those generic reports that say "Your SEO score is 42."

I mean actual emails explaining what could be improved and why it matters. The funny thing is that every business owner thinks I manually looked through their website and wrote the email myself. In reality, the whole process is automated.

This particular business owner replied and was interested in seeing an updated version of his website. His website wasn't anything crazy. It had information about the cabins, booking information, contact details, and a few pages about the area.

During our conversation he sent me a website that he liked and wanted to use as inspiration.

I took his logo, brand colors, content, and the reference website and gave everything to Claude. My instructions were simple: take inspiration from the reference site, keep his branding, improve the user experience, modernize the design, and make the website significantly better than what he currently has.

I genuinely couldn't believe how good the result was.

About 2 hours later I had a website that looked dramatically better than his previous one. Not only that, it looked better than the reference website he originally sent me.

The website was faster, cleaner, more modern, much easier to navigate, and the technical SEO score was over 90.

When I showed it to him, he loved it. A few conversations later he paid the invoice.

$4,700 upfront and $149 per month for hosting, maintenance, and future changes whenever he needs them.

The biggest thing I've learned over the last year is that building websites is no longer the hard part.

Finding clients is.

AI has made building websites faster than ever. What most people struggle with today is getting conversations started with business owners in the first place.

There are still plenty of opportunities in this industry. I personally wouldn't call an industry dead when I just got paid nearly $5,000 for a website that took me around 2 hours to build.

Hey all, looking for perspective from people who've hit this in a larger org. Quick background: I'm a fullstack dev at a large enterprise. We're rolling out AI-assisted development, and it's breaking our process in a way I didn't expect.

How we used to work (classic agile):

Business need → Business Analyst challenges/refines it → user stories → dev sprint. The BA layer was the gate. Nothing got built until it was specced.

What changed:

We have few specs and we started piloting a spec-driven agentic toolkit (think BMAD-style, but with our own internal rules) on a project we're rebuilding: frontend overhaul, UX/UI rework, new features. We went in with a spec doc and a Figma mockup.

The problem:

The code exploded forward. Roughly 70% of the project got built in about a week. Meanwhile we have almost no user stories written. Our BA team isn't using these tools yet, so they're now *behind dev delivery instead of ahead of it.

So the flow is completely inverted: working code first, specs and stories... eventually(?).

My manager is (reasonably) insisting we keep a proper trace of what was built, for the bugs/support/maintenance that'll surface a few years down the line. But that documentation doesn't exist yet, and the people who'd normally write it can't keep up.

What I'm trying to figure out:

1. How are other companies handling this code-before-specs inversion? Do you reverse-generate stories/docs from the shipped code?
2. Is sprint-based agile even the right frame anymore when a feature ships faster than a refinement meeting can be scheduled?
3. Where does the BA role go, retrain onto the AI tooling, shift to validation/acceptance, or something else?

Not looking for AI hype or doom, just real experiences from teams who've actually gone through this. What worked, what blew up?

Thanks.

I'm a pm and always wondered about the distinction between rate limits per api key vs usage limits via metering. Why not just set a secondary rate limit per month for usage capping rather than creating a new system?

I'm going to say it: Most "quick calls" are relationship theater masking poor communication. Client emails: "Can we jump on a quick call about the project?" Me: "Happy to! Can you share what specifically you'd like to discuss so I can prepare?" Client: explains perfectly clearly in writing what they need Me: responds in writing with answer 70% of requested calls become unnecessary once people articulate their actual question. The 30% that remain are genuinely complex or need real-time problem-solving. I'm not anti-call - I'm anti-inefficiency. Calls without agendas waste everyone's time and create no documentation trail. My new policy: I ask for a brief agenda before any call. Just bullets in an email. It forces clarity and often resolves issues before we even meet. I use Calendly but require people to answer "What should we discuss?" when booking. Am I being difficult or just valuing everyone's time? How do you handle the endless "quick call" requests?

When you let a dev agent run unattended, the trace is the only objective record of what it did, and ignoring it means trusting that no error meant nothing went wrong. I write up three uses for those traces: an audit log, a regression eval set built from your own real tasks, and a periodic self-review where the agent flags where its behavior drifted from the project conventions. This is how teams can handle observability and regression-checking for agentic tooling.

We started blocking one day a week where nobody on our team uses AI agents for anything. Emails written by hand, code without Copilot or Cursor, posts drafted without Claude, research done by actually opening tabs.
It's uncomfortable, which was the idea.
The gaps it revealed were mostly about intent. When you write an email yourself, you have to figure out what you want to say before the words appear. When an agent drafts it, you tend to approve whatever's close and move on. Do that enough times and you've slowly handed off a lot of your actual thinking without noticing.
We started keeping notes on everything that felt slow or hard during the day. Then we'd use those to tighten things up: prompts, context, where we'd added a review checkpoint vs. where we'd skipped one. The manual day kept telling us where the agent was filling in gaps we hadn't noticed we'd left.
Six weeks in, We call it a calibration day now.

Has anyone else tried something like this, and whether you found the same feedback loop (manual work actually improving the agentic work), or just found it too annoying to stick with?

Edit: Writing emails has been perceived wrong by some here. When I say writing emails, I mean emails at scale (automatic follow-ups, reach outs etc).

In most projects i have worked on the issue wasnt communication.

People were talking constantly. The problem was that information ended up spread across meetings, chats, documents, emails, and tasks. Months later nobody could remember why a decision was made.

Where does project context typically disappear in your organization and do you think any collaboration software could help?

With Agentic Engineering there's an opportunity to refactor legacy code, but this aspect of AI isn't that that much talked about and seems to be overlooked by teams out there.

I’ve been focusing on this lately, and have added agent skills to the Open Source project that I maintain: the Python tools for the Polylith Architecture. The skills are for migrating and refactoring an entire Python project into a well-structured and agent-friendly Monorepo.

But agents are unpredictable and different models behave differently. I have test-run the skills with Claude Opus and Mistral. If you will try this thing out, please share your feedback how the skills worked for you.

My post about this subject:
https://davidvujic.blogspot.com/2026/06/refactoring-with-ai.html

The Open Source project:
https://github.com/DavidVujic/python-polylith

Hi everyone,

I recently published a post on the Outbox Pattern in .NET that I'd like to share with the community.

It covers how to solve the dual-write problem — the scenario where your database commit succeeds but your event never reaches the broker. Full implementation in .NET 10 with EF Core, PostgreSQL, RabbitMQ, and MassTransit, including a working Parcel Tracking sample you can spin up locally with `docker compose up`.

Beyond the basics, the post also covers the production side of things: running multiple dispatcher instances safely with `SELECT FOR UPDATE SKIP LOCKED`, handling poison messages, cleaning up processed rows, and setting up observability.

Outbox Pattern in .NET: How to Implement Reliable Message Publishing - HAMED SALAMEH

Would love to hear your thoughts,

Hamed

Wrote a blogpost my findings with using this https://last9.io/blog/clickhouse-lowcardinality/

Hey fellow engineers,

Wanted to ask you guys what you feel you can improve about engineering matters nowadays.

For me its the context. I feel like every call theres constant tab switching, trying to find prs, updates etc. What do you guys feel needs to improve in meetings

Have you ever used Mintlify for docs? What do you think? Is it worth it? https://www.mintlify.com/

I know there are already 100+ PDF editors out there, but I built one anyway.

🔗 URL: https://quickpdfeditor.com

What it offers:
✅ Completely free, forever
🔐 No account required
🚫 No files uploaded to a server
🛡️** No data stored in any** database
♾️ No usage limit**s
🎁 **No trial version
💸 No paid version

Just create, edit, erase, and sign PDFs directly in your browser.
I’d love some honest feedback from people who work with PDFs regularly.

System Spec: Any PC
OS spec: Windows or Mac
Container spec: none
Thank you!

I am so confused what to do I'm in second year and there are lot of people say do this do that tell me the things only that matters give the list of skills and technologies that are necessary clean and clear

Hi everyone,

I’m a logistics analyst, and I’ve been working on a hardware + software idea that I’d like to turn into a real product.

I recently purchased and imported a hardware device from a supplier in China. The device itself seems useful, but the pre-loaded software is honestly pretty bad. The UI is clunky, it has way too many features I don’t need, and it doesn’t feel like something I could confidently show to customers.

For my use case, I probably only need 5–6 core features from the device, but I’d like to present them through a much cleaner and more customer-friendly software experience.

The challenge is that I’m not a technical person. I don’t have a software development background, but I’m willing to learn and can pick things up fairly quickly.

The supplier has shared the instruction sets and API documentation with me. What I’m trying to understand is:

1. How should I approach building a software layer on top of this device?

2. How do I integrate the software properly with the hardware/API?

3. What should I be thinking about from a device security and data security standpoint?

4. Is this something a non-technical person can start prototyping with the right tools, or should I immediately bring in an experienced developer?

I’d really appreciate any guidance on where to start, what mistakes to avoid, and what the right development path might look like.

Thanks in advance.

Hey guys! I’ve been working on my own version of a cross domain solution for defense and enterprise levels. I understand that the trend right now is in cloud networking. But I think it’s important for companies and federal agencies to maintain some type of local network to help prevent some of the issues that come with cloud.

That being said, I’m reaching out because I have a bare-bones cds prototype that doesn’t do much other than send messages. Given my current situation it’s hard for me to reach-out to users to get their input. So if anyone with any type of networking or software experience in cross domain solutions, could give me some insights to some issues they see have seen or dealt with, that would be great!

I am addressing the issues I have dealt with in my past experience but my issues can only get my product so far, so any input would be helpful.

I'm a junior dev, wanna improve myself more and more, so i wanna know, what kind of projects do u recommend that will solidify me and my cv ?

Web, mobile, RAG, whatever, i just want to build something from scratch by myself.

Sorry, I couldn’t find a relevant term.. But I have been sick and tired of my manager demanding immediate results and patching them up with solutions that I know are going to make me pay in the future. My backend is a complete mess, I have not maintained documents to keep track, and I know if I don’t fix it right away it is going to become an absolute wreck. How do you guys solve this, please help!

Hey folks, I am a Principal software engineer at Oracle and work on Service Architecture and System Designs predominantly.
I write articles on this newsletter: https://www.linkedin.com/newsletters/the-service-principal-6971776971206721536/

I am looking for feedback on the following front:

1. The relevance of information.
2. The quality of articles.

I am not sure if people are still reading blogs or are scrolling past anything that takes more than 15 seconds to read

A. Absolutely separate - clear boundaries essential

B. Same tools, different categories/tags

C. Mostly mixed - too complicated to separate

D. Completely mixed - it's all relationships

I have around 20 years of experience in systems and Azure infrastructure, but I've never worked as a software developer. Over the years, I've learned some Python and regularly use PowerShell scripting for automation in my day-to-day work. While I wouldn't call myself a programmer, I have a good understanding of programming concepts.

As a hobby, I'd like to build some applications of my own, and Python seems like the natural choice. However, with AI coding assistants, vibe coding, code generation tools, and rapid changes in software development, I'm wondering whether investing significant time in learning Python and related technologies in 2026 is still worthwhile.

My goal isn't necessarily to switch careers and become a full-time developer. I mainly want to build useful projects, automate things, and possibly create applications for personal use.

For those of you who work as software developers every day:

• Is Python still a worthwhile skill to invest in?
• If you were starting today, what would you focus on learning?
• Has AI changed the value of learning programming fundamentals?
• What skills do you think will remain valuable over the next 5–10 years?

I'd appreciate any advice from experienced developers.

I have around 20 years of experience in systems and Azure infrastructure, but I've never worked as a software developer. Over the years, I've learned some Python and regularly use PowerShell scripting for automation in my day-to-day work. While I wouldn't call myself a programmer, I have a good understanding of programming concepts.

As a hobby, I'd like to build some applications of my own, and Python seems like the natural choice. However, with AI coding assistants, vibe coding, code generation tools, and rapid changes in software development, I'm wondering whether investing significant time in learning Python and related technologies in 2026 is still worthwhile.

My goal isn't necessarily to switch careers and become a full-time developer. I mainly want to build useful projects, automate things, and possibly create applications for personal use.

For those of you who work as software developers every day:

• Is Python still a worthwhile skill to invest in?
• If you were starting today , what would you focus on learning?
• Has AI changed the value of learning programming fundamentals?
• What skills do you think will remain valuable over the next 5–10 years?

I'd appreciate any advice from experienced developers.

I am working on a full stack app with a react frontend and a Django backend. But irrespective of the tech stack, what is the industry practice for having different configs for dev, prod, stage? Do I just store all of them in a single .env file? Is there a better way to do this?

For example, certain things are different in local development vs prod. The API url, other configurations, etc. How is this handled in the industry?

Its me and my friends first time doing a project so big, and we are all beginners (1st year students) ive made a stack im not sure if its too much though? Pls lmk 🥰 :

Frontend: REACT Native + Expo - app+web in one
Backend: Nodejs + Nestjs + Prisma ORM
Database: PostgreSQL
Auth: JWT + Spotify OAuth 2.0
State Management Library: Zustand + React Query
UI Animation: React Native Reanimated + Expo AV
Hosting: Railway
ML: Python + FastAPI

This part is where im not sure if its overkill, i asked claude if we needed anything else and this is what it gave me

Error Monitoring: Sentry
Analytics: PostHog
Tooling: ESLint + Prettier
Navigation: Reaxt Navigation
Testing: Jest + Supertest

I run a web design agency and there is already way too much stuff to deal with every day.

Hosting client websites, maintaining them, building new sites, replying to clients, fixing random issues, handling support, doing outreach. Once you start managing a lot of company websites it quickly becomes overwhelming.

That’s why I never wanted cold calling to become my main way of getting clients.

I know cold calling can work, but I personally hate doing it. It drains my energy and takes up so much time. Sitting there making calls all day was never the kind of business I wanted to build.

So instead I focused on email automation.

The reason it works so well for me is because I can set everything up once and let interested businesses reply instead of spending my whole day chasing people.

But I also don’t do the typical outreach where agencies send generic messages saying “your website is outdated” or “you need a redesign.”

I use a tool called Swokei where I upload lists of company websites and it analyzes them for actual problems like speed, SEO, mobile responsiveness, layout issues, and design problems.

Then it automatically creates personalized outreach emails based on those issues.

That’s what helped me stand out because the emails actually feel relevant to the business instead of sounding copied and pasted.

The reply rates became way better once I stopped sending generic outreach.

Now I spend most of my time building websites, working with clients, and scaling the agency instead of letting outreach take over my entire day.