Tag: AI

Building Landing Pages with AI

~ Veselin ~ 8 Comments

We had a special month at Automattic that ended last Friday. For a full month, we could form groups of two people and work on whatever we liked, as long as we are in a pair.

I chose 4 projects and ended up working on 3 of them, discarding the 4th – couldn’t get to it. First was the new Writing Prompts, which was relatively low-tech (on the surface) but pretty cool. Seeing people respond to blogging prompts that were my idea is melting my soul.

The second project was around building a way to assemble good looking landing pages with AI quickly.

A landing page on WordPress.com is a page that tells a story, highlights a feature, or shows something so it’s discoverable. For example, a colleague runs a program that gives paid plans to students. Another wants to show how WordPress.com compares to a competitor. They write content, the content is then designed, and then the design is turned to an actual page by an engineer.

Landing pages

My team is sometimes responsible for the implementation of these. I didn’t like this type of front-end work and avoided it. A few months ago, we were in a situation in which the demand for new landing pages was high, and the resources for implementing them low, so I was “shoot, if I have to make these, let’s at least offload as much possible to AI”. The first round resulted into something like a vibe-coding flow, the benefit of which was that the work moved from the WordPress editor to Claude Code. But it was still too technical, and required a design (usually in the shape of a Figma document).

My colleague Jordan Hiller came up with the idea to give sense to Claude Code by providing it with a library of pre-designed, ready to use, empty sections that can be filled with text and images, depending on the needs. The technology behind it is Gutenberg Block Patterns. They’ve been around for awhile and can also be used from the editor or the wp cli. However, we expect the usage through a Claude skill to be the primary way to use this work because it doesn’t require expertise when making more advanced tweaks.

It’s an internal tool project. Something to make our lives easier, replace an annoying process with a faster one. The faster process lets you maintain the pages better, update more frequently, apply best practices sooner. Essentially, do more and stay on top of the change requests or avoid them altogether by letting the person who requests the change do it on their own.

Is that going to result into anything you’ll notice? Probably not. But if we’ve done our job well, the new landing pages will be built and updated faster, will load faster, and the colleagues who come up with the content will take the control from engineering.

Rusty the cat

~ Veselin ~ 14 Comments

A story about the 33-year-old cat Rusty took Reddit by storm. Rusty passed away at the age of 33, making him into top 10 of the oldest cats in the recorder cat history. The poster submitted proof to the mods of r/cats that Rusty was real. People rushed to update Wikipedia’s list of oldest cats, expressed condolences, sent love and wishes. The post generated 134K likes and was probably viewed by most of the non-bot Redditors.

Unfortunately, Rusty was AI slop. Rusty:

The post and the bot that submitted it got deleted.

I think my attempt to restrict Reddit to a few essential subreddits like r/cats is not very successful and I still have exposure to something that I wouldn’t even call AI slop. More like farming for free human-generated text for the purpose of training LLMs. Rusty helps me understand why the sudden rush to gather personal IDs and verify humans on social media. All the social networks are vulnerable to slop and risk losing engagement if they don’t put it under some level of control.

Here’s a real orange cat for you, blissfully unaware about the decay of r/cats.

UPDATE: this is a male cat named Pesho, also known as The Son of a Mother. Likes cuddles and bites for no reason.

AI Singularity

~ Veselin ~ 14 Comments

I’m a software engineer. My job mostly boils down to three things:

  1. Understanding a requirement and turning it into tasks
  2. Implementing those tasks or monitoring the implementation by others
  3. Querying data about the project – events, stats, trends and such

About a year ago, I switched entirely to AI-first engineering or vibe coding. Essentially, I let AI do most of the engineering work and mostly review the output it and provide feedback. By doing that, I felt a gradual increase of my output.

At first, the gains were modest and it wasn’t uncommon to lose more time with AI than I would’ve lost without it. Then the models improved. I experimented with new tools and ways of work. I learned what works for me and what doesn’t.

Today, I feel somewhere between 2x and 5x more productive than I was before. It happened gradually, not overnight.

Which leads to the bigger questions:

How far can this trajectory go? What are the moral and societal implications if it keeps scaling up?

If an individual engineer can increase their output 2x, does global engineering output double? Or do we simply need half as many engineers? And what happens if the multiplier isn’t 2x but 20x? At what point does implementation become irrelevant? Is that threshold 5x productivity? 50x? There must be a number after which coding won’t matter.

Is there a future where organizations only need small groups of engineers who mainly handle:

  • Rare edge cases
  • System architecture
  • Oversight of autonomous systems

If that happens, what becomes of the generation that studied software engineering expecting decades of demand, where the demand is now just gone?

If each engineer becomes a force multiplier, 5x or 50x of what a human of the past would be, then human capability is expanding, not shrinking. So how can the need for humans decrease if every human is more powerful?

Then there’s the ethical layer.

Most coding models are trained, at least in part, on open-source code. Millions of developers contributed to that, often without attribution or compensation. Zero of them did it to make a couple of demigods the richest men alive. And some of the people whose code was used to make the AI coding agent possible would face a future of unemployment and misery.

If coding productivity keeps accelerating, could we approach something resembling a software singularity? A point where:

  • Anything specifiable is immediately implementable
  • Humans are no longer required for execution
  • Software creation becomes a matter of compute and cost

If that’s theoretically possible, the constraint stops being talent and starts being infrastructure and tokens.

How many data centers would it take to autonomously build the world’s software? How much compute to replace human implementation entirely? And if we ever reached that point, what happens to money or people?

I don’t have answers. But I see that that the society is accelerating like a spaceship towards a black hole. I wish there were more conversations going on about the vision for the future. I’ve not seen anything inspiring from the leaders of the AI transition from OpenAI, Google, Microsoft, or Anthropic. Everyone just hopes there’s no singularity ahead of us, while speeding up the ship that way.

Opus

~ Veselin ~ 3 Comments

Claude Opus is my current most favorite model. I had a few blissful months of using it. Generated some good PRs, got stuck in debug loops not as many times as with previous models. I ended up extending the spend limit multiple times.

Opus Cocktail Bar, Sofia

After burning through far too many tokens, I had to stop and think. Is my usage really appropriate? Is it worth thinking how much tokens each prompt consumes? Is it because of the MCPs? Why does it make all these API calls to my dev server? How much does all of that even cost? It’s not clear from the dashboard at all.

While I’m rethinking my life’s choices, I switched to Codex and GPT 5.2. I feel like between the 4 AI editors that I have, I may have enough agent time available to last until the end of the billing period.

Being stuck with one option is not ideal. The situation is not like I have to write code without agents but my overuse of Opus is giving me a glimpse into a future where these models may start costing as much as people.