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- Filament v4.0 Stable, Laravel Boost, Laravel 12.23, 12.24 & The State of AI 2025, When Building Gets Easy, Winning Gets Hard & more
Filament v4.0 Stable, Laravel Boost, Laravel 12.23, 12.24 & The State of AI 2025, When Building Gets Easy, Winning Gets Hard & more
Ahmad
August 17, 2025
Hey Makers 👋
It’s been a busy week in the Laravel world, while the latest framework releases (12.23 & 12.24) are mostly about polish and fixes, there’s one small but very handy new addition that will save you some boilerplate code (more on that below 👇).
On top of that, Filament just shipped its long-awaited v4.0 stable with big performance gains and fresh features. If you’re using SaaSykit, good news: support for v4.0 is right around the corner.
And perhaps the most exciting announcement: Laravel Boost has officially launched, bringing AI-assisted development into the heart of the ecosystem by giving AI the context it needs to generate framework-aware code.
Often you’ll want to append something to a nested array if it exists—or create it if it doesn’t. That usually means a bit of boilerplate. Now it’s just one call:
if ($this->hasChanges($data)) {
Arr::push($result, 'pending.changes', $data);
} If $result['pending']['changes'] doesn’t exist, Laravel creates it as an empty array first, then pushes the new value. If it already exists, it just appends, no extra checks needed.
From the Community
It's official! As of today, August 12, 2025, Filament v4 is officially stable! And in large part, that is thanks to our incredible community and all the help with testing, bug fixing, and overall recommendations. We don't take for granted all of you and the work you've put in to help us get to where we are today.
Are you ready to take your Laravel development workflow to the next level? In this video, I dive into the public beta of Laravel Boost, a game-changing AI coding assistant designed specifically for Laravel projects. Whether you’re a seasoned developer or just getting started, Lateral Boost promises to make your coding experience smarter, faster, and more productive.
Pulse delivers a dashboard of application metric cards. Beyond these are reusable templates and a record-and-aggregation system to help us craft custom cards tailored to our very needs.
When something doesn't work on the first try, what do we do? We try it again, right? Expecting that it might work this time.
We, as a human, do this all the time in our day-to-day lives.
In modern-day applications, there is often a need to collect user data through forms. When many details are required from users, the form can be very long and look messy. This often leads to a bad user experience and a high bounce rate from the application. A simple solution to this is creating multi-step forms.
If your app ingests data from users (webhooks or similar), then it’s important not to miss any of that data.
This is actually a bit scary. We need, like, a lot of uptime! The typical way to increase uptime smells like “scaling” and often feels like expensive premature optimization. How do we do this!?
Before we start optimizing performance we need ways to effectively measure it. But even before we can measure it we need to know what exactly we want to measure.
All about SaaS
If 2023 was the AI Big Bang*, 2025 feels like First Light. The fog of the early calamity is lifting— revealing clusters of foundational companies, best practices for building, and patterns for startup success. We’re still a ways from declaring any semblance of stability, but these early AI Galaxies give us more visibility than ever of the shape of things to come.
My fellow Balderton Capital EIR Dan Teodosiu and I recently published an article on aligning product and go-to-market teams using metrics, specifically customer-value metrics. In this post, I’ll talk a bit about the article and how we came to write it, with the hope that I’ll pique your interest in reading it.
I shared my take on Sam Altman’s recent tweet that “we’re entering the fast fashion era of SaaS very soon” on LinkedIn here.
The post triggered a controversial discussion with 139 comments (and counting) - something I really enjoy and one of the key reasons I regularly post online. Few better ways to challenge your thoughts at scale ;)
Chasing product-market fit when you don’t even have messaging that resonates with your ICP is the wrong approach for many early-stage startups.
By skipping messaging validation, you’ll end up paying for it in churn, CAC, and missed sales later.
When I meet a startup, I always try to answer a high-level question: “How well does this company understand their customers?” This can be revealing of many related downstream questions: “Does this company have product-market fit? Are they solving an important problem for their customers? Are they prioritizing the right pieces?”
Last week I was at dinner with a group of executives, and of course, the topic of ChatGPT and AI came up. We went around and shared some of our favorite use cases for the technology, as well as ways we are experimenting with AI in our respective companies. Then I asked if anyone used existing prompts or more advanced context engineering. Not a single person did.
Videos
Keep building, keep rocking! 🤘