This month I gave myself one job to do: redesign the Scarfolk theme.
markconroy 27th Feb 2026Do you have a favorite restaurant with a “secret” menu item? Well, DrupalCon has its own secret. And, I’m spilling the beans. If you ask any DrupalCon veteran, what the best thing about the events are, they’ll say, “The Hallway Track”. Huh?
What is the “Hallway Track”?The “Hallway Track” is the space around and between official schedule items. This might be in the actual hallway, in the sponsor floor, at the parties, or even in a taxi ride to the airport.
Space like this lets serendipity happen. You might get bored and join a conversation and make new friends. You might hear of a problem, and think of a new business idea. Or…
Stories from the Hallway TrackI reached out to several friends to get hear some stories about their experiences in the hallway track
Nikki Flores tells about how she ran into a colleague at DrupalCon and became fast friends!
I had worked with her for almost 2 years, had seen pictures of her family and her dog and her vacations. We had always been connecting weekly and sometimes twice a week on our teleconferences. I never saw her in person until she called my name from across the hall at DrupalCon. When we saw each other, we were so excited because we recognized each other's faces!
Carlos Ospina tells the story about how he took his son to DrupalCon, and that led to the genesis of the IXP program.
I wanted my son to understand why I love this community so much, so we flew him out to Seattle. I told him I knew a lot of people there, but since it was contribution day, there would not be much time to socialize.
After COVID, he agreed to join us again for Portland in 2022. The Sunday before the event, we met some friends for breakfast. I spotted someone I thought I recognized and mentioned it. My son teased me, saying it was probably just because I think I know everyone at DrupalCon.
We sat down, and in the middle of breakfast Eduardo Telaya walked by our table. I called out to him, and he came over. We hugged, and suddenly we were no longer just five people having breakfast. A couple of other friends stopped by to say hello, and our table grew. My son looked at me and said, “So maybe you really do know everyone at DrupalCon.”
I think that moment stuck with him. When we started talking about career options, he agreed to give Drupal a try and came with us to Pittsburgh in 2023 to look for a job. After all, Dad knows everyone, right?
Unfortunately, that was when the hiring slowdown was becoming clear. It was the first time the Drupal Association organized a job fair, and we attended. At one point I had to step away to take a call, and my son did great on his own. He introduced himself, talked to people confidently, and put himself out there. But there were no real opportunities for someone in his position. He had just completed DrupalEasy, had no professional experience, and no background in computer science.
That experience led to conversations with Anilu, and from those conversations the IXP Program was born. It started as a way to help my son get a foothold. He has since moved on from Drupal to explore something different, but the program lives on. We are now approaching 1,750 contribution credits awarded, and six participants have gone through the program.
What began as something personal turned into something that helps others enter the community.
Mike Gifford tells several stories about how he met friends and started his journey to be an Accessibility Maintainer for Drupal Core.
I’ve had so many great conversations with people who have inspired me, challenged me, and made me laugh in the hallway of DrupalCons. Over coffee, lunch or just while trying to charge a device, leaning against the wall.
The first story that came to mind was trying to find Eriol Fox in DrupalCon Vienna. I am not sure what we were using to message each other, but there was a large delay between sending and receiving messages. Then there is the challenge of actually finding each other in these crazy conference centers. Anyways, we had a good time chatting, but she also pointed me to some folks that she had connected with in Japan. I was going to be going there and wanted to find some open source connections while there.
I think it was in DrupalCon Atlanta that I had great conversations with Stephen Mustgrave & Stephen Musgrave. We were all in slightly different breakout groups. I had confused the two of them only a month or two ago and remembered connecting with them and verifying that they are indeed not the same person.
I can’t remember when I ran into Mark Gifford, but it was in some hallway, where we talked about me mostly grabbing the @mgifford in so many new social platforms before he could. I guess he has some right to them.
I actually started contributing to Drupal’s accessibility after a hallway chat. It was some time before Drupal 7 was released, and I remember going up to Webchick and complaining about accessibility errors in Drupal. She turned around and suggested I could do something about it. I don’t know how many thousands of hours I’ve spent on fixing accessibility issues in Drupal since she made that suggestion. Thanks Angie.
Mike Anello intentionally avoided the assignment, but tells a great story about the contribution room!
Forget about the hallway - let’s talk about the contribution room track.
There’s no better way to learn something new and make meaningful personal connections than spending a few hours in a contribution room. There are a few Drupal events each year that I know I won’t be wasting any time listening to over-caffeinated Florida-based front-end developers rant at me about the future of front-end development. Instead, I arrive with an agenda to learn something new about some new Drupal thing by spending time in the contribution room helping to test, write documentation, or work on existing issues.
I can credit this method for supercharging my learning of single directory components, ECA, a good portion of the Drupal AI ecosystem, and more Views internals than I ever wanted (thanks, Lendude!)
At my first Drupal Dev Days (Ghent 2023, IIRC) one of my goals was to use my evolving PhpUnit test-writing skills to use in the contribution area. After talking with a few folks, I was introduced to Len Swaneveld, a core maintainer for the Views module. Len pointed me at a few potential issues to work on, and after reviewing a few of them, I settled on one that seemed like it was completable in a reasonable amount of time. What transpired over the next few weeks will be no surprise to anyone who’s ever worked on core Views code - nothing is simple.
But, the thing that I remember most about that issue is the time that Len spent with me (both in-person and online) mentoring me on some of the darker areas of the Views code base. It gave me an all-new perspective of the module as well as the challenges of maintaining it.
This process, and similar ones related to other areas of Drupal, I knew that I was improving my skills by learning from leaders in the community - all while I was helping them!
Perhaps the most rewarding part of it is the fact that after the event, a personal connection now exists - and it doesn’t feel forced. It is a perfectly natural thing to reach out to these new connections via email or Slack with a little, “it was great getting to know you a few weeks ago at Dev Days; I have a quick question for you…”
Networking is the reason for Drupal events - not presentations (sorry, presenters!)
Michael Richardson tells us how the hallway track led to the creation of DrupalCon Singapore!
For me it would be when I went to DrupalCon Lille with the wild idea of running something like a "DrupalCamp Asia", which would be focused on trying to get folks from all over the continent (and the Pacific) to connect together and share their Drupal stories, cultures, and experience for the first time in nearly 10 years.
Through the power of the hallway track in Lille, I was able to connect directly with sponsors, Drupal Association leadership, and regional community leaders, and over those few days the idea evolved into a fully fledged DrupalCon Asia with sponsors, organisers, and the support of the DA all aligned. What would have taken months to organise online was all put in place in just 3 days and a year later, DrupalCon Singapore was a massive success. I'm not sure that would have been possible without those first conversations half way across the world in Lille.
Baddý Breidert tells us how participating in the DrupalCon prenote led to multiple friendships!
My first DrupalCon was Amsterdam in 2014 and I remember going to that event not knowing anyone. During the Hallway Track I got to know MortenDK that introduced me to a lot of people and from that conference it always became a bit easier to attend DrupalCon. At DrupalCon Dublin 2016, Jam and others from the community invited me to join the pre-note which I gladly accepted. The pre-note always happened before the Driesnote and the purpose of the event was to entertain the keynote attendees and kick-off the conference. The show featured an Irish adventure theme, where the characters attempted to find a “pot of gold” while exploring the concept of “scope” in a humorous, technical, and musical “infotainment” style.
Cristina Chumillas tells how she went outside of the conference to find a magical donut, and brought it back to share!
Soooo on the first DrupalCon in Portland after covid, the day after committing Claro and Olivero, with Lauri, we went for a quick adventure to find a famous doughnut with bacon and maple syrup. At Voodoo Doughnuts.
Anyway, we were at the sprints and were working on Olivero issues, so by the time we left it was about to close. On the way it started raining A LOT and when we arrived they were closing and there were no more doughnuts. But since we were there we took the chance to get inside the shop and asked for it, and they still had one! So we bought it and ended up eating it with 8 people at the sprints.
JD Flynn perfectly wraps up the hallway track in his rendition.
To me, the hallway track is where the magical moments are found. It's where connections are made. It's where friendships begin. Sessions at events are amazing, and should definitely be attended. However, the real inspiration and sparks happen during spontaneous conversations that happen just because you bump into someone and start talking about this idea you've had or this bug you found. Before you know it, you're both sitting with your laptops out and building something together. That doesn't happen while sitting quietly in a session.
The "hallway" track isn't limited to just the hallway of the event's venue either. It carries over to the parties and the after parties where lifetime friendships and memories are formed. It's not an exaggeration to say that most of the people in my life who I consider good friends are good friends because of that spark that happened in the hallway, wherever that hallway might exist. It could be bonding over a drink, shared love of a type of food, randomly bumping into someone who looks familiar outside of the event, or picking the song at karaoke that gets everyone up and dancing. I owe some of the strongest relationships in my life, personally and professionally, to the hallway track.
Make space for the Hallway TrackAs JD said, the hallway track is where the magic happens. But how do you find it?
You need to put yourself out there. Sit down at lunch tables where you don’t know anyone, and strike up conversations. Go to the event parties and talk to people in the lines at the bar. Join a trivia team with people that you don’t know!
You might just end up with some serendipity of your own!
Visitors form an impression of a site almost instantly. If those first moments feel smooth, they’ll keep exploring. If not, they’ll quietly close the tab. That challenge is even greater for content-rich websites, where each request can trigger complex rendering behind the scenes.
I hadn't head of WebMCP, but now I'm mildly fascinated by the possibilities.
markconroy 25th Feb 2026Got some issues with Drupal workspaces? I got your back.
markconroy 25th Feb 2026At Tag1, we believe in proving AI within our own work before recommending it to clients. This post is part of our AI Applied content series, where team members share real stories of how they're using Artificial Intelligence and the insights and lessons they learn along the way. Here, Ajit Shinde (Senior Drupal Developer), explores how AI supported his work on the contributed Trash module, including a complex taxonomy hierarchy challenge, and what he discovered about getting real value from these tools.
How I Used AI to Tackle a Tricky Trash Module ChallengeI have been using AI for work for quite some time now for various personal projects. I was inspired and empowered by Tag1's internal AI workshop, and I started using it extensively for both internal projects and a challenging contrib module assignment. What surprised me most was not AI magically solving hard problems, but how much time it could save on the repetitive parts of the work, especially around writing and iterating on tests. I want to share what I discovered because some of it genuinely surprised me.
The Challenge of Adding Taxonomy Support to TrashWanting to find an issue to tackle with AI for my own learning experience, I picked up issue #3491947 to add taxonomy support to the Trash module. The Trash module provides soft-delete functionality for Drupal entities and, once configured, it lets you delete entities temporarily and restore them later or purge them permanently if needed. This sounds straightforward enough, but taxonomy terms have a wrinkle that makes things interesting. When you delete a parent term, Drupal core deletes its children too, and this hierarchical deletion creates real challenges for a trash and restore workflow.
This issue had been open for a while with some interesting discussion about the right approach, and I had actually started working on it earlier as part of Tag1's sponsored open source development. I had created an initial MR that enabled trashing terms, but the hierarchy problem was still unsolved, and I wanted to see how AI would handle the complexity.
The module maintainer, Andrei Mateescu (amateescu), had suggested an elegant approach in the issue queue: since cascading deletes happen in the same request, all the deleted terms would have the same timestamp, so we could use that deleted timestamp to restore child terms along with their parent. It sounded promising, and I wanted to test whether it would actually work. So I started down the path, expecting that if I could lean on the shared deleted timestamp, I might avoid storing extra hierarchy data myself.
First Steps: Planning with ClineI started with the Cline extension for VS Code in a “Plan” mode (Figure 1).
Figure 1: Cline Plan modeJust for fun, I opened with a prompt asking to help me formulate a plan by going through the issue and studying the Trash module code. It could not access the issue directly, which is actually good from a security perspective, but Claude scanned my project and was able to find the Trash module in it, scanned through the code, and presented a decent understanding of how trashing works. I then explained the hierarchical deletion problem in detail, and the AI checked again and reached the same conclusion I had. When I shared Andreii’s suggestion about using the delete timestamp for restore, the AI presented a three-phase plan covering implementation, basic tests, and optional UX improvements.
At first glance it looked reasonable, but I spotted a major flaw immediately. The AI assumed that deleting a term would trash the parent and hard-delete the children, which is simply wrong. Once trash support is enabled, all terms being deleted move to trash including the children, and every bit of logic that followed was built on this broken assumption. This is exactly the kind of thing that makes working with AI both frustrating and fascinating. There were other misunderstandings (hallucinations) too. So, I decided to start fresh.
After a few trials, I used the following detailed prompt in a new session:
Assume a role of an expert Drupal developer developing a custom feature for the contributed Trash module on a Drupal site. We want the module to support "trashing" taxonomy terms, which is currently disabled. Background/Current State: The Trash module adds a deleted column to entity data tables to enable soft-delete/trash functionality. Taxonomy term trashing is currently disabled via a code line that I can remove to re-enable it. When a taxonomy term is deleted by default in Drupal, its children (if they have only one parent) are also deleted. This complicates restoration logic. Goals: Allow taxonomy terms to be trashed (not hard-deleted), leveraging the module’s infrastructure. Enable correct restoration of trashed terms, including their child terms. Technical Challenges: Taxonomy Overview Page Tree Rendering:\n\nThe taxonomy overview page uses the buildTree function to load hierarchical term data via direct database queries. buildTree currently doesn’t account for the trashed (deleted) column, so trashed terms might break the vocabulary page (e.g., inaccessible, errors). Core updates to taxonomy API are not allowed (must solve without modifying Drupal core). Restoration Logic for Hierarchies: The existing trash implementation only restores single entities. When a parent term is restored from trash, I need to also restore child terms that were trashed at the same time. All terms trashed together share the same deleted value, which can be used to identify them as part of a single trash operation. Please provide step-by-step guidance for: Enabling trash support for taxonomy terms. Where and how to safely re-enable support (removing the disabling line). Modifying or extending buildTree (or its usage) without core changes to prevent errors from trashed terms. Approach for filtering out trashed terms when rendering the tree. If possible, suggest ways to hook, alter, or override tree loading, limited to contributed/custom code. Implementing restoration logic for hierarchical terms. How to batch-restore child terms if their parent is restored from trash. Using the shared deleted value (timestamp/etc.) to identify child terms involved in the same operation. Any Drupal hooks or architectural suggestions for this process.I had to do several trial-and-error iterations to come up with this prompt. With that detailed context, the AI performed much better.
Why This Prompt WorkedThis prompt was far more effective than earlier ones because it clearly defined the AI’s role, goals, and constraints from the start.
By identifying the AI as an expert Drupal developer, the prompt aligned its reasoning with real-world Drupal development patterns rather than generic guesses.
Defining clear end goals (enabling trash for taxonomy terms and restoring hierarchical relationships) kept the conversation focused, while listing technical challenges upfront, such as fixing buildTree() behavior without touching core and managing term restoration logic, provided essential guardrails against hallucinations.
Together, these details created a structured context that helped the AI generate more accurate, actionable output instead of speculative or incorrect code suggestions.
It enabled the trash support for taxonomy in configuration by identifying the code. It then tried to fix the listing page queries and failed. I pointed it to use query tags to tag the listing queries and alter them to check if the term is trashed. This was implemented swiftly. The AI implemented a Trash handler for taxonomy terms, which was actually a good decision I had not prompted. But its implementation had a fatal flaw in that it used a class-level array variable for storing the term hierarchy (static caching). This obviously will not work because delete and restore operations happen in separate requests with no persistence between them.
While testing, I found that the trash module automatically trashed the child terms if the parent is deleted. This was expected behavior.
The Discovery That Changed My UnderstandingThrough old-fashioned debugging and stepping through the deletion flow, I finally understood why the timestamp approach would not work, and it comes down to how Drupal core handles term deletions.
Say you have a hierarchy of terms A and B where A is the parent. When term A is deleted, Term::preSave is called and then the term is deleted. After that, Term::postDelete is called to delete the orphaned children. But here is the problem: When the child term B is about to be deleted, Term::preSave is called again, and that function resets the parent to root before the term gets trashed. This removes any trace of the previous hierarchy entirely.
So even though both terms end up with the same deleted timestamp, we have lost the parent-child relationship by the time they are in the trash. We will need to store the hierarchy data somewhere else, probably with the term itself as others had suggested in the issue. I posted this finding back to the issue queue because it changes the direction of the solution. After that, the maintainer suggested that we pause and reconsider the overall direction of the fix before writing more implementation code. I didn’t want to just stop working at that point, so I decided to focus on something that would still add value: a solid set of tests around the behavior we had uncovered.
I reached this conclusion through traditional debugging, but AI became useful once the solution path was unclear, because it could help me quickly generate and refine tests instead of spending my time on boilerplate.
Starting Fresh and Finding My RhythmWith the understanding that solving hierarchical restore is tricky and needs more intervention from the module’s maintainer, and that the direction of the fix was on hold, I decided to change how I contributed. Instead of trying to force a solution, I asked AI to help enumerate test scenarios and create tests for trashing, restoring, and purging terms, and it came up with a decent list of scenarios (it applied trashing, restoring, and purging):
I specifically requested creating atomic tests where one test does one thing. In previous iterations I had noticed it crammed multiple assertions into single tests, but this time it created a comprehensive test class covering all scenarios properly. AI generated the initial test code and structure, and my job was to review, adjust, and guide it toward clean, atomic tests that matched how we actually use the Trash module.
This felt like a real breakthrough in how to work with these tools, namely: you must provide as much context, detail, and guidance as possible in order to get good results.
It tried to run these tests, failed a few times, and I had to step in to explain that the project uses DDEV and tests need to run inside the container. Even then it took three or four more attempts to get the tests running, which tested my patience a bit. As expected, all tests except the hierarchical restore passed.
None of this moved the core solution forward directly, but it still added real value. By using AI to design scenarios and generate most of the test code, I could keep making progress without sinking a lot of time into repetitive work. Those tests now act as a reusable safety net for future changes, so when the direction is finally decided, we will already have a solid foundation to build and iterate on.
Without AI, I probably would have stopped at one or two manual checks or a much smaller test suite, simply because of the time investment. With AI handling the boring parts of writing and reshaping tests, I could afford to cover more scenarios and refine them, even though the underlying solution is still on hold.
Internal Work Showed Me the Real PotentialThe Trash module work showed me how AI can help with testing around complex problems, but internal projects are where it really clicked for me. For internal projects, the AI proved more immediately useful, and I got genuinely excited about the possibilities here. For example, on a separate internal project, I needed to create a text filter plugin for rich text formats in Drupal that checks for special unordered lists and replaces them with a Storybook component.
I crafted my prompt carefully based on previous attempts where the AI went wild and tried to implement everything from scratch including the filter plugin, the component, and all the theme functions. In a new session I prompted explicitly that I did not need a new theme function, that it should just use twig include from Storybook, and that it needed to handle nested lists properly since they are multi-level.
It generated a decent filter plugin on the first try, and while there were mistakes of course, I guided it toward modern PHP patterns like attributes and constructor property promotion and PHPStan compliance. A couple of project-specific issues needed manual fixes, but the core implementation was solid.
The tests went really well too. I started with a Kernel test, then tried a Functional test, and eventually settled on Unit tests on the tech lead's suggestion. The Unit test was precise and to the point, and I think this is where AI really shines because the context is clear and limited in unit testing scenarios.
CSS Help Was a Pleasant SurpriseAs someone who is mostly a backend developer, this is where I found the use of AI to be genuinely delightful. It quickly understood the project's styling approach, detected that we were using Tailwind, and suggested fixes with basic prompts. No deep context needed, just quick wins that saved me from the usual frustration of wrestling with frontend styling.
Together, these internal projects reinforced the same pattern I saw with the Trash module: AI is most helpful when I give it a narrow, well-defined problem and let it handle the repetitive parts while I focus on the decisions.
The Lessons That Actually MatterThe biggest realization I had is that you need to treat AI as a junior developer who needs clear guidance and supervision. It never replaced my debugging or architectural judgment, but it did make it cheaper and faster to handle the repetitive parts of the work. Providing context aggressively makes an enormous difference, and the more specific you are about the codebase structure the better the results turn out. In my case that meant offloading a lot of test boilerplate, trying out different test structures (Kernel, Functional, Unit), and iterating on scenario coverage without feeling like I was wasting time. Limiting where the AI can scan also helps manage the context window size, which matters more than I initially realized.
I found that spending time in Plan mode before rushing to Act pays off tremendously because it lets the AI think through the problem first. Keeping scope small is also critical since large ambitious prompts lead to hallucinations and broken assumptions while small well-directed tasks actually get completed correctly.
When the AI starts hallucinating, restoring to a previous checkpoint or starting fresh with the same context works much better than trying to correct a conversation that has gone off the rails. I learned this the hard way through several frustrating sessions.
Managing the “context window” for the AI is important. Sometimes starting a fresh conversation makes more sense than continuing with the existing one. I made sure that I exported the context in each conversation, adjusted it and carried that to the next session.
Used this way, AI feels like a junior developer who is great at cranking out tests and repetitive scaffolding, while I stay focused on debugging, design decisions, and understanding the problem. The thing that excites me most is that using AI we can finally do test-driven development without it feeling like a burden. That alone makes learning to work with these tools worthwhile, and I am looking forward to exploring this further on future projects.
This post is part of Tag1’s AI Applied content series, where we share how we're using AI inside our own work before bringing it to clients. Our goal is to be transparent about what works, what doesn’t, and what we are still figuring out, so that together, we can build a more practical, responsible path for AI adoption.
Bring practical, proven AI adoption strategies to your organization, let's start a conversation! We'd love to hear from you.
Image by Cline
At LocalGov Drupal Dev Days in London earlier this month, the topic came up of releasing custom project code as contrib modules.
There were many people in the room who said they had custom code in their site codebase that they planned to release as contrib modules, but needed to find the time to get it ready. I heard people mention the work that they had left to do for this, and it sounded very familiar: generalise the functionality, remove client-specific code, remove client-specific strings.
This reminded me of a session I did at Drupal Camp London way back in 2014, on this very topic: releasing more code from your codebase, to lower the amount of custom code and share more with the community. Since then, I've gone on to release many more contrib modules, and the introduction of more powerful APIs and systems with Drupal 8 has added to what's possible, so I thought I'd revisit my thoughts on different ways to approach this. My presentation was on the 'why' as well as the 'how', but I'll assume you know that part already.
The first thing to say is that as with tests or accessibility, it's much easier to write contributable code from the start rather than rework it later.
Fundamentally though, whether to plan from the start or retrofit, the baic principle is that you want your code to be split into two layers: the contrib, and the custom. Think of it as a contrib cake with custom icing on top.
The tricky part is where to put the dividing line. It's not always clear how much of your functionality is generic and applicable to other use cases and other clients.
I always err on the side of putting too much in contrib, and offsetting the possibility that the contrib code is too specific with customisability.
But how do we actually slice it up?
PluginsPlugins are one of the most powerful ways of switching behaviour in Drupal. Defining your own plugin type allows you to design exactly which parts of the code are handed over to the plugin, and in as many places as you want, by adding more methods to your plugin's interface.
If the methods in the plugin start to look unrelated, you can always add a second plugin type. And if the amount of boilerplate needed for a plugin type is offputting, Module Builder generates it all for you.
It's worth also considering the lesser-known sibling of attribute plugins, the YAML plugin. If you only want to change strings or parameters, then you can put all that into YAML instead of a whole class. (And YAML plugins do allow custom classes for oddball cases.)
With a plugin system, you need a way to set the plugin to use. There are two ways you could do this: if it's a single plugin that you select, use a plain config setting. If it's a pattern that you might want several of, use a config entity that holds the reference to the plugin. This requires a fair bit of boilerplate code, but there are examples in contrib that you can crib from, such as Flag and Action Link.
And remember that there are other systems that allow ways to select a plugin: field formatters and widgets, Views handlers for fields and filters and so on, paragraph behaviours, and more.
Twig templatesTwig templates are a great way to customise output from your module. You can change strings, rearrange elements, and add CSS classes for styling.
You'll need to define the theme hook using hook_theme(), and define the variables the template uses. Then, provide a neutral version of the template in the contrib module's /templates folder, and override it in your site's theme.
Form alterationFor forms, use hook_form_alter() to change the labels of elements and their order.
Or you can even add extra form elements, and handle their values in a custom submit handler.
If your alterations start to get too complex, consider using a plugin that you pass the form to for customization.
Overridden configSimplest of all is to use config to override values, whether they are strings or parameters.
Define the config schema for the settings, add a default config to the module's config/install, and then override it in your project's config.
Other APIsIt's worth looking at existing APIs that allow a custom module or theme to alter functionality. For example, in core, field widgets can be altered with hook_field_widget_single_element_form_alter() and field formatters with hook_field_formatter_third_party_settings_form(). And all sorts of unspeakable things can be done to Views with field, filter, argument, and sort handlers, and display extender plugins.
ShortcutsIf you're short on time and resources to work on splitting your cake up, there are some shortcuts you can take. It's what I call the 'code and run' method of releasing code: the contrib module is incomplete, but released in the hope that the next person who finds it useful will pick it up and move it forward.
My opinion on this is that releasing some code, even if it's half-baked, is better than not releasing code at all, as long as you clearly explain on the project page that the module has things missing or incomplete, and leave a trail in the code in the form of comments and placeholders.
Do you need help with preparing custom code to be released as a contrib project? It's a great way to get more presence for you or your organisation. I'm available for hire - contact me!
joachim Tue, 24/02/2026 - 09:52 TagsWe're excited to celebrate you -- our future speakers! If you've got an idea for a session, now's the time to get involved in MidCamp 2026, happening May 12-14 in Chicago.
Call for SpeakersSince 2014, MidCamp has hosted over 300 amazing sessions, and we're ready to add your talk to that legacy. We're seeking presentations for all skill levels, from Drupal beginners to advanced users to end users and business professionals!
For full submission details and guidelines, visit: midcamp.org/events/2026/how-submit-session
Key DatesLooking to connect with the Drupal community? Sponsoring MidCamp is the way to do it! Whether you're recruiting talent, growing your brand, or simply supporting the Drupal ecosystem, MidCamp sponsorship offers great value. Act early to maximize your exposure!
Stay in the LoopReady to submit your session? Click away and let's make MidCamp 2026 unforgettable!
For most developers, DDEV solves a common challenge: making sure that each developer has a consistent, stable local environment for building their web application. We had more and more success with DDEV at Lullabot, but another related issue kept coming up: how do we grow and develop our use of continuous integration and automated testing while avoiding the same challenges DDEV solved for us?
A typical CI/CD pipeline is implemented using the tools and systems provided by the CI service itself. For example, at a basic level you can place shell commands inside configuration files to run tests and tools. Running those commands locally in DDEV is possible, but it's a painful copy/paste process. If you're a back-end or DevOps engineer, odds are high you've wasted hours trying to figure out why a test you wrote locally isn't passing in CI – or vice versa!
As a first step, we used Task to improve our velocity. Having a unified task runner that works outside PHP lets us standardize CI tasks more easily. However, this still left a big surface area for differences between local and CI environments. For example, in GitHub, the shivammathur/setup-php action is used to install PHP and extensions, but the action is not identical to DDEV. Underlying system libraries and packages installed with apt-get could also be different, causing unexpected issues. Finally, there was often a lag in detecting when local test environments broke because those changes weren't tested in CI.
This brought us to using DDEV for CI. It's a great solution! Running all of our builds and tasks in CI solved nearly every "it works on my machine" problem we had. However, it introduced a new challenge: CI startup performance.
Unlike using a CI-provider's built-in tooling, DDEV is not typically cached or included in CI runners. Just running the setup-ddev action can take up to a minute on a bad day. That doesn't include any additional packages or Dockerfile customizations a project may include. At Lullabot, we use ddev-playwright to run end-to-end tests. Browser engines and their dependencies are heavy! System dependencies can be north of 1GB of compressed packages (that then have to be installed), and browsers themselves can be several hundred MB. This was adding several minutes of setup time just to run a single test.
Luckily, based on our experience building Tugboat, we knew that the technology to improve startup performance existed. When WarpBuild was announced with Snapshot support in 2024, we immediately started testing it out. We theorized that the performance improvement of snapshots would result in significant startup time improvement. Here's how we set it up!
We had three parallel jobs that all required DDEV:
Note that our Playwright tests themselves run in parallel on a single worker as well, using lullabot/playwright-drupal. This allows us to optimize the additional startup time for installing Drupal itself (which can't be cached in a snapshot) across many tests.
After linking WarpBuild to our GitHub repository, we had to update our workflows. For the full combined example, see the repository at ddev/ddev-ci-warpbuild-example.
Here is an example representing the changes we made to our workflow after enabling Snapshots in the WarpBuild UI. At a high level, here's the flow we want to create with our GitHub jobs:
flowchart TD A[determine-snapshot: <br>Hash key files] --> B[Request WarpBuild runner<br>with snapshot key] B --> C{Snapshot exists?} C -->|"Yes (fast path)"| D[Restore snapshot<br>DDEV pre-installed] C -->|"No (first run)"| E[Install DDEV, browsers,<br>and dependencies] D --> F[Start DDEV & run tests] E --> F F --> G{First run?} G -->|Yes| H[Clean up & save snapshot] G -->|No| I[Done!] H --> IStart with a basic workflow to trigger on pull requests and on merges to main.
name: "WarpBuild Snapshot Example" on: push: branches: [main] pull_request:Before running our real work, we need to know what snapshot we could restore from. We start by creating a hash of key files that affect what gets saved in the snapshot. For example, if Playwright (and its browser and system dependencies) are upgraded by Renovate, we want a new snapshot to be created. Extend or modify these files to match your own project setup.
jobs: determine-snapshot: # This could be a WarpBuild runner too! runs-on: ubuntu-24.04 outputs: snapshot: ${{ steps.snapshot-base.outputs.snapshot }} steps: - uses: actions/checkout@v6 - name: Determine Snapshot Base id: snapshot-base run: | set -x hash=$(cat .github/workflows/test.yml test/playwright/.yarnrc.yml test/playwright/yarn.lock | md5sum | cut -c 1-8) echo "snapshot=$hash" >> $GITHUB_OUTPUT shell: bashWarpBuild needs some additional configuration to tell GitHub Actions to use it as a runner. This could be as simple as runs-on: 'warp-<runner-type>' if you aren't using snapshots. WarpBuild has many runner options available, including ARM and spot instances to reduce costs further.
The runs-on statement:
We also switch to the WarpBuild cache (so it's local to the runner) and check out the project. Update the cache paths as appropriate for your project.
jobs: # other jobs... build-and-test: needs: [determine-snapshot] runs-on: "${{ contains(github.event.head_commit.message, '[warp-no-snapshot]') && 'warp-ubuntu-2404-x64-16x' || format('warp-ubuntu-2404-x64-16x;snapshot.key=my-project-ddev-1.25.1-v1-{0}', needs.determine-snapshot.outputs.snapshot) }}" steps: - uses: WarpBuilds/cache@v1 with: path: | ${{ github.workspace }}/.ddev/.drainpipe-composer-cache ${{ github.workspace }}/vendor ${{ github.workspace }}/web/core ${{ github.workspace }}/web/modules/contrib key: ${{ runner.os }}-composer-full-${{ hashFiles('**/composer.lock') }} - uses: actions/checkout@v6We need to add logic to either start from scratch and install everything or restore from a snapshot. Since DDEV isn't installed by default in runners, we can use its presence to easily determine if we're running from inside a snapshot or not. We save these values for later use.
jobs: # other jobs... build-and-test: steps: # ... previous steps ... - name: Find ddev id: find-ddev run: | DDEV_PATH=$(which ddev) || DDEV_PATH='' echo "ddev-path=$DDEV_PATH" >> "$GITHUB_OUTPUT" if [ -n "$DDEV_PATH" ]; then echo "ddev found at: $DDEV_PATH (restored from snapshot)" else echo "ddev not found (fresh runner, will install)" fiIf ddev exists, we can skip installing it:
jobs: # other jobs... build-and-test: steps: # ... previous steps ... - name: Install ddev uses: ddev/github-action-setup-ddev@v1 if: ${{ steps.find-ddev.outputs.ddev-path != '/usr/bin/ddev' }} with: autostart: false # When updating this version, also update the snapshot key above version: 1.25.1At this point, we've got DDEV ready to go, so we can start it and run tests or anything else.
jobs: # other jobs... build-and-test: steps: # ... previous steps ... - name: Start ddev run: | # Playwright users may want to run `ddev install-playwright` here. ddev start ddev describe - name: Run tests run: | ddev exec echo "Running tests..." # Replace this with one or more test commands for your project. ddev task test:playwrightNow, tests have passed and we can create a snapshot if needed. If tests fail, we never create a snapshot so that we don't accidentally commit a broken environment.
We shut down DDEV since we're going to clean up generated files. This keeps our snapshot a bit smaller and gives us an opportunity to clean up any credentials that might be used as a part of the job. While we don't typically need a Pantheon token for tests, we do need it for some other jobs we run with DDEV.
jobs: # other jobs... build-and-test: steps: # ... previous steps ... - name: Clean up for snapshot if: ${{ steps.find-ddev.outputs.ddev-path != '/usr/bin/ddev' }} run: | # Stop ddev to ensure clean state ddev poweroff # Remove any cached credentials or tokens rm -f ~/.terminus/cache/session # Clean git state and temporary files git clean -ffdxNow we can actually save the snapshot. We skip this if we can since it takes a bit of time to save and upload. There's no point in rewriting our snapshot if it hasn't changed! The wait-timeout-minutes is set very high, but in practice this step only takes a minute or two. We just don't want this step to fail if Amazon is slow.
jobs: # other jobs... build-and-test: steps: # ... previous steps ... - name: Save WarpBuild snapshot uses: WarpBuilds/snapshot-save@v1 if: ${{ steps.find-ddev.outputs.ddev-path != '/usr/bin/ddev' }} # Using a matrix build? Avoid thrashing snapshots by only saving from one shard. # if: ${{ matrix.shard == 1 && steps.find-ddev.outputs.ddev-path != '/usr/bin/ddev'}} with: # Must match the snapshot.key in runs-on above alias: "my-project-ddev-1.25.1-v1-${{ needs.determine-snapshot.outputs.snapshot }}" fail-on-error: true wait-timeout-minutes: 30To test, once you have jobs passing, you can rerun them from the GitHub Actions UI. If everything is working, you will see all steps related to installing DDEV skipped.
Note: We don't pin actions to hashes in these examples for easy copypaste, but for security we always use Renovate to pin hashes for us. We would also like to use Renovate Custom Managers to automatically offer DDEV upgrades and keep the version number in sync across all files and locations.
The Results?While this seems like a lot of work, it was only about half a day to set up and test – and that was when WarpBuild was in beta, had minimal documentation and some rough edges. We haven't really had to touch this code since. Setting up new projects is an hour, at most.
Do you have other optimizations for DDEV in CI to share? Post in the comments, we'd love to hear them!
Hey experienced developers! You know how to tame Drush, charm Composer, debug like a detective, juggle configs, and wrestle with tricky modules. But there’s an event that will max out your RAM with Drupal hacks, insights, and wisdom.
Chicago may be famous for deep-dish pizza, but this spring it’s serving up something even more satisfying: deep dives into Drupal. DrupalCon Chicago 2026 is the place for seasoned developers to sharpen their skills, swap stories, and maybe laugh at a few module mishaps along the way.
It’s a code playground with a side of professional growth — sessions designed to challenge, inspire, and connect. Ready to level up your craft and enjoy a few geeky chuckles? The program is packed with standout sessions, but here are a few you absolutely won’t want to miss.
Top DrupalCon Chicago 2026 Sessions for Experienced Developers “The state of JavaScript Code Components in Drupal Canvas” — by Bálint KlériDrupal Canvas, the new-generation page builder, offers multiple ways to create pages for different audiences. Non-tech users will enjoy intuitive drag-and-drop tools, ready-made components, and even building pages from a prompt to an AI agent. But what’s in it for developers? First of all, it’s Code Components.
JavaScript in Drupal keeps evolving, and Code Components in Drupal Canvas are the latest twist worth watching. First unveiled at DrupalCon Atlanta, they came with a zero‑setup, in-browser editor and instant support for React and Tailwind CSS.
Things have moved fast: data fetching and Next.js-style image optimization are now supported, and experiments with server-side rendering and third-party imports are in progress. And editing isn’t limited to the browser anymore — a new CLI lets you work with Code Components anywhere, opening doors to decoupled frontends and fresh workflows.
Catch Bálint Kléri (balintbrews), the technical lead for JavaScript components in Drupal, in his insightful session, where he will walk through what’s stable, what’s experimental, and what’s next. You’ll discover specific approaches and techniques for working with Code Components.
“AI Agents for Site Builders” — by Marcus JohanssonAI-driven automation is changing the ways organizations handle content personalization, workflows, customer support, and data insights. One of the most exciting tools to emerge from the Drupal AI initiative is AI agents — autonomous systems that carry out tasks, make decisions, and pursue goals on behalf of users.
You can learn more about Drupal’s new AI Agents framework from Marcus Johansson (marcus_johansson). On his drupal.org page, Marcus describes himself simply: “I tinker with AI.” But his “tinkering” is transforming Drupal from the ground up: Marcus leads the Drupal AI initiative in Drupal, shaping its architecture, driving its development roadmap, and steering the future of AI-powered tools in Drupal.
In this session, Marcus will show you how Drupal’s Agents framework lets you create business-specific agents without writing a single line of code. Instead of slogging through implementation details, you’ll see how prompt writing and communication skills can drive the interaction, while Drupal quietly handles the complexity behind the curtain.
Join Marcus as he unpacks what agents are, how the framework was built, and how it connects with the MCP (Model Context Protocol). For experienced developers, this session is a chance to explore a tool that cuts through the noise and unlocks fresh possibilities.
“Advanced Site Building with Drupal Canvas” — by Ted BowmanDrupal Canvas is gaining serious momentum, and it deserves a closer look from more than one angle. Alongside the earlier-mentioned session on Code Components, this one is a hands-on exploration of how Canvas works hand in hand with some of Drupal’s most powerful tools.
Ted Bowman (tedbow), a long-time Drupal contributor, will show how Drupal Canvas can be combined with core features like Views and popular contributed modules to build advanced setups — all without writing a single line of code.
You’ll see an exciting demo packed with practical examples: creating dynamic landing pages, formatting structured content with Canvas templates, linking field data to SDC (Single-Directory Components) and Code Component properties, building Views inside Canvas templates, and using template slots to give editors more control.
As Canvas continues to evolve, Ted will also spotlight the latest features and contributed modules that extend its capabilities even further.
“Next Generation ECA - Vision and Progress update” — by Jürgen HaasDrupal offers many ways of workflow automation. But having tasks quietly carried out in the background — triggered by events, checked against conditions, and completed through actions — is a special kind of magic.
Experienced developers may remember the Rules module that pioneered this idea. Today, its modern successor, the Event–Condition–Action (ECA) module, takes the concept further, reimagined for Drupal’s current ecosystem. With a no-code/low-code approach and graphical modeling tools like BPMN, ECA makes building workflows more intuitive and far less intimidating.
Despite the amazing graphical interface with diagrams for ECA workflows, ECA needed to become even more approachable, especially for people without prior Drupal experience. So after solid real-world use and plenty of feedback from the community, ECA is entering its next phase. In his session, ECA’s creator, Jürgen Haas (jurgenhaas), the creator of ECA, will share how things are going with the revamp.
By lowering the barrier for site builders and project managers, the evolving ECA creates more room for developers to extend, integrate, and scale automation. The refreshed interface makes workflows easier to work with, while the underlying architecture opens fresh opportunities for custom plugins, enterprise integrations, and performance tuning.
“A Taste of the Future: Site Templates and Recipes in Drupal” — by Jim BirchDrupal has always had a knack for ambitious site building, but the Recipes Initiative is cooking up something new. Instead of distributions that lacked flexibility, we now have lightweight, composable recipes and site templates that make functionality easier to share, remix, and extend.
For experienced developers, it’s about speeding up the boring parts so you can focus on the interesting ones. Default content APIs and config actions are steadily maturing, and the community is already serving up recipes that cut down setup time while keeping flexibility intact.
Step into this session led by Jim Birch (thejimbirch), a renowned Drupal core committer and initiative coordinator. He will walk you through the progress so far, highlight examples from the community, and demonstrate practical authoring workflows. You’ll leave with a clear sense of how recipes fit into Drupal’s future, how to find and apply them effectively, and how to contribute your own to the growing ecosystem.
“Beyond Iframes: Modern Embedding in Drupal with Media and oEmbed” — by Pedro CambraEmbedding external content in Drupal has become trickier as platforms tighten security rules and content policies. If iframes keep letting you down, this session offers a cleaner, more future-proof approach.
Join Pedro Cambra (pcambra), an experienced Drupal contributor, as he shares practical guidance on embedding external content with oEmbed. He explores how Drupal uses the oEmbed standard together with core Media tools and contributed modules like oEmbed Providers to embed third-party content safely and reliably. You’ll get a clear look at how oEmbed works behind the scenes, which modules fit best for different use cases, and how CKEditor handles embedded objects.
The session also touches on enhancing embeds with authentication or privacy controls and building your own oEmbed resources for custom content. Practical examples keep things grounded, with plenty of tips you can apply right away. If you’ve ever wrestled with embeds or want a more robust setup that plays nicely with modern platforms, this session is well worth your time.
“Future Proof Theming: Best Practices for Drupal’s New Era” — by Mike Herchel and Andy BlumTheming in Drupal is entering a new era, and this training is designed to keep even seasoned developers ahead of the curve. It will be led by Mike Herchel (mherchel) and Andy Blum (andy-blum), key contributors driving theming innovations in Drupal. The training session dives into Single Directory Components, Drupal Canvas, and modern CSS/JS techniques that will shape how we build themes going forward.
Through hands‑on exercises, you’ll learn to craft reusable components, streamline workflows with Storybook, and deliver designs that are fast, accessible, and maintainable.
You’ll pick up strategies to dodge common page‑builder pitfalls and keep your themes flexible for whatever comes next. If you’re ready to sharpen your skills and future‑proof your toolkit, this training belongs on your schedule. It must be noted that training sessions require an additional ticket.
Driesnote — by Dries BuytaertEvery DrupalCon has its traditions, and the Driesnote is one of the most anticipated. For developers who spend their days building and maintaining Drupal sites, the Driesnote is a chance to catch a glimpse of what’s emerging in the platform.
Beyond the usual updates, it’s the place to hear the newest features, initiatives, and announcements that set the stage for what’s coming next for Drupal. You’ll discover new tools, architectural changes, and exciting directions for core and contributed projects, all straight from Dries Buytaert. Right in the main auditorium, you’ll catch demos that haven’t been shown anywhere else yet.
This session is Drupal’s roadmap in real time. Experienced developers will walk away with inspiration for their own projects, and an insider’s view of upcoming improvements that could change how we work with the platform.
Final thoughtsWrapping up the developer sessions at DrupalCon Chicago, the vibe is clear: Drupal keeps giving us new tools, and it’s up to us to explore them, stress-test them, and help shape what comes next. Canvas, ECA V2, Recipes, Site Templates, and other cool innovations are all evolving fast, and the fun part is digging into the details to see how they really work.
For experienced developers, the focus shifts away from shiny demos to spotting patterns, catching edge cases, and laughing when the “easy” stuff turns into a rabbit hole. These sessions are a reminder that Drupal’s future is being built in real time — and that we still get to shape it through commits, patches, and the occasional late-night debugging marathon.
Authored By: Nadiia Nykolaichuk, DrupalCon Chicago 2026 Marketing & Outreach Committee Member
Today we are talking about Mautic, marketing automation, and its history with Drupal with guest Ruth Cheesley. We'll also cover Mautic ECA as our module of the week.
For show notes visit: https://www.talkingDrupal.com/541
TopicsRuth Cheesley - ruthcheesley.co.uk RCheesley
HostsNic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Catherine Tsiboukas - mindcraftgroup.com bletch
MOTW CorrespondentMartin Anderson-Clutz - mandclu.com mandclu
Every technology cycle has its buzzwords. This one has AI stamped on every roadmap, budget request, and vendor pitch deck. As Nitish Chopra argues, the rush to “integrate AI” into content management systems feels less like strategy and more like panic. Organizations are bolting large language models onto legacy stacks without confronting a harder truth: most digital architectures were never designed to support structured, machine-readable intelligence.
The pattern is becoming predictable across the CMS landscape. Some teams chase quick wins through plugin overload and surface-level integrations. Others pay enterprise premiums for repackaged APIs marketed as innovation. A third group disappears into technical rabbit holes, overengineering AI experiments that never survive contact with production realities. In each case, the failure is architectural. AI is treated as a feature to be installed, not a capability that depends on disciplined data modeling, governance, and system design.
This is where the Drupal ecosystem enters the conversation. For years, Drupal’s insistence on entities, fields, taxonomies, and structured content was criticized as overly complex. Yet those very foundations align with what AI systems require: clean schemas, reusable content objects, and predictable relationships. What once felt rigid now looks intentional. What was labeled pedantic now resembles preparation.
For Drupal builders, agencies, and enterprise stakeholders, the question is not whether to integrate AI, but how to do so without abandoning architectural discipline. AI success in Drupal will not come from chasing wrappers around APIs or cosmetic chatbot add-ons. It will come from doubling down on structured content architecture, refining data governance, and designing composable systems that can support automation at scale. In that sense, the ecosystem’s competitive advantage is not novelty. It is discipline.
This week’s edition reflects on that tension between momentum and method before turning to the stories shaping the ecosystem.
With that, let's shift the spotlight to the important stories from last week.
INTERVIEWDISCOVER DRUPALWe acknowledge that there are more stories to share. However, due to selection constraints, we must pause further exploration for now. To get timely updates, follow us on LinkedIn, Twitter, Bluesky, and Facebook. You can also join us on Drupal Slack at #thedroptimes.
Thank you.
Alka Elizabeth
Sub-editor
The DropTimes
Introduction
There is a subtle bait-and-switch here: I am going to talk about my experience coding with AI in Python, but the lessons learned apply to Drupal and the broader challenges developers face when coding with AI.
Over the past few months, AIs have begun to understand and write code for Drupal, and I want to understand how AI can help me with my Drupal projects. I would be the first to say “Vibe Coding” sounds like something invented in a hipster cafe, but it is here to stay, just like the Frappuccino.
As a Drupal Developer who has written a lot of PHP code over the years, I welcome the opportunity to write less and think more. Call me old-fashioned, but I am a self-taught developer who learned by reading books, even though AI moves so fast that books on the topic are out of date within a year. I decided to look for a book to help with this journey.
A search for “Coding Drupal with AI” yields very few results, yet it is notable that a post titled “Claude Code meets Drupal” by Dries Buytaert, the creator of Drupal, appears on the first screen of results. Sometimes, when learning something new or facing a new challenge, I like to work around the challenge.
For example, when I first started learning Drupal 8 as an experienced Drupal 6/7 developer, I was stumped by Symfony and the OOP patterns being introduced into Drupal, so I spent a few weeks building a Symfony application and then dove deep into Drupal 8. So I decided to approach AI coding in Python because it is a popular programming language that I was curious to learn. I chose to read Coding with AI: Examples in Python by Jeremy Morgan because it focuses first on AI and secondarily on using Python.
My...Read More