Earlier this week, in "Drupal's role in agentic workflows", I argued that Drupal's AI future has two parts: helping people with AI inside Drupal, and helping agents use Drupal from the outside.

So we are splitting Drupal's AI strategy into two workstreams. Inside AI is led by Christoph Breidert, who has been driving that work already. Outside AI, the new workstream, is led by Scott Falconer.

The easiest way to think about the difference: with Inside AI, a person uses Drupal, and Drupal uses AI to help. With Outside AI, a person uses an agent, and the agent uses Drupal.

We launched the Drupal AI Initiative one year ago, in June 2025, with a published strategy. A year later it spans 32 organizations and more than 50 contributors, shipping against a public 2026 roadmap through two paid delivery teams.

So far, most of that work has focused on Inside AI, though much of the foundation also supports Outside AI.

Outside AI will serve three kinds of users:

• Developers new to Drupal. They ask an AI agent to build a website, and the agent chooses what to build on. Agents reach for whatever they can spin up in seconds, so the opportunity is to make Drupal that easy to install, configure, and use.
• Experienced Drupal developers. They already know Drupal is the right tool, and they want agents to take on more of the work. For Drupal agencies, Outside AI should turn AI into a stronger advantage: helping teams move faster, win more work, protect profitability, and get more value from their Drupal talent.
• External agentic systems and workflow automation tools. These systems coordinate work across many tools, but when they touch content, they need a trusted system of record for workflows, permissions, revisions, and publishing. Rather than rebuilding that governance elsewhere, they should call into Drupal.

If we are successful, agents will recommend Drupal to new users, help Drupal developers move faster, help agencies win more work, and use Drupal as the trusted layer for content management and governance.

Thank you to everyone who helped bring the Drupal AI Initiative to this point. Together, the community has turned an ambitious idea into real momentum.

I'm excited about what comes next! Want to get involved? Join the #ai-initiative channel on Drupal Slack.

By the Drupal AI Initiative

A year ago, we launched the Drupal AI Initiative with a published strategy and a bet that AI would matter enormously to Drupal's future. Today the initiative spans 32 organizations and more than 50 contributors, shipping against a public 2026 roadmap.

As the work has grown, it's become clear that our AI strategy needs to cover two distinct areas. While innovation and product development remain core goals across everything we do, we are organizing our day-to-day execution into two workstreams: Inside AI, led by Christoph Breidert, and Outside AI, a new stream led by Scott Falconer. 

The unified AI initiative leadership team - made up of the existing initiative members - will continue to shape our overarching roadmap, while Christoph and Scott ensure that vision is executed. We will outline this leadership team and other key supporting roles in an upcoming post.

The core difference: Inside AI brings AI tools into the Drupal interface to assist the people using it. Outside AI makes Drupal the platform external AI agents reach for and act on.

Inside AI

Inside AI is AI inside Drupal, for the people using it: assistants, in-product workflows, page-building, and the rest of the user-facing surface. This is the work the initiative has been driving for the past year, and it continues against the 2026 roadmap already in flight.

Outside AI

Outside AI is AI outside Drupal, acting on Drupal. A person, agency, host, or developer is using an external agent or builder tool, and that agent needs to start with Drupal, connect to Drupal, inspect Drupal, change Drupal, verify Drupal, migrate into Drupal, or launch Drupal. 

What's next

You'll see public roadmaps from both streams. Inside AI continues against its existing 2026 roadmap; Outside AI will publish its own outcomes and milestones, with a first proof of direction targeted for DrupalCon Rotterdam. Where both streams need the same capability, the answer is usually one shared Drupal contribution, not two parallel builds.

Get involved

The initiative is open, and both streams need contributors  -  whether you write code, test against real agent workflows, work on documentation, or bring a use case from your own agency or organization.

• Read the strategy and the public 2026 roadmap to see where each stream is headed.
• Collaborate with our partners to deliver the latest AI features to your users.
• Become an AI Partner.
• Join the conversation in the #ai-initiative channel on Drupal Slack.
• Check the issue queues for Inside AI and Outside AI work, and pick something up.

Not sure where to start? Come say hello in Slack and we'll help you find a first contribution.
 

For Drupal teams, small technical choices often decide how maintainable a site becomes. DrupalCamp Kortrijk speakers are using that practical layer as the entry point for sessions on configuration, performance, CSS and editorial work.

Three Players, One Direction: ECA, FlowDrop, and Maestro Jürgen Haas Thu 25 Jun 2026 - 13:00

ECA, FlowDrop, and Maestro all draw boxes and connect them with arrows, so people keep asking whether three Drupal workflow modules means a split community. Not quite. Dries Buytaert, Randy Kolenko, Shibin Das, and I are writing a shared orchestration design spec, disagreeing productively in writing. One axis explains all three: how much state a run carries. ECA reacts statelessly to any Drupal event across the whole request surface. Maestro holds a durable process that can wait days for human approval. FlowDrop spans the axis with a typed, inspectable dataflow graph that runs sync, async, or stateful from one definition, and Shibin is refining it toward strictly serializable data, ideal for building complex AI agents. Nothing is frozen. The word "orchestration" itself is contested in the spec glossary. Composition already ships: maestro_eca_task lets a Maestro process hand off to ECA. The bigger vision, ECA reacting to content, calling a FlowDrop AI flow, then routing through Maestro for human approval, is a picture we are building toward, not a release. But bridges are the start, not the finish. The real work is building a shared foundation, common primitives and APIs so the three tools stop reinventing the same concepts under different names. The spec's vocabulary synthesis shows the embarrassing similarity: Trigger, Step, Condition, Workflow, Run. The keystone is a defined contract for handing data between steps and between tools, one that works beyond Drupal's border for AI agents and external systems. Three tools is the right number because the stateless-reactive and instance-stateful ends pull architectures in opposite directions. Specialization beats a mediocre merger.

Take Away

At 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, Dénes Szabó (Drupal Developer) built LinkStash, a production-ready Drupal 11 bookmarking module, in one weekend using Claude Sonnet 4.5.

The Browser Tab Apocalypse

You know the feeling. It's Tuesday afternoon, you have 47 browser tabs open across three different browsers, and somewhere in that digital haystack is that one article you absolutely need to reference. Chrome has the documentation you bookmarked last week. Firefox has the GitHub issues you were reviewing. Safari has... honestly, you can't remember what Safari has anymore. Your browser's "Reading List" feature is laughing at you. Your bookmarks folder looks like a digital hoarder's attic. And don't even get started on those "bookmark this page to read later" services that require uploading all your data to someone else's server.

As a Drupal developer, I looked at this chaos and thought: "I could fix this. I have the technology. I have the skills. I have... absolutely no time to actually build it because I'm too busy managing 47 browser tabs."

So naturally, I decided to see if AI could help me build it in a weekend instead.

The Experiment: Can AI Build a Real Drupal Module?

The goal was ambitious but clear: build LinkStash, a personal bookmarking tool, as a production-ready Drupal 11 contrib module suitable for release on drupal.org. Not a prototype. Not a proof-of-concept. A real, tested, documented, standards-compliant module that follows all of Drupal's best practices and passes the strict quality requirements for the official repository.

The feature list was substantial: entity system with full CRUD operations, browser bookmarklet for one-click saving, automatic metadata fetching with SSRF protection, smart domain-based auto-categorization, video embed support for YouTube and Facebook, Views integration with filters, 100% PHPCS compliance, PHPStan Level 1 static analysis, and a full test suite. Oh, and proper documentation including README, CHANGELOG, and API docs.

You know, just a light weekend project. What could possibly go wrong?

Why Claude Sonnet 4.5, Not Opus?

Here's where it gets interesting. Everyone assumes you need the biggest, most powerful AI model for serious development work. But I deliberately chose Claude Sonnet 4.5 instead of Opus, and here's why: it's way cheaper, significantly faster, and (here's the kicker) equally clever for code generation.

For structured development tasks with clear requirements, Sonnet 4.5 absolutely shines. It understands Drupal architecture, follows coding standards precisely, writes comprehensive tests, and generates production-quality code. The speed difference is noticeable: responses come back in seconds instead of tens of seconds. When you're iterating on test failures or fixing PHPCS violations, that speed compounds into serious time savings.

The cost difference? Even more dramatic. We're talking roughly one-fifth the cost per token. Over the course of building LinkStash, which consumed an estimated 200-250K tokens across multiple development sessions, Sonnet 4.5 probably cost around $3-$5 total.

That's less than a fancy coffee, for a complete, production-ready Drupal module. Let that sink in.

The Human-AI Collaboration: How We Actually Built It

AI didn't build this module alone. This was a collaboration, and understanding the dynamics matters.

What AI did (the heavy lifting):

• Generated all entity boilerplate following Drupal 11 patterns
• Implemented three complete plugin systems (ContentFetcher, CategoryRule, MediaProvider)
• Wrote 187 tests (132 unit + 55 kernel) with proper fixtures and mocks
• Wrote the documentation (README, CHANGELOG, API docs)
• Fixed all PHPCS and PHPStan violations autonomously
• Debugged test failures systematically (13 failures across 3 test suites, all resolved)
• Generated field configurations, Views configs, and taxonomy vocabularies

What I did (the professional supervision):

• Created the Product Requirements Document with the 3-phase roadmap
• Made all architectural decisions (entity structure, plugin patterns, security model)
• Decided on module naming (checked drupal.org availability, chose "LinkStash")
• Identified critical security requirements (SSRF protection, XSS prevention)
• Reviewed and corrected AI assumptions when they didn't match Drupal realities
• Ran the actual tests in DDEV (AI can't access Docker environments)
• Caught edge cases AI missed (like the DNS rebinding vulnerability in SSRF protection)
• Made final calls on trade-offs (documented limitations vs. complex solutions)

When I Had to Intervene: The Learning Moments

The most surprising part wasn't what went smoothly; it was where AI stumbled and needed human expertise.

The constant mystery. AI kept trying to use EntityStorageInterface::SAVED_NEW, but that constant doesn't live in that interface. It's a global constant in core/includes/common.inc. I had to explicitly correct this: "This constant does not exist in this interface. It's defined in common.inc. Fix it." The AI course-corrected immediately.

The access control saga. All seven access tests were failing despite correct permissions and entity ownership. AI tried using AccessResult::allowedIf(), which should work, but didn't in Drupal 11's kernel test environment. After systematic debugging, I suggested trying explicit conditionals instead. That fixed it instantly; it was a behavioral quirk AI wouldn't have discovered alone.

The vocabulary ID confusion. Tests were creating a tags vocabulary, but the actual config created linkstash_tags. AI confidently wrote tests that failed due to this mismatch. Human pattern recognition caught it: "You're testing against the wrong vocabulary ID."

The YouTube ID format. AI used 3-character test IDs (abc, xyz), but YouTube video IDs are exactly 11 characters using base64url encoding. The regex pattern [a-zA-Z0-9_-]{11} doesn't lie. Once I pointed out that YouTube IDs are standardized at 11 characters, AI immediately generated valid test data.

These weren't AI failures; they were collaboration points. AI had the speed to generate code and tests. I had the domain expertise to catch subtle Drupal-specific issues. Together, we debugged faster than either of us could alone.

The Development Speed

The numbers are worth a look:

• Calendar time: Friday/Saturday to Sunday (February 7-9, 2026)
• My active time: 10-20 hours of supervision, decision-making, and testing
• AI sessions: Multiple sessions totaling ~200-250K tokens
• Code generated: 8,000+ lines across entity classes, plugins, services, tests, and configs
• Test suite: 187 tests written and debugged to 100% pass rate
• Documentation: 1,800+ lines (README, CHANGELOG, module intro HTML)

Here's what "one weekend" actually delivered:

• Complete entity system with 12 fields
• Three working plugin systems with 8 plugin implementations
• Browser bookmarklet with popup fallback logic
• Automatic metadata fetching with SSRF protection
• Smart auto-categorization based on 5 domain-matching rules
• YouTube and oEmbed video embed support
• Two Views (list + detail) with exposed filters
• 187 tests (100% passing, ~85% code coverage)
• Zero PHPCS violations, PHPStan Level 1 clean
• Complete documentation ready for drupal.org submission

The security model deserves a callout: SSRF protection blocks private IP ranges, local thumbnail storage prevents IP leaking, and all data is isolated per user. All three plugin systems are also fully extensible, other developers can add custom content fetchers, categorization rules, and media providers. The module ships with sensible defaults but is built for extension.

Could I have built this solo in a weekend without AI? Absolutely not. The test suite alone would have taken days. Could AI have built this without supervision? Also no. Those subtle Drupal-specific issues required experienced judgment calls.

But together? We shipped a release-ready beta in 48 hours.

The Numbers: What Did This Actually Cost?

Let's break down the economics.

Time investment:

• Human time: ~15 hours (let's split the 10-20 range)
• AI compute time: Maybe 30-45 minutes total across all sessions
• Calendar time: One weekend

Token usage:

• Estimated total: 200-250K tokens (spanning multiple sessions)
• Breakdown by task (from progress.md):
  • Project setup: ~10K tokens
  • Entity/field architecture: ~14K tokens
  • Major features (8-10): ~15K tokens each
  • Test suite (187 tests): ~30K tokens
  • Code review + fixes: ~15K tokens
  • Documentation: ~20K tokens

Actual costs (Claude Sonnet 4.5 pricing):

• Input tokens: ~$3 per million tokens
• Output tokens: ~$15 per million tokens
• Rough estimate: $3-$5 total for the entire project

Traditional development cost (rough estimate):

• Senior Drupal developer: $100-$150/hour
• Time required (solo): 40-60 hours (conservative)
• Traditional cost: $4,000-$9,000

The AI-assisted approach wasn't just faster; it was two to three orders of magnitude cheaper while maintaining professional quality standards.

The Future: Where Do We Go From Here?

Building v1 in a weekend was exhilarating, but it's just the beginning. The roadmap has two more phases.

Phase v2 (enhanced features):

• Browser extension for Chrome/Firefox (deeper integration than a bookmarklet)
• Import/export (JSON, CSV, HTML bookmark files)
• Link health checking (detect broken links via cron)
• Duplicate detection and merging
• Collections system (folders, boards, groups)
• Full-text content archival (Wayback Machine style)

Phase v3 (advanced capabilities):

• AI-powered auto-tagging using actual page content (not just domain matching)
• Smart recommendations based on browsing patterns
• Multi-site synchronization for users with multiple Drupal sites
• Drupal Recipe for one-click installation
• Social features (public collections, sharing)

The best part? Now that the architecture is solid and the plugin systems are proven, adding these features becomes incremental. Each new feature is just another plugin implementation or service extension. The hard architectural work is done.

Was It Fun? (Spoiler: Yes, Incredibly)

Nobody warns you that AI-assisted development is fun.

There's something magical about describing what you want, for example, "Now we need a plugin system for content fetchers that can pull metadata from any URL with SSRF protection," and watching structured, working code appear in seconds. Then catching a subtle bug, pointing it out, and watching the immediate course correction. It feels less like programming and more like conducting. You're directing the architecture and reviewing the output, not typing every curly brace.

The debugging sessions were particularly entertaining. When all seven access tests failed, AI and I became detective partners:

Me: "Add debug assertions before the access check. Let's see if the user actually has permissions."

AI: Adds assertions. "Okay, permissions confirmed. User owns the entity too."

Me: "So why is AccessResult::allowedIf() not working?"

AI: "Let me try explicit conditionals instead..."

Me: "That... actually fixed all seven tests. Interesting."

That back-and-forth, that collaborative debugging energy, reminded me of pair programming with a really fast typist who never gets tired but occasionally needs you to remember obscure Drupal API behaviors.

The satisfaction of running ddev composer run-tests and seeing "187 tests, 846 assertions, OK" flash green? That hit the same way shipping your first module to production does. Except this time, we'd done it in a weekend instead of a month.

The Real Lesson: Augmentation, Not Replacement

If there's one takeaway from this experiment, it's this: AI is an amplifier, not a replacement.

I couldn't have built LinkStash in a weekend alone. But AI couldn't have built it without me either, not to production quality, not with proper security considerations, not with the architectural decisions that make it extensible and maintainable.

What AI gave me was force multiplication. Instead of typing boilerplate entity code, I specified requirements and reviewed output. Instead of writing 187 tests manually, I described what needed testing and verified the results. Instead of formatting documentation, I outlined structure and AI filled in details.

I stayed in the driver's seat for architecture, security, and critical decisions. AI handled the mechanical work of code generation, test writing, and standards compliance. Together, we shipped something neither of us could have done alone in the same timeframe.

And honestly? For a problem that's been in the back of my mind for months, "I really need a better bookmarking solution," going from idea to a release-ready beta in one weekend feels like the future.

Now if you'll excuse me, I need to actually use LinkStash to bookmark all the tabs I've accumulated while writing this blog post. The irony is not lost on me.

LinkStash is available at drupal.org/project/linkstash. Built with Claude Sonnet 4.5 via Claude Code. Source code, documentation, and contribution guidelines are available in the project repository.

Development metrics: 1 weekend, ~15 human hours, ~240K AI tokens, $3-5 compute cost, 8,000+ lines of code, 187 tests, 0 PHPCS violations, live on drupal.org.

If you're weighing whether AI can carry real weight on your next Drupal contrib module, or you want to talk through where human oversight still has to stay in the loop, let's start a conversation! We'd love to hear from you.

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're still figuring out, so that together, we can build a more practical, responsible path for AI adoption.

Image by Mahmoud Ramadan from pexels

When Paragraphs-based content models grow deep, Drupal teams can inherit slower rendering, heavier databases, and harder migrations. Custom Field maintainer Andy Marquis explains where field-based structured data offers a leaner alternative, and where Paragraphs still belongs.

Critical security vulnerabilities don't wait for a convenient time. They arrive on their own schedule, and how quickly your team responds can mean the difference between a routine update and a serious exposure.

A highly critical advisory with a 48-hour window

On May 18, the Drupal Security Team issued PSA-2026-05-18, a pre-announcement for a highly critical security release affecting every supported branch of Drupal core. The advisory scored a 20 out of 25 on the security risk scale. No authentication required, no special access needed. The release window was two days later, on May 20, between 17:00 and 21:00 UTC.

The Drupal Security Team urged site owners to reserve time for immediate updates because exploits could be developed within hours or days. They took the unusual step of providing best-effort patch files even for end-of-life versions of Drupal 8 and 9 because the potential impact was that significant.

If you're running a site that processes orders and manages customer data, you can’t put something like this off until the next sprint.

Coordinating across every client

When the pre-announcement landed, we reached out to all of our support clients and worked directly with their teams to determine priority, assess whether the vulnerability applied to each site's specific configuration, and plan accordingly.

Read more

Drupal Metatag Module Basics for Content Editors Joel Steidl Tue, 06/23/2026 - 14:38 Drupal

Helping your website content be found, shared, and understood clearly and responsibly.

When you publish website content, the work does not stop at the page itself. Search engines, social platforms, and browsers all rely on behind-the-scenes information to understand what your content is about and how it should appear to people looking for it.

In Drupal, the Metatag module gives content editors a way to shape that understanding. You do not need to be a developer to use it effectively as part of your day-to-day content work. Editing and reviewing metatags is generally straightforward for content editors.

Installing the module and establishing site-wide defaults typically requires a developer or someone with Drupal experience. Tasks such as adding the module, enabling it, and defining default values are usually handled during site setup. Once that foundation is in place, content editors can focus on the quality and context of their content rather than technical implementation details.

This article explains the most common Metatag settings you will encounter, what they do, and when they matter.

What the Metatag Module Does

The Metatag module lets you manage information about your content that is not visible on the page itself, but is visible to:

• Search engines such as Google and Bing
• Social media platforms such as Facebook, LinkedIn, and X
• Web browsers and assistive technologies

You can think of metatags as context. They help external systems understand your content and present it accurately to people who depend on those systems to find trustworthy information.

Metatags on Content Edit Screens

As a Drupal content editor, the metatag fields you will work with most often appear directly on the content editing screen alongside the rest of the page fields.

You will typically see them:

• On content edit screens for pages, articles, events, and similar content types
• Grouped under a Metatag or SEO section

Many of these fields are pre-populated using defaults established during site configuration.

These fields control how a specific piece of content appears in search results and social shares. You will not need to adjust them for every page. Understanding what they do helps you make informed decisions for high-visibility content, time-sensitive information, or pages likely to be shared widely.

Metatag Configuration

You may also hear references to "Metatag settings" or "Metatag configuration." These live in the Metatag module's administrative settings rather than on individual content pages.

This configuration is used to:

• Define site-wide defaults for titles, descriptions, and social previews
• Control which metatag fields appear for different content types
• Set fallback values when editors leave fields blank

Because these settings affect the entire site, they are typically managed by developers or site administrators. Content editors generally do not need to interact with this area as part of their regular workflow.

Understanding this distinction helps establish clear ownership: developers maintain the framework, while editors focus on content quality and accuracy.

Core Metatags You'll Use Most OftenPage TitleWhat it is

The page title appears in browser tabs and is often used as the main headline in search results.

Why it matters

This is one of the clearest signals search engines use to understand what a page is about. It is also the first thing many people see when deciding whether to click.

Best practices

• Keep it clear and specific
• Put the most important words first
• Aim for roughly 50 to 60 characters

Example

Summer Programs for Kids | City of Example

Meta DescriptionWhat it is

A short summary that often appears below the page title in search results.

Why it matters

While it does not directly affect rankings, it helps people decide whether a page is relevant to them.

Best practices

• Write in plain language
• Be accurate and inviting
• Aim for roughly 150 to 160 characters

Example

Explore fun and educational summer programs for children ages 5–12. Registration now open.

Canonical URLWhat it is

The canonical URL tells search engines which version of a page should be treated as the primary one.

Why it matters

This helps search engines identify the authoritative version of content when similar or duplicate pages exist.

For editors

In most cases, this is handled automatically. You usually will not need to change it.

Robots (Index / Follow)What it is

Instructions that tell search engines whether they should:

• Include the page in search results (index)
• Follow links on the page (follow)

Common settings

• Index, Follow: Appropriate for most public-facing pages
• No Index: Used for pages that should not appear in search results

Why it matters

These settings help ensure that search engines surface the right content while excluding pages that may be temporary, incomplete, or intended for limited audiences. Used thoughtfully, they support clarity, trust, and consistency across the site.

When "No Index" is appropriate

• Temporary or time-limited pages
• Confirmation or thank-you pages
• Internal-only content

Social Sharing Metatags

These settings control how your content appears when it is shared on social media. Clear, accurate previews help people quickly understand what they are being asked to read or click.

Open Graph (Facebook, LinkedIn, and Others)Open Graph TitleWhat it is

The headline shown in social previews when the page is shared on social platforms.

Helpful tip

This does not have to match the page title exactly. You can use more conversational language if it helps provide useful context.

Open Graph DescriptionWhat it is

A short summary shown beneath the title in social previews.

Helpful tip

Focus on clarity and relevance. This text helps people decide whether the content is useful to them.

Open Graph ImageWhat it is

The image displayed alongside the title and description in social feeds.

Why it matters

A clear, relevant image helps your content stand out and be understood at a glance.

Best practices

• Choose an image that reflects the content honestly
• Use high-quality images without small or difficult-to-read text
• Avoid images that feel generic or misleading

Advanced Metatags

You may notice additional fields that are rarely needed on a page-by-page basis. These metatags are typically managed at the site level rather than by individual content editors.

In most Drupal sites, advanced metatags are:

• Configured centrally in the Metatag module settings
• Applied automatically using site-wide defaults
• Maintained by developers or site builders as part of the site's overall configuration

This approach promotes consistency across the site while reducing the risk of configuration drift and unintended changes.

As a content editor, you generally do not need to edit these fields. They are managed for you so you can focus on creating and maintaining clear, useful content.

Keywords

Modern search engines largely ignore this field. You can usually leave it empty unless your organization has a specific reason to use it.

Content Language

The Content Language metatag communicates the language of the page to search engines, browsers, and assistive technologies.

This is usually set automatically based on the site's configuration. During site setup, a developer or site builder defines the site's default language and any additional supported languages in Drupal's language settings.

Drupal applies the appropriate language metadata to each page based on:

• The site's primary language
• Whether the site supports multiple languages
• How a specific piece of content is configured or translated

You typically do not need to manage this field directly. It is handled automatically to help ensure content is interpreted and presented correctly across devices, platforms, and accessibility tools.

Site Verification, Geo Tags, and Custom Tags

These fields are often used for:

• Search engine verification
• Analytics and monitoring tools
• Organization-wide integrations

They are usually managed globally rather than by individual editors.

Want to Go Deeper?

For teams responsible for Drupal configuration, governance, or ongoing platform maintenance, the following resources provide additional detail:

Drupal Metatag module documentation (Drupal.org)

Official documentation covering available metatag types, defaults, and configuration options:

https://www.drupal.org/docs/contributed-modules/metatag

Working with images in metatag fields

A helpful explanation of how metatag image fields work with Drupal Media and tokens:

https://mark.ie/blog/adding-tokens-for-metatag-image-fields-when-using-drupal-media-entity

These resources are most useful for developers and site builders, but they can also provide helpful context for editors interested in understanding how content is presented across platforms.

Key Takeaways

Most Drupal sites provide sensible metatag defaults, which means editors rarely need to complete every field. Even so, it is worth reviewing metatags for key landing pages, high-traffic content, major announcements, and pages that are likely to be shared externally.

Before publishing, take a moment to confirm that:

• The page title clearly reflects the content.
• The meta description accurately summarizes the page.
• Social sharing previews make sense when viewed outside the context of the website.
• The page is intended to appear in search results.

Metatags are not a substitute for clear content, good information architecture, or strong governance. They are supporting metadata that helps search engines, social platforms, browsers, and assistive technologies interpret content consistently. When paired with well-structured content and thoughtful editorial practices, they help ensure information is represented accurately wherever people encounter it.

Jon Bowman

Freedom is Not Free: A Model for Open Source Sustainability demet Tue, 06/23/2026 - 11:49

How to align public policy and procurement to support the costs of our shared digital infrastructure

The modern world runs on open source software—trillions in economic value, and growing more essential to digital sovereignty by the day. Yet, beneath this foundation, the projects producing it are starved of capital. Open source simply does not have the structural resources it needs to be sustainable. The code is free, but the human and technical infrastructure required to maintain it is not.

A project like Drupal is no longer just a code repository; it is a full-scale utility provider. We deliver supply chain security, product management, and continuous integration pipelines. Our licenses waive all warranties and responsibilities—and yet enterprise scale demands we provide these services anyway, because no one else will. The core failure of our current model is that open-source funding is completely disconnected from these operational cost centers.

Because we lack a built-in mechanism to capture the value open source creates, we have accidentally engineered an extractive system. The Takers who consume open source without paying their fair share of its operational footprint are not acting out of malice; they are simply doing exactly what the market currently incentivizes them to do.

It is not inevitable that open source must be extractive. That is an architectural choice. To change the outcome, we must change the incentives. Using regenerative system design, we must re-engineer open-source models to capture enough resources from our outputs to continuously sustain our inputs. We must ensure that supporting open source the right way becomes both the easy way and the expected way.

Right now, supporting open source the right way is almost impossible for our largest users. Public procurement systems are designed to buy structured services from single vendors. They cannot write open-ended checks to decentralized communities. To bypass this "charity trap," we must transition to an operational cost framework and move the operating costs of open source off the donation sheet and directly into core operating budgets as a predictable, line-item consumption expense.

To make the easy way possible, open source foundations must clearly quantify and communicate our true technical and human costs. In Drupal, we know part of it. We provide $10 per site per year in consumable technical infrastructure, but our revenues only fund $7.50. The remaining $2.50 is pushed off as technical debt to the future. That gap says nothing about the release managers and security teams whose essential work is still mostly donated—that burden sits entirely outside this number. We must turn these technical and human maintenance costs into a transparent, billable utility, giving institutions a clear, legally compliant way to pay for what they consume.

But once we make it easy to pay for this utility, how do we make it the expected way?

That requires establishing two clear standards.

For the vendor ecosystem, we need a sustainable participation standard. In Drupal, we have a contribution credit system to visibly recognize our Makers, those who invest real capital, code, and labor into the project. This system also helps us to identify the Fakers, organizations that use sponsorship and marketing to signal commitment while funding and doing little-to-none of the actual work.

For public institutions and enterprise users, we need a sustainable use standard defined by three practices:

• One, select vendors who sustainably participate in the projects they use.
• Two, include an explicit open source maintenance line item in every contract—a cost-recovery expense that shifts the burden off pro-bono maintainers.
• Three, require timely upstream release of all non-sensitive bug fixes and features.

With these standards in place, Open Source Program Offices can work with procurement officers to differentiate the true Makers from the Takers and Fakers at the point of purchase. And, the market-making power of public purchasing operationalizes "Public Money, Public Code" into the norm.

Open source cannot thrive on the margins of volunteerism, but it doesn’t have to. Once public policy acknowledges open source maintenance as an operational cost rather than a charitable act, everything else follows. That's regenerative system design in practice: change the incentives, and the system begins to fund itself.

Adapted from a June 23, 2026 presentation by Tiffany Farriss at the Sovereign Tech Agency's Breakfast Reception during United Nations Open Source Week.  Photo by Mike Gifford, licensed under CC BY-SA 4.0.
 

When we started working on the Drupal AI initiative in June 2025, I assumed most AI features would live inside Drupal.

By my DrupalCon Chicago keynote in March 2026, my thinking had changed. I framed the shift as "inside-out" versus "outside-in" and concluded that not every AI capability belongs inside Drupal. Some work is better done outside the CMS, where AI tools can move faster and connect back to Drupal when needed.

Last week, I explored these ideas in more detail in "AI and the great CMS unbundling". That post argued AI is making the CMS less central as a creation tool, but more important as a control layer: the place where content is structured, governed, reused, and published with trust.

This post picks up from there. If Drupal's role as the control layer is becoming more important, it needs to support AI-driven workflows that run inside Drupal, start outside Drupal, and move across both: external workflows that call into Drupal, and Drupal-native workflows that outside systems can safely rely on.

Drupal joins workflows beyond the CMS

First, Drupal needs to work well with tools outside the CMS: coding agents like Claude Code and Cursor, and orchestration platforms like Salesforce Agentforce, n8n, and Activepieces.

I actually showed what this could look like in my DrupalCon Vienna keynote in October 2025. Here is a short clip of that:

It was a proof of concept demo, and we had some fun with it. But the pattern behind the demo mattered more than the demo itself: an external tool drove the work and handed tasks to Drupal, while Drupal returned structured content and state.

Watch the demo, and it will be easy to imagine the same pattern in a real marketing use case. Campaigns usually begin with a marketing brief and span many tools and channels: email, website landing pages, social media, paid media, and more.

An external agentic platform could generate campaign copy and ask Drupal to build a landing page. Drupal could map the copy to the right structured content type, place it into approved components with Drupal Canvas, save a draft, and flag any fields, metadata, or translations still missing before it can publish.

If Drupal reports a missing hero image, the agentic platform could search the digital asset management system (DAM), find an approved campaign image, and hand it back. Drupal could then attach it through its media model, supply or verify the required alt-text, confirm the page meets its requirements, and advance the draft through the editorial workflow.

This is a pattern that Drupal will need to support well. External platforms can coordinate work across the broader digital stack, but Drupal should remain the system that assembles, validates, governs, and publishes the content.

External workflows call Drupal-native workflows

While the larger campaign workflow may live outside Drupal, there is an equally important case for Drupal-native workflows.

External agents are good at coordinating work across systems. But once a workflow needs to act on Drupal content or data, it should use Drupal's native content model, permissions, validation rules, moderation states, revisions, and publishing workflows rather than recreate them outside of Drupal.

That is where projects like ECA, FlowDrop, and Maestro become more important. They let Drupal turn site-specific processes into repeatable, multi-step workflows that outside systems can call.

For example, any of these three systems could power a single Drupal workflow that validates a draft, coordinates translations in five languages, assigns reviewers, and publishes the content only after all required approvals are complete.

Depending on the task, these internal Drupal workflows can be deterministic, AI-assisted, or fully agentic. Drupal can support that today.

An external agent should not have to manipulate Drupal from the outside, field by field or function by function. It should be able to ask Drupal to execute a Drupal-native workflow through a single external API call.

That is the other half of what I showed in the demo video above. Drupal was not just exposing content to an external agent. It was exposing custom Drupal-native ECA workflows that an external automation tool called.

That was powerful last fall at DrupalCon Vienna, but as agentic workflows become more common, this pattern will only grow in importance.

The best end-to-end experience will win

There is a natural tendency to debate what should live where. Should AI happen inside Drupal, or outside of it? Should workflows be Drupal-native, or managed by external platforms?

Those are useful questions, but the answer is not universal. AI and workflows should live where they create the best end-to-end experience. Sometimes that will be inside Drupal, sometimes outside Drupal, and often across both.

What "best" means depends on the use case, the user, and the requirements for speed, reliability, security, governance, cost, and human review. There will be best practices, but no single approach fits every case.

Who is doing the work shapes what "best" looks like:

• A developer may prefer an external coding agent like Claude Code.
• A marketer may prefer a Drupal-native experience that keeps them close to previews, translations, moderation, and publishing.
• A campaign manager may need an external workflow that coordinates email, social media, analytics, DAM, and CMS.

Work will move across systems and people. The best end-to-end experience will come from doing each step where it can be done best, while making the handoffs feel invisible.

A head start is not a plan to win

Understanding Drupal's role in these future workflows gives us clarity about where Drupal needs to go. Drupal needs to get better at supporting external orchestration, Drupal-native workflows, and the real-world hybrids that combine both.

What makes Drupal interesting is that it already has so much of the hard, unglamorous infrastructure these workflows need: structured content, granular permissions, revisions, rollback, JSON:API, and plenty more. These are exactly the capabilities agents need, and they're genuinely difficult to build well from scratch or retrofit.

Conceptual clarity and a strong foundation are wonderful things, but they are not enough to win.

When I asked whether AI coding agents would recommend Drupal, the issue was not Drupal's capability. It was whether agents could get from prompt to a working Drupal site quickly and easily enough. As I wrote in "Friction, abstraction and verification", agents tend to choose the path that gets them to a real, verified result with the least friction.

For experienced Drupal teams, the challenge is different. They have already chosen Drupal. They do not need an agent to recommend it. They need agents that help them build, validate, and ship quality work faster.

To turn Drupal's advantage into adoption, we need to improve both paths: helping agents choose Drupal for new builds, and helping existing Drupal teams ship better work faster. Both depend on making it easier for agents to work with Drupal from start to finish.

That means Drupal needs to expose the best practices, site context, tool definitions, constraints, and precise validation agents need to take the right actions and verify the result.

A lot of this is already underway across Recipes, Site Templates, Drupal AI, Drupal Canvas, ECA, FlowDrop, Maestro, MCP, and CLI improvements, to name a few.

But the goal is bigger than any one project. Drupal needs these efforts to add up to a clear, coordinated path for agents: from setup to connection, context, governed action, validation, recovery, and launch.

Special thanks to James Abrahams, Jürgen Haas, Randy Kolenko, Scott Falconer, and Shibin Das for their review and contributions to this blog post.

I Keep Evaluating Alternatives to Drupal. I Keep Choosing Drupal. Here Is the Actual Reasoning. Why I Bother Looking at All

There is a failure mode among experienced developers where they defend their stack because switching would invalidate years of accumulated expertise. The sunk cost is real and the bias is real. The antidote is to take the alternatives seriously when the opportunity comes, build something real with them, and see whether they have caught up.

So when a project's requirements actually push me toward another tool, or when I am curious enough about a new one to spend real time on it, I do exactly that. I read the docs properly. I build a non-trivial prototype. I model a real content structure, not a blog with three fields. I look at what production would actually require. Then I compare honestly.

This post is the result of those evaluations. It is not a Drupal sales pitch. It is the reasoning of someone who has genuinely used the alternatives and keeps finding that, for the work I do, the decision still holds.

Where the Alternatives Are Genuinely Better

Let me start here, because a post that only praises Drupal is not credible.

The modern headless stacks are genuinely better at greenfield speed. If I am starting a small-to-medium project with a clean content model and a React frontend, Sanity or Payload will get me to a working state faster than Drupal will. The developer experience is smoother. The frontend integration is more natural. The mental overhead is lower. For a certain class of project, they are simply the better choice, and I have recommended them when that was the case.

Custom Next.js builds give you total control. No framework opinions to fight. No contrib modules to maintain. For a team with strong frontend engineers and a genuinely unusual set of requirements, building from scratch can be the right call.

These are real advantages. I am not going to pretend otherwise. If your project is greenfield, your content model is simple, and your team is React-native, the alternatives deserve serious consideration and might win.

Where They Keep Falling Short

Here is the pattern I keep hitting. The alternatives are excellent at greenfield and start to strain the moment the content model gets genuinely complex.

A blog with posts and authors is easy in any of these tools. A content structure with deeply nested relationships, polymorphic references, conditional fields, revision workflows across content types, and the kind of editorial complexity that real enterprise content demands is where the headless tools start showing their age, and where Drupal's entity and field system pulls ahead.

This is the single most consistent finding across every round of re-evaluation I have done. The tools that win the demo lose the complex content model. Drupal that loses the demo wins the complex content model. And in the kind of work I do, the content model is almost always complex.

The Four Reasons I Keep Choosing Drupal

When I strip away the noise, four things keep Drupal as my default for the work I actually do.

1. The content modeling is genuinely better

Drupal's entity and field system is the best content modeling foundation I have worked with, and I have worked with most of them. The ability to define content types with arbitrary fields, reference entities polymorphically, attach fields to anything, build view modes for different rendering contexts, and have all of it integrate cleanly with revisions, translations, and access control is not matched by the headless alternatives.

The headless tools model content as documents with schemas. That works beautifully until your content is not really document-shaped. Drupal models content as entities in a relational graph, which is harder to learn and more powerful when the structure gets complex. For the content I work with, that power is the difference between a clean implementation and a pile of workarounds.

2. Long-term maintenance and stability

I have Drupal sites I built years ago that still run, still update, still get security patches, and still make sense to a developer opening the codebase for the first time. The upgrade path from Drupal 8 forward has been genuinely good, and the project takes backward compatibility and security seriously in a way that matters when you are responsible for a site over years rather than months.

The headless ecosystem moves faster, which is exciting and also exhausting. Tools get acquired, change pricing, deprecate APIs, or simply lose momentum. Betting a long-lived enterprise site on a venture-funded SaaS CMS means betting on that company's roadmap and survival. Drupal is not going to get acquired and pivot. That stability has real value when the site needs to live for a decade.

3. Ecosystem and community depth

Twenty years of contrib modules, documentation, Stack Exchange answers, and accumulated community knowledge is a moat that is easy to undervalue until you need it. When I hit an unusual problem in Drupal, someone has almost certainly hit it before and written about it. The depth of the ecosystem means most problems are solved problems.

The newer tools have enthusiastic communities, but they do not have twenty years of accumulated edge-case solutions. When you hit the unusual problem in a younger ecosystem, you are often the first one there, which means you are solving it from scratch.

4. Migration and enterprise-scale capability

Drupal's Migrate API and its broader enterprise tooling (multilingual, workflow, content moderation, granular permissions, multisite) are built for the scale and complexity that enterprise content operations actually have. I have migrated large, messy, legacy content estates into Drupal, and the tooling for that work is mature in a way the alternatives have not matched.

When a project involves moving hundreds of thousands of pieces of content from a legacy system, with all the data-cleaning and field-mapping and URL-preservation that entails, Drupal has the tools and the patterns. Most of the alternatives assume you are starting fresh, because greenfield is where they shine.

What This Means in Practice

The honest synthesis is this. Drupal is not the right answer for every project, and I do not pretend it is. For greenfield projects with simple content models and React-native teams, the alternatives are often better and I will say so.

But for the work I actually do, which involves complex content models, enterprise requirements, long-lived sites, and frequently the migration of large legacy content estates, Drupal keeps winning the evaluation. Not because I am attached to it. Because every time I take the alternatives seriously and build something real with them, I hit the same wall: they are excellent until the content model gets hard, and then Drupal pulls ahead.

The decision is not "Drupal is best." The decision is "Drupal is best for this kind of work," and the kind of work I do keeps being that kind.

Closing Thought

The reason I stay aware of the alternatives is that the day one of them closes the gap on complex content modeling, long-term stability, and enterprise migration, I want to know about it before my competitors do. So far that day has not come. The headless tools keep getting better at the things they were already good at, and keep not solving the things Drupal is good at.

Maybe that changes. Maybe Payload or whatever comes next builds a content modeling system that matches Drupal's entity API while keeping the modern developer experience. If it does, I will notice, because I pay attention. Until then, the choice keeps making itself.

If you have moved from Drupal to one of the alternatives and it held up on a genuinely complex content model, I would be curious to hear about it. That is the case I keep expecting to find and keep not finding, and I would rather learn it from you than from losing a project.

The Drupal Scheduler module automates content publishing and unpublishing. Learn about the module setup, its cron dependency, workflow integration, and configuration.

Overview Defence Housing Australia’s challenge The Defence Housing Australia website was on Sitefinity CMS, a proprietary content management system that was approaching end-of-life (EOL). DHA wanted to rebuild its website on the GovCMS SaaS platform, within a tight time frame of only 9-12 weeks to ensure that the replatforming was done prior to the EOL date. Defence Housing Australia’s transformation Salsa Digital started with an assessment to ensure GovCMS SaaS and CivicTheme would meet DHA’s needs. As part of the assessment (and in preparation for the content migration) Salsa mapped the existing content structures to CivicTheme. The mapping became a key input to the Figma designs, platform configuration and content uplift.

Today we are talking about AI, Agents, and A System to manage them with guest Luke McCormick. We'll also cover AI Auto-reference as our module of the week.

For show notes visit: https://www.talkingDrupal.com/558

Topics

• Introducing Agent Management
• Origin Story Claude Credits
• Scrum Meets AI Retention
• Handoff Protocol Filesystem
• Why Handoffs Work So Well
• Examples and Human Loop
• Agent Roles and Model Costs
• Choosing Models by Task
• Not Drupal Specific
• Works With Any Model
• Scrum Sprints For Agents
• Human Cognitive Overload
• Tuning Autonomy Levels
• Setup And Handoff File
• Updating Customized AMS
• Persistent Memory Artifacts
• Demand Better Summaries
• Solo Power With Agents
• Roadmap And AMS Trio

Resources

• Stanford Web Camp - Agile for Agents – Managing Robots The Way We Manage Humans.
• AMS
• Robert Douglas spec kitty
• xdebug tui
• ams-trio

Guests

Luke McCormick - cellear

Hosts

Nic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi

MOTW Correspondent

Martin Anderson-Clutz - mandclu.com mandclu

• Brief description:
  • Have you ever wanted to use AI to suggest related content on your Drupal site? There's a module for that.
• Module name/project name:
  • AI Auto-reference
• Brief history
  • How old: created in June 2023 by Scott Euser (scott_euser) or Soapbox
  • Versions available: 1.0.0-rc4
• Maintainership
  • Actively maintained
  • Security coverage - opted in, needs stable release
  • Test coverage
  • Number of open issues: 4 open issues, 1 of which is a bug
• Usage stats:
  • 19 sites
• Module features and usage
  • AI Auto-reference works with any reference fields, so it could find suitable taxonomy terms, nodes, etc
  • It does that by rendering a specified view mode, so it should with any kind of complex layout approach you may have implemented on your site
  • It will also automatically shorten your content to fit within your AI model's token window, which you can also configure
  • The module extends Drupal's main AI module, which means you can select which model to use, and probably means you can also use guardrails, and all the other powerful features that come with that ecosystem
  • Ai Auto-reference comes with default prompts, but you can also edit those if you really want to make sure you're squeezing out every drop of relevance
  • You can also choose for which fields in each content type you want to generate suggestions, as well as whether you want the suggestions should be automatically applied, or whether you want them manually reviewed
  • As mentioned on the project page, you can already have AI suggest things like tags using the AI module without this project, but this may be a better choice if you want to make sure the recommendations stick to an existing set

Governance, infrastructure funding, and release maintenance define this week’s Editor’s Pick as the Drupal Association keeps self-nominations open for its 2026 At-Large Board Election and introduces the Drupal Sustaining Members Program. The updates connect elected representation, recurring support for shared project infrastructure, security remediation, and final testing for Drupal 11.4.0-rc2.

The election will fill one community-elected seat on the Drupal Association Board. The seat opens as Alejandro Moreno completes their 2024–2026 term. Candidates must self-nominate, and nominations close on 30 June 2026 at 23:59 UTC.

Candidates will be announced on 7 July 2026. The Get to Know the Candidates period runs from 7 July to 21 July 2026, followed by voting from 22 July 2026 at 00:00 UTC to 14 August 2026 at 23:59 UTC. The new board member will be announced on 26 August 2026.

Voting eligibility depends on individual Drupal Association membership. Members must have an active membership by 21 July 2026 at 00:00 UTC, at least 24 hours before voting opens. The schedule gives prospective candidates and voters clear deadlines for participation before the election enters its voting phase.

The Drupal Sustaining Members Program creates a recurring funding path for organisations that depend on Drupal. The association says contributions support Drupal.org, code repositories, software packaging and distribution, the Composer package endpoint, issue tracking, contribution workflows, continuous integration and testing, Automated Updates, Project Browser infrastructure, and security response systems. The programme frames shared infrastructure as an operational responsibility rather than an incidental benefit of open-source use.

The programme follows Acquia’s Fair Trade Initiative, which directs 2% of eligible Acquia partner Drupal deals to the Drupal Association. Together, the two efforts point to a more predictable funding model for infrastructure used across the Drupal ecosystem.

Maintainers should also review Drupal security advisories published on 17 June 2026. The Drupal core advisories cover improper validation, server-side request forgery, cache poisoning and open redirect, a gadget chain, and PHP object injection. Contributed project advisories were also published for Plotly.js Graphing, Flag attendance field, and Formatter Field.

Drupal 11.4.0-rc2 is available for final testing ahead of the Drupal 11.4.0 stable release window. Release candidates are not supported for production sites, but they allow developers, maintainers, translators, and site builders to test compatibility before the stable release. Sites using Media oEmbed URL discovery may also need to review media_oembed_discovery_trusted_host_patterns in settings.php.

Drupal 11.4.x will receive security support until June 2027. Drupal 11.3.x will continue to receive security support until December 2026. Those support windows give site owners a near-term basis for upgrade and maintenance planning.

The DropTimes also held its June Open Townhall as part of its monthly community coordination format. The session covered editorial updates, contributor coordination, community feedback, and coverage planning. It reflects TDT’s continuing effort to align editorial priorities with Drupal community activity and reader input.

Upcoming Drupal events include DrupalCamp Tokyo 2026 on 27 June 2026 in Tokyo, DrupalCamp Kortrijk 2026 from 29 June to 30 June 2026 in Kortrijk, Drupal Camp Asheville 2026 from 10 July to 12 July 2026 in Asheville, and Decoupled Days 2026 from 6 August to 7 August 2026 in Montréal.

The week’s updates place governance, funding, security, release readiness, editorial coordination, and community participation in the same frame. Community members considering board service can review the election process before nominations close. Organisations that rely on Drupal can assess whether recurring infrastructure support fits their open source contribution model.

Additional developments from across the Drupal ecosystem were published during the week. Readers can follow The Drop Times on LinkedIn, Twitter, Bluesky, and Facebook for ongoing updates. The publication is also active on Drupal Slack in the #thedroptimes channel.

Allen Jason
Junior sub-editor
The Drop Times

Provider costs, agent behaviour and multilingual support are becoming practical governance questions for Drupal sites adopting AI workflows. In written responses facilitated by the DrupalCamp Tokyo 2026 organisers, James Abrahams told The DropTimes that Drupal AI is relying on pluggable governance, Drupal CMS-aligned work, outside-in agent workflows and collaboration with Symfony AI. His answers frame Drupal’s AI direction around maintainability, structured site building and multilingual production readiness rather than isolated feature development.

Read more

AI makes execution cheap. It makes context, coordination, governance and sovereignty more valuable.

The CMS is being unbundled into a control plane and an execution plane. Follow that logic across the full customer experience and something else becomes visible: the DXP is being rebundled as the shared control plane for an organisation’s digital promise.

The CMS is unbundling. The DXP is rebundling.drupalMonday, June 22, 2026 - 18:00

DrupalCon Rotterdam’s first Government Summit has opened its call for public-sector session proposals ahead of the one-day event on Monday 28 September 2026. The summit will bring local, national, and European public administrations together around shared digital infrastructure, open source reuse, digital sovereignty, and Drupal-based service delivery. Organisers are seeking case studies, demonstrations, workshops, and facilitated discussions, with submissions closing on Monday 29 June 2026 and selected participants receiving complimentary access to the summit.

We Love To Hear Your Support Questions!

As you know and have experienced personally, AI has been replacing human interaction in support situations, and in some cases doing a decent job. It generally does a good job with questions about DDEV.

But getting answers to questions is not the only purpose of support. It's also a great way to communicate problems and ambiguities to project maintainers.

We want you to ask us questions! We live for your questions. We miss the fact that you've been absent from Discord, #ddev in Drupal Slack, and the issue queue. When you ask, it helps us to understand what your struggles are and how DDEV can get better. DDEV's strength has always been the community's willingness to engage and share their needs and frictions and hopes for the project.

As you know, Stack Overflow has been displaced by AI. There aren't new answers going up there, because people use the AI answers and don't improve anything for the future. But DDEV is not static and its future depends on you and your needs. If we don't hear you ask about those, we can't react to your experience.

Join us in all the support channels!

Upsun Completes DDEV Trademark Transfer

Upsun has finished transferring the DDEV trademark to the DDEV Foundation — a milestone for the DDEV project's long-term independence and health. This is a generous and important step for DDEV. (At one time before Upsun/Platform's involvement, we were ready to fork and rename the project due to trademark issues.) Read our announcement↗ and see Upsun's generous response↗ as well.

What's New

• coder.ddev.com: Drupal Contrib → The hosted Coder.ddev.com environment now supports Drupal contrib projects via the DDEV Drupal Contrib add-on workflow.
• Joomla! Explicit Support → Joomla users have loved DDEV for years, and in DDEV v1.25.2 we introduced an explicit joomla project type. Community member renekreijveld also maintains the ddev-joomla↗ repository, which provides scripts and tooling for extended Joomla workflows.
• mayfly.live → Zero-config DDEV-based online preview environments, in open beta.
• Drupal AI Learner's Club AI Safety Session → Randy was co-host of AI Security 'Opportunities': Guardrails, Sandboxes, and Keeping Your Agents on a Leash and introduced a couple of the many add-ons.

New DDEV GUIs

New community-built GUI tools have appeared for DDEV:

• ddevbar → A macOS menu bar app for managing DDEV projects with a single click — start, stop, and restart without touching the terminal. klemens.ee/ddevbar↗
• DDEVUI → A native macOS app (Swift/SwiftUI) that puts a visual front-end on DDEV. github.com/dave-agilepixel/DDEV-Apple-GUI↗
• ddev-ui → A cross-platform desktop app for macOS, Windows, and Linux built with Electron and React. Covers project management, database import/export, snapshots, add-on management, log streaming, and more. github.com/shiv122/ddev-ui↗

Stanford WebCamp: Pre-Flight Checklist for Drupal Developers

Bob McDonald (UltraBob) presented "Pre-Flight Checklist: Local Code Quality for Drupal Developers" at Stanford WebCamp, covering the ddev-drupal-code-quality add-on for running Drupal.org CI checks locally before pushing. View session↗.

DrupalDevDays Athens — Video Now Available

Community member Bill Seremetis (bserem)'s "From Chaos to Consistency" DevOps talk from DrupalDevDays Athens 2026 is now on YouTube. The talk covers how DDEV add-ons work as a file/feature delivery mechanism for standardizing team projects. Watch on YouTube↗ • Slides↗.

Community Highlights

DDEV Sponsorship Data Story — A new post on ddev.com tells the story of how a LinkedIn message from Anoop John at TheDropTimes turned into live, auto-updating sponsorship displays across DDEV properties and a public data feed. Read it↗

Open Source AI Contributions — Amber Matz wrote about the complexity AI-generated contributions are bringing to open source projects, using a conversation with Randy as a central example. Worth a read for all maintainers and contributors and AI users. Read↗

Community Tutorials from Around the Web

• Getting Started with DDEV for Drupal Development → WebWash covers installation, project setup, commands, database management, and debugging with DDEV and Drupal. Read on WebWash↗
• DDEV Linux Installation with WordPress → Step-by-step guide to installing DDEV on Ubuntu and setting up a WordPress project with WP-CLI. Read on rueegger.me in German↗
• DDEV + a-blog cms (Japanese) → A guide to using DDEV as a local development environment for a-blog cms, covering multi-project management and Mailpit. Read on kazumich.com↗
• Lando & DDEV: Replacing Custom Shell Scripts — Drainpipe → Lullabot explores how Drainpipe, a Composer plugin for Drupal CI/CD, can use either Lando or DDEV as its local environment. Read on Lullabot↗

Governance

The DDEV board and community are working on updated sponsorship tiers and improved communication around them. Discussion at ddev/sponsorship-data#42↗ and ddev.com#647↗.

The first-ever DDEV Foundation Board meeting was held on June 17!

The next DDEV advisory group meeting is July 1, 2026 at 8:00 AM US Mountain / 10:00 AM US Eastern / 16:00 CEST. Add to Google Calendar • See the agenda.

Sponsorship Update

Sponsorship is at 84% of the goal, thank you to everyone who has contributed!

April 2026: ~$9429/month (79% of goal)

June 2026: ~$10,075/month (84% of goal)

If DDEV has helped your team, consider sponsoring. → Become a sponsor↗

Contact us to discuss sponsorship options that work for your organization.

Statistical Tidbits of the Month

• DDEV has exceeded 20,000 weekly users some weeks! — live graph.

Stay in the Loop—Follow Us and Join the Conversation

• Blog↗
• LinkedIn↗
• Mastodon↗
• Bluesky↗
• Discord↗

Compiled and edited with assistance from Claude Code.

Views is one of the most important modules in Drupal. After the field system, it is the tool you reach for most often as a site builder. You use it to build content listings, create blocks, power admin screens, and feed components into Drupal Canvas.

In the video above, you’ll learn how to build a Views page, customize fields with image styles and rewrite tokens, expose filters and sorts, configure pagers and infinite scroll, expose a view block as a Canvas component, and create a backend admin page.