Dries Buytaert’s recent article on AI and the unbundling of digital agencies maps out many of the pressures and changes agencies are navigating right now. He outlines the shift from execution to orchestration, the reduced value of raw platform expertise, and the growing need for agencies to focus on outcomes rather than tasks. One idea that deserves more attention, though, is how AI might not just change the work agencies do, but change how clients define the work they need in the first place.
Most discussions around AI in agencies focus on internal operations. How can teams use AI to write content, generate code, automate testing, or produce visuals faster? That’s important. But equally important is what happens outside the agency, how client expectations change once they begin using the same tools themselves. When AI gives clients direct access to capabilities they once hired agencies for, their view of what an "agency" is supposed to deliver will shift.
This creates a more subtle kind of unbundling, not just in how services are delivered, but in how problems are framed. A client who used to ask for a full website may now ask for a performance audit or a targeted campaign strategy instead. A marketing team with AI-generated content at their fingertips may turn to agencies less for copywriting and more for brand consistency, cross-channel orchestration, or data-informed decision support. The deliverables may look the same on the surface, but the reasoning behind them changes.
Agencies that understand this shift early will be in a better position to adjust their messaging, services, and proposals. The real question isn't how AI will change agency workflows. It's how AI will reshape what clients believe they need help with. That shift won't happen all at once. But it's already starting, and those who recognise it can prepare for a very different kind of conversation at the next client pitch.
Maya Schaeffer Secures Victory in 2025 Drupal Association Board Election
Drupal: A Digital Public Good for a Better Digital Future | Mike Gifford writes
ECA Module 3.0.0 for Drupal Released with Drupal 11.2 Support and Modeler API
Drupal Releases Modeler API 1.0.0, Paving Way for Unified Automation and UI Flexibility
Drupal Introduces New Contribution Records System to Enable GitLab Issue Migration
DrupalCon Vienna 2025 Opening Reception Sponsorship Opportunities Available
Nominations Open for Women in Drupal Award at DrupalCon Vienna 2025
Upcoming Drupal AI Webinars Focus on Search and Agent Development
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Vortex 25.7.0 Released with Drupal 11.2 Support, Improved CI Pipelines, and Composer Integration
We 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,
Sincerely
Kazima Abbas
Sub-editor, The DropTimes.
Today we are talking about HTMX, What it is, and why it could be a game changer for Drupal with our guests Shawn Duncan & Carson Gross. We’ll also cover RefreshLess as our module of the week.
For show notes visit: https://www.talkingDrupal.com/514
TopicsShawn Duncan - HTMX intiative fathershawn Carson Gross - bigsky.software 1cg
HostsNic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Rich Lawson - richlawson.co rklawson
MOTW CorrespondentMartin Anderson-Clutz - mandclu.com mandclu
Technically, Drupal is one of the most secure open-source platforms out there. It has an active developer community, frequent patches, and a robust architecture. But the reality is that cyber threats aren’t slowing down even in 2025. If you still think updating modules is enough, that’s one of the biggest mistakes today.
You know, cybercriminals in 2025 are sharper than ever. Hacking a site used to take time previously. Now they need just a few minutes, especially when site owners overlook basic security. Drupal may be powerful and built for high traffic, but without proper setup and maintenance, it can be breached. Read this article to learn how to protect your Drupal website from emerging threats.
Hooks are used in Drupal to allow modules and themes to listen to or trigger different sorts of events in a Drupal system. During these events Drupal will pause and ask if any modules want to have any say in the event that is currently being triggered.
For example, hooks are commonly used when content is viewed, created, updated, or deleted. So, if we delete a page of content then a delete hook is triggered which allows modules to react to that content item being deleted. Using this, we can react to this and perform clean up operations on items of content that don't exist any more. Our custom module might want to remove items from a database table, or delete associated files since they wont be needed.
This is just one example of how hooks are used in Drupal as they are used in all manner of different situations, and not just listening for content events. Another example of a common Drupal hook is when creating a custom template. Many modules will use a hook called hook_theme() to register one or more templates with the theme system so that they can be used to theme custom content.
Hooks have been used in Drupal for a long time (probably since version 3) and have always been one of the harder things for beginners to understand. Module files full of specially named functions that seem to be magically called by Drupal is not an easy concept to get into and can take a while to get familiar with.
New in Drupal 11.1.0 is the ability to create object oriented (OOP) hooks, which is a shift away from the traditional procedural based hooks that have been a part of Drupal for so long. This OOP approach to hooks can be used right now, has a backwards compatible feature, and will eventually replace procedural hooks (where possible).
In this article we will look at how to create a OOP hook, how to transition to using OOP hooks in your Drupal modules, and how to create your own OOP hooks.
Last week’s Drupal AI webinar, Choosing the Right AI Tools for Content and Marketing, brought together a global audience and a powerhouse panel. Jamie Abrahams, Alan Botwright, and Matthew Saunders spoke while being moderated by Paul Johnson. Together, we tackled pressing topics facing digital leaders: how to harness AI to deliver real marketing value without getting lost in hype or hamstrung by complexity.
The webinar attracted attendees from more than 20 countries and nearly 80 participants at its peak. This session wasn’t a technical demo. It was an honest conversation about challenges of implementing AI in today’s constrained marketing landscape.
Paul started the conversation by framing the discussion with some statistics. Budgets are under pressure.
Gartner released a report indicating that marketing budgets have dropped to around 7.7% of company revenue, down from 11% in pre-COVID days and this is looking to be the new normal. Combined with that, expectations are rising. Boards want more measurable results, greater efficiency and faster delivery. So everyone needs to do more with less. 59% of CMOs have insufficient budget to execute their strategies and most of them are looking towards AI to have as a possible lever to address this gap or at least try and bridge it. But there are real risks here. Teams are often starting with the technology and then going looking for problems to solve with that technology and that rarely delivers value and often leads to stalled initiatives. How do you help your clients avoid this solution-first mindset and what does a more structured problem-led approach look like in real marketing environments?
– Paul Johnson
Too many teams jump into AI with a solution-first mindset. The panel pushed hard against that.
You need to understand the whats and whys before you start tackling the hows.
– Matthew Saunders
We stressed the importance of identifying repetitive, data-heavy, and feedback-loop-dependent processes. Things like content review gates or asset tagging as the most valuable opportunities for automation.
Jamie framed Large Language Models (LLMs) not as creative geniuses, but as very good pattern recognizers. They’re more “clever librarians” than original thinkers.
LLMs are not doing reasoning in the human sense, they’re more like an extremely good search engine of human knowledge.
– Jamie Abrahams
Expecting them to invent breakthrough creative or strategy will leave you disappointed. But as support for summarising, filtering, and speeding up content workflows? They become an efficiency booster.
AI isn’t a replacement for people, it’s a partner. Matthew walked through a mini case study where AI was used to aid in brand guideline compliance audit, reduce SLA reporting times by 80%, and streamline asset pipelines. But in every case, humans remained in control.
We never removed people from the loop. The AI was an assistant, not an overlord.
– Matthew Saunders
This framing, AI as a force multiplier, resonated across the panel. Alan added:
You can never spend too much time framing the problem. Once that’s clear, everything else starts to fall into place.
– Alan Botwright
Jamie suggested that human soft-skills are going to be increasingly important and that those with educational backgrounds not grounded in computer science might adapt more quickly.
People with psychology or literature backgrounds often adapt to AI tools faster than engineers. Soft skills are a real superpower here.
– Jamie Abrahams
The team then tackled one of the biggest blockers to enterprise adoption: where does your data go?
If you’re using a public LLM, your data is not private. Full stop.
– Matthew Saunders
The options? Either host your own (complex, but sovereign) or work with a trusted provider who can guarantee control over data storage and model access.
Licensing, training, integrations, governance, and internal change management all add up. Matthew suggested teams run a “pre-mortem”:
Ask: a year from now, this AI rollout failed. Why? Map every reason—and you’ll surface the hidden costs before they become real.
– Matthew Saunders
Jamie added that the best outcomes come from constrained agents and narrowly scoped tasks. Not sprawling generalist bots.
If you make your agent or LLM do as little as possible, it’s much more likely to get it right.
– Jamie Abrahams
When asked why Drupal AI matters and what it means to organizations, the panelists had quite a bit to say:
You can build and demo an end-to-end AI prototype in 5 minutes on Drupal. No other open platform gives you that kind of agility.
– Matthew Saunders
This isn’t just a tech shift—it’s a change program. Trust, communication, and alignment across teams are critical to success.
– Alan Botwright
Drupal’s built-in abstraction layers mean you can swap models, switch providers, and adapt as the AI landscape evolves—without rearchitecting everything.
This was a real-world conversation grounded in experience: how to launch, govern, scale, and sustain AI in environments with limited budget, complex regulation, and high user expectations.
If you missed the session or want to share it with your team, the full recording is available here:
Got questions or want to connect around Drupal AI or implementation strategies? Drop by the Drupal AI Slack channel or check out the Drupal AI LinkedIn page.
File attachments: Choosing_the_right_AI_tooling_for_your_business_image.png
john
Wed, 07/30/2025 - 08:54
I’ve been using SendGrid as the transactional email provider for my site for a while. Since I only send about three emails a week—mostly simple contact form submissions—the free tier was perfect for my needs. It let me test things out, integrated easily with Drupal, and just worked.Thinking about AI for marketing? Discover how to identify high-impact use cases for AI adoption and avoid common pitfalls in our recorded expert-led AI webinar.
Shopify is the biggest name in the e-commerce space, and for good reason. The platform is relatively easy to set up, performs well, and has excellent marketing. Its app marketplace is constantly growing, adding more capabilities.
For many merchants, Shopify is all they need. Going with the market leader is an obvious choice.
However, when you reach an enterprise scale, with requirements for B2B commerce and increased operational complexity, the story becomes quite different. Shopify says they offer B2B capabilities at scale, and when you’re subjected to their marketing and advertised track record, it's easy to start nodding your head to the beat of their tune.
Let’s dive into the true cost of Shopify Plus. Reading this will help you ask the right questions and better equip you to judge the answers.
When Shopify's enterprise sales team comes knocking, they arrive with a compelling story. They position Shopify Plus as the solution to all your B2B woes: lower total cost of ownership, enterprise features without enterprise overhead, and the promise that migrating to Shopify Plus will lead to a conversion rate boom.
But often these promises are unrealistic. The pitch typically centers around three key pillars that deserve closer scrutiny.
Shopify's sales pitch often includes dramatic claims about conversion improvements—sometimes suggesting compounding monthly increases that would theoretically give you a 55% conversion rate within six months.
Read more