Talking Drupal

Today we are talking about Drupal, AI, and learning to use it responsibly with guest Mike Anello. We'll also cover Entity Mesh as our module of the week.
For show notes visit:
https://www.talkingDrupal.com/566
Topics
Course overview
Fast moving modules
Inside vs outside AI
No code approach
Keeping curriculum current
Essentials vs add ons
Chat Claude Code setup
Inside vs Outside AI
Rules and Provider Calls
Guardrails in Drupal UI
Model QA and Testing
Local Models and Costs
Token Budgets and Logging
Course Use Cases Overview
RAG and Vector Basics
Class Schedule and Pricing
AI Predictions and Wrap
Resources
New DrupalEasy class: Responsible Drupal AI Basics
Training at orlando
amazee ai
Jrockowitz losing my skill
AI module ecosystem
AI browser provider (LLM in Google Chrome)
amazee.ai Private AI Provider
Derecho
Guests
Mike Anello - drupaleasy.com ultimike
Hosts
Nic Laflin - nLighteneddevelopment.com nicxvan
John Picozzi - epam.com johnpicozzi
JD Flynn - dorficus
MOTW
Correspondent
Martin Anderson-Clutz - mandclu.com mandclu
Brief description: Have you ever wanted a way to analyze and visualize the ways in which the content on your Drupal site is interlinked? There's a module for that.

Module name/project name: Entity Mesh

Brief history How old: created in Jan 2025 by Jorge Tutor (gedur) of Metadrop
Versions available: 2.1.0 and 2.0.3, both of which work with Drupal 11

Maintainership Actively maintained, latest release last month, and a commit just yesterday
Security coverage
Test coverage
Documentation? Project page is pretty descriptive
Number of open issues: 13 open issues, 4 of which are bugs, but 2 of those were marked fixed in the past week

Usage stats: 437 sites

Module features and usage With Entity Mesh installed, the module will analyze the rendered output of your nodes using a chosen account, looking for links to other content
That means it will find not just links in entity relationship fields, but also links within formatted text, menus, and more
The results can be visualized in a D3.js 3D visualization, displayed as a table, or exported as a CSV
The report also exposes a set of Views-style filters, to help you narrow down to the specific set of information you want to understand
Entity Mesh analyzes the DOM of your rendered nodes, looking for links, iframes, and images. Internal paths are further analyzed and categorized, for example based on whether the specified path redirects, is broken, points to something that is access-denied, and so on
From a marketing perspective, that allows you to understand the paths available to navigate from a source page to a target page, the content linked to or from a specific page, and will also augment the content deletion confirmation form to advise the user of any existing links to the content being deleted
There are obvious SEO advantages to being able to find redirect chain, broken or access denied links, and there are GDPR compliance implications for being able to identify iframes that might load third-party cookies
The project page also mentions that this module could be very useful to run after a content migration, for QA
The actual analysis of your site content be triggered by drush, an admin form, or by cron, and you can set limits on the size of the batch to run, because of the weight it puts on your site by rendering every node it analyzes
The current versions Entity Mesh also depend on the Entity Registry and Entity Render Context modules, that have essentially the same maintainers, so if there's only part of Entity Mesh that you really need, you could also give those a look
Back in episode #321 we covered Entity Usage, and there are some definite similarities, but also some differences. While they both provide reporting on content relationships, Entity Usage does so by examining structured field values at save time. So, the information gathered is different, and collects data that can be displayed in views or custom code.

Today we are talking about Open Source sustainability, becoming your own content creation machine, and how drupal influenced some of that with guest Jeff Geerling. We'll also cover AI Metering as our module of the week.
For show notes visit:
https://www.talkingDrupal.com/565
Topics
Jeff's Timekeeping Icebreaker
Jeff's Drupal Origin Story
From Drupal to Hardware Tinkering
Staying Motivated on YouTube
What Conferences Are Really About
DrupalCon Memories and Community
Why Jeff Moved to Hugo
PSA Tornado Warning Detour
Keeping Up with Drupal CMS
PHP Perception Shift
Fast Drupal Setup
COVID Streaming Boom
Picking Video Projects
Decommissioning Builds
YouTube Algorithm Risk
Vintage Time Server
Creator Starter Tips
Supporting Maintainers
Books and Crohns
Local Control Trends
AI Workflow Boundaries
Timing Obsession
Kind Drupal Culture
Guests
Jeff Geerling - jeffgeerling.com geerlingguy
Hosts
Nic Laflin - nLighteneddevelopment.com nicxvan
Mike Anello - drupaleasy.com ultimike
JD Flynn - dorficus
MOTW
Correspondent
Mike Anello - drupaleasy.com ultimike
Brief description: AI Metering module - helps keep track of your users' AI token usage on the site. Includes cost estimation, token limits, and local LLM fallback options.

Module name/project name: AI Metering

Brief history How old: created in June 1 2026 by Jérôme Tchania (codeitwisely)
Versions available: 1.0.1

Maintainership Actively maintained - yes
Co-maintained by Carlos Ospina (camoa)
Security coverage - yes
Test coverage - yes
Documentation - yes
Number of open issues: 9 open issues, 4 of which are bugs against the current branch

Usage stats:
Sites: 78

Module features and usage Obtains token costs for all modules from LiteLLM
Can be configured to send email when the token limit is being approached.
Per user and per role reports.
LLM fallback to Ollama

Today we are talking about Maintaining NodeJS, Patternlab, Writing Books, and Open Source with guest Brian Muenzenmeyer. We'll also cover AI Webform Generator as our module of the week.
For show notes visit:
https://www.talkingDrupal.com/564
Topics
Brian Open Source Origins
Pattern Lab Node Journey
Maintaining and Moving On
Writing Approachable Open Source
Who the Book Is For
Beyond Code Contributions
All Things Open Book Signing
Choosing Conferences to Attend
Pitching Open Source at Work
Misconceptions and Starting Small
Avoiding Maintainer Burnout
Handling AI Noise and Low Effort PRs
DCO and Licensing Basics
Better Communication and Reviews
Node and Drupal Lessons
Optimism for Open Source Future
Resources
Brian Muenzenmeyer https://brianmuenzenmeyer.com
https://approachableopensource.com/
https://bsky.app/profile/brianmuenzenmeyer.com
https://www.linkedin.com/in/brian-muenzenmeyer-91a77554/
https://www.renderatl.com/schedule upcoming
https://nodeconf.eu/program upcoming
spectrum of engagement
https://approachableopensource.com/blog/2025-open-source-pace-layers/ change in contention
https://brianmuenzenmeyer.com/posts/2018-i-maintainer/ burnout
https://approachableopensource.com/read/the_spectrum_of_engagement/
https://approachableopensource.com/read/the_four_files_of_any_open_source_project/ LICENSE

Hodag Cryptid
https://en.wikipedia.org/wiki/Hodag
https://www.rhinelanderchamber.com/about-the-hodag/

You should write a book
All contributors spec
Talk at all things apart
DCO Developer Certificate of Origin

Open source law policy and practice
Sustain OSS
Guests
Brian Muenzenmeyer - brianmuenzenmeyer.com
Hosts
Nic Laflin - nLighteneddevelopment.com nicxvan
John Picozzi - epam.com johnpicozzi
Bernardo Martinez - bernardm28
JD Flynn - dorficus
MOTW
Correspondent
Jacob Rockowitz - jrockowitz.com jrockowitz
Brief description: AI Webform Generator enables site builders to create a Drupal Webform, or update an existing one, from plain-English instructions. It sends the request through the site's configured Drupal AI provider, validates the returned Webform definition, and saves the resulting form. Review the generated change before using the form.

Module name/project name: AI Webform Generator (ai_webform_generator)

Brief history Created on 2 July 2026 by chaitanyadessai (Chaitanya R Dessai).
The current stable release is 1.0.2, released on 3 July 2026, and supports Drupal ^10 || ^11.

Maintainership Appears actively maintained: Drupal.org lists an update on 24 July 2026.
Maintainers: zeeshan_khan and chaitanyadessai. (Specbee)
Security coverage: Yes. Stable releases are covered by Drupal's security advisory policy.
Test coverage: Yes. Version 1.0.2 includes unit, kernel, and functional tests for prompt building, JSON validation, settings, route access, Webform building, and optional CAPTCHA elements.
Documentation: Yes. The project page and module README cover requirements, configuration, usage, security considerations, and supported field types.
Issues: 1 open issue, with 0 open bug reports (7 issues total).

Usage stats: 1 site reports using this module.

Module features and usage Creates complete Webforms and updates existing Webforms in place from natural-language prompts.
Supports common Webform elements, including text, email, telephone, number, date, select, checkbox, radio, range, password, hidden, and managed-file elements.
Validates the AI response before applying the Webform definition.
Uses the existing Drupal AI provider configuration; API keys are not stored in this module's configuration.
Provides configurable model, temperature, output-token, and per-user request limits to balance output quality and provider spend.
Requires trusted users with both the generator permission and ordinary Webform edit access when changing an existing form.
AI-Generate Notes, Review, and Recipe (used for testing)
https://github.com/jrockowitz/drupal_playground/tree/main/recipes/drupal_playground_webform_ai
AI-Generated Assessment
Technical:
The module separates AI generation, prompt building, JSON validation, and Webform construction into Drupal services. It uses the site's configured Drupal AI provider, validates a limited allowlist of Webform element types before saving, and exposes model, temperature, output-token, and per-user request-limit settings.
Access and error handling:
Generation requires its own permission, and updating an existing Webform also requires normal Webform update access. A per-user flood limit constrains provider spend; failures are logged, with detailed upstream errors shown only to generator administrators.
Code quality:
Version 1.0.2 uses strict types and separates form, service, validation, and persistence responsibilities. It includes unit, kernel, and functional coverage for core behavior. This assessment is a code review of the released module, not a security audit.
Implementation:
The module creates new Webforms and updates supported fields of existing Webforms in place, but saves the generated definition immediately without a preview, diff, or approval screen.
Usefulness:
The module is useful for quickly drafting straightforward Webforms and iterating on common field changes when a site builder reviews the result. Complex, highly customized, or regulated forms need especially careful manual review before publication.
How to use it:
Configure a chat-capable provider, select an existing Webform or choose to create one, describe the fields and validation in plain English, submit the request, and then review the saved Webform. For example, create a disposable contact Webform and ask the generator to add a required telephone field while preserving the existing fields.
AI-generated source code:
The module's runtime use of AI and its code style cannot establish whether its source was AI-generated or AI-assisted. Its public project metadata does not make an authorship claim, so this is unknown.
Possible improvements:
Add a preview/diff and explicit approval before saving; broaden support for advanced Webform structures and handlers; add optional, privacy-conscious prompt and response audit logs; and expand regression coverage for complex Webform updates.
Next steps for adopters:
Restrict generation to trusted roles, begin with a low request limit, test representative prompts outside production, and review every generated field, validation rule, confirmation message, and permission before publishing.

How should development teams adopt AI without sacrificing code quality or collaboration? In this Talking Drupal Cafe, Stephen Cross is joined by Mike Miles and Jim Birch to discuss practical strategies for integrating AI into Drupal development teams. They explore AI coding assistants, team policies, code review, agent workflows, governance, and real-world lessons from using tools like Claude Code and GitHub Copilot in production environments.
For show notes visit:
https://www.talkingDrupal.com/cafe020
Topics
Why AI Matters Now
Team Introductions
From Experiments to Workflows
Standards and Guardrails
Skills and Automation Examples
Taming Verbose AI Code
Adoption and Tool Choices
Governance and Training
Measuring Productivity Gains
Keeping Up Without FOMO
AI for Editors and Site Features
Red Teaming and AI Security
Jim Birch
Jim Birch is Director of Engineering and AI Practice Lead at Kanopi Studios, where he leads engineering teams and oversees the company's responsible adoption of AI. Jim is also a Drupal CMS committer, and Recipes Initiative Coordinator, and is a Google Cloud Certified Generative AI Leader.
Michael Miles
Mike Miles is a technical leader and speaker with more than 20 years of experience in web engineering, open-source development, and digital platform delivery. As the Director of Web Development at MIT Sloan, he leads the team responsible for the development, maintenance, and growth of the school's public digital properties.
Mike regularly speaks at technical conferences on topics including modern web development, Drupal, technical leadership, testing, delivery practices, and practical AI adoption. He is also one of the organizers of New England Drupal Camp.
Stephen Cross
Stephen Cross has been a Drupal developer for over 20 years and founded Talking Drupal in 2013. As founder of Second Signal Media, he combines his passion for open source and media production to share conversations that help the Drupal community learn and grow.
Guests
Michael Miles - mikemiles86
Jim Birch - thejimbirch
Stephen Cross - stephencross
Resources
Courses
https://anthropic.skilljar.com/
https://academy.openai.com/pages/courses
Skills
https://kanopi.github.io/cms-cultivator/
https://kanopi.github.io/delivery-record/

Today we are talking about Drupito, its Business model, and Marketplaces with guest Ashraf Abed. We'll also cover Generate (Social Media) Image as our module of the week.
For show notes visit:
https://www.talkingDrupal.com/563
Topics
Meet Drupalito and the Mission
Platform Layers and Roadmap
Pricing and New Markets
Marketplace Success Stories
Exportability and Vendor Lock In
Growing the Drupal Ecosystem
Derivatives and Recurring Revenue
Rebuilding on Drupedo
Funding Drupal Association
Global Community Check In
Migrating Sites to Drupedo
Marketplace Vision Shift
Maintenance and Incentives
Safe Updates Blue Green
Testing Mindset for Templates
Official Marketplace Collaboration
Agency Revenue and Partnerships
Niche Derivatives and Pricing
Launch Plans and Vetting
Resources
Code that ships
Hosts
Nic Laflin - nLighteneddevelopment.com nicxvan
John Picozzi - epam.com johnpicozzi
Ashraf Abed - drupito.com ashrafabed
Avi Schwab - froboy.org froboy
MOTW
Correspondent
Avi Schwab - froboy.org froboy
Brief description: Have you ever wanted Drupal to generate dynamic social media images using tokenized node data, similar to the share images on GitHub repos or Reddit threads? There's a module for that

Module name/project name: Generate (Social Media) Image

Brief history How old: Created by tfranz of Germany on 22 April 2022
Versions available: 1.x-dev, 2.0.0-beta2, published a few weeks ago by our own Martin Anderson-Clutz

Maintainership Minimally (although now slightly more actively) maintained
No Security coverage (yet)
Passing GitLab CI tests
Well fleshed out README for docs
Number of open issues: 8 open issues, 0 of which are bugs against the current branch, but there are lots of feature requests

Usage stats: 1 site reports using this module

Module features and usage GSMI requires an image style that uses a "Text Overlay" effect — this comes from the Image Effects module and lets you burn tokenized (or static) text onto an image. Normally, when Drupal generates an image style derivative, there's no entity in scope — it's just processing a file — so a token like [node:title] would resolve to nothing. GSMI's real contribution is the glue: when it builds a derivative for a specific node, it swaps in the node-resolved text before generating the image. That's what makes entity-aware tokens work inside an effect that otherwise only sees global tokens.
Once the image style exists, GSMI's settings form lets you pick a source image field on the node — an image field or a media-reference field — plus a fallback image for when that's empty. From there it generates the styled derivative from that source image, for any node of any content type that has the field.
Finally, GSMI exposes its own token — [node:generate-style], with optional style/field overrides — so you're not locked into the one global style/field pair configured in the settings form. I used that to drop the generated image into Metatag's og_image field for the Session content type on the MidCamp site, getting us dynamically generated session images..
A couple of gotchas we hit setting this up:
Text Overlay's layout options have some bugs, and not filling out all of the options will result in an image library error.
The bigger one: GSMI names the generated derivative file after the source image's filename — extension included — not after whatever format the image style actually outputs. If you try to convert an image to WebP you might get a WebP image with a JPG extension.
BUUUUT - LinkedIn still doesn't support WebP (at least as per their documentation, so it's still in 2026 not safe to use WebP for a universal og:image. https://www.linkedin.com/help/linkedin/answer/a521928