A few weeks ago, I joined Thierry Muller, VP of AI Products at WP Engine, and Tamara Bohlig, CMO at our shared client, Vida Health, for a webinar discussing a familiar challenge in healthcare marketing and digital experience: AI pilots are easier to start, but much harder to stand behind once they touch real content, customers, and compliance constraints.

In the white paper, we described this challenge as a shift toward “Assured AI.” The goal is not simply to experiment with new models, but to design systems with the observability, governance, and safeguards required to support responsible innovation.

The conversation surfaced and reinforced several practical lessons for healthcare teams exploring AI today.

Reinforcing the principles of Assured AI

Our webinar reinforced the core principles behind our Assured AI framework. AI integrations need to be:

• Observable. Teams can monitor how the system is used, what it outputs, and where it fails, because generative systems don’t behave deterministically.
• Reversible. Teams can constrain, roll back, or disable behaviors quickly if they aren’t acceptable.
• Auditable. Teams can trace outputs back to source material and decisions, which matters for compliance confidence and internal stakeholder trust.

This “three pillars” framing also helps align leadership. CMOs, CTOs, legal, compliance, and security can agree on policy, process, and platform as they shape and ship AI products safely.

Download the White paper

Start with a bounded scope and controlled knowledge base

During the webinar, we recommended that healthcare teams treat AI pilots as a proof of control, not a proof of intelligence. The more a system is allowed to “fill in the gaps,” the more likely it is to produce confident-sounding output that’s wrong or noncompliant.

We pointed to Mount Sinai research where chatbots were tested with fabricated medical terms. Instead of refusing or asking for clarification, the models confidently elaborated, going so far as to invent diagnostic criteria, treatment protocols, and even medications. It illustrates why “open-ended” experiences can create risk faster than they create value.

A better approach is a pilot designed around constraints:

• Choose valuable, bounded use cases such as content discovery, semantic search, and guided education experiences.
• Restrict outputs to vetted sources that content and compliance teams already manage and review.
• Build in safe failure behavior, including knowing when the AI pilot should say “I don’t know,” rather than improvising.

Thierry also explained retrieval-augmented generation (RAG) in practical terms: the model behaves less like a general-purpose “answer machine” and more like a researcher that can only pull from approved “books on shelves.” If the answer isn’t in the source library, the system should stop, not guess.

Speed and compliance aren’t oppositional, unless the system is designed that way

One insight from the webinar that stood out explained why healthcare teams often hit the brakes: the compliance environment is complex and unforgiving. We dug into the regulatory “minefield” spanning HIPAA, FDA rules, state laws like Washington’s My Health My Data Act, and GDPR.

We referenced a public cautionary example: the World Health Organization introduced an AI assistant, SARAH, that was later flagged for providing incorrect medical guidance, including misstating drug approval status. It’s a useful reminder that even well-intentioned deployments can create credibility and compliance exposure if systems aren’t bounded, monitored, and governed.

The takeaway: design systems so that compliance is achievable at scale. Practically, that means building experiences that:

• stay grounded in approved source content (including approaches like RAG),
• cite sources and enforce boundaries,
• and are designed to fail safely.

Personalization is the holy grail. And the fastest way to break trust.

Vida Health’s CMO offered perspective that sharpened the conversation: personalization remains one of the largest opportunities in digital marketing, and in healthcare it’s also one of the fastest ways to damage trust.

We noted that anonymous browsing patterns on health topics can become protected health information under certain interpretations, which changes how personalization and measurement need to be approached.

The panel also touched on the backdrop many marketing leaders are navigating: recent rulings against tracking users in highly regulated contexts are forcing healthcare organizations to rethink standard digital marketing patterns. How can personalization and recommended content work without relying on sending sensitive data to third parties like Google and Meta?

Responsible personalization can’t be an afterthought. It has to be designed as a trust-centric capability, not a tracking-first tactic.

Start implementing responsible AI

We wrapped the webinar with a rapid-fire action plan the audience could take back to their teams immediately: 

An internal AI usage audit. Map where AI tools are already in use across the organization, including any customer-facing experiences that may have been deployed without broad visibility.

Build a safe place to learn. A staging or sandbox environment on a compliant stack, ideally a close replica of production, where teams can test for safety before anything ships. Just as important, the environment needs a clear rollback path when something doesn’t behave as intended. 

Take an inventory of how the organization or brand is portrayed in AI tools and generative search results. Determine whether that portrayal aligns with marketing plans, brand positioning, and compliance requirements. As noted by Tamara during the webinar, our team at Fueled helps brands navigate this through our AI Brand Visibility Audit, a strategic assessment designed to help organizations understand and manage how they appear in this new search ecosystem.

Treat compliance as a partner, not a blocker. Organizations get to better solutions faster when governance is built in early rather than negotiated at the finish line.

The goal is faster shipping with fewer compliance reversals, and AI experiences that can be measured, traced, and corrected.

Making responsible innovation tangible

AI becomes meaningful in healthcare when it’s paired with systems that make it safe: product governance, experience design, engineering rigor, and infrastructure that supports oversight.

At Fueled, we help healthcare organizations move from experimentation to execution by bringing those disciplines together: secure managed hosting, workflow patterns that support controlled change and reversibility, analytics that demonstrate real impact, and editorial systems that keep human oversight at the center. That’s the thinking behind Assured AI: systems designed not just to generate answers, but to operate with visibility, control, and accountability.

For a deeper look at these takeaways, check out the full webinar. If your healthcare team is exploring how to bring AI into content, infrastructure, or patient-facing experiences responsibly, we’d love to talk.

The post AI in Healthcare Marketing & Content: Takeaways From Our Webinar appeared first on Fueled.

In the increasingly uncommon case where a product is only targeting either iOS or Android, we usually recommend building on native frameworks. However, very often we work with clients to develop cross-platform products where framework selection is more complex.

Cross-platform development toolkits have matured considerably in the last few years, but the decision is still nuanced. The biggest trade-offs are not purely technical, but instead involve factors such as staffing realities, product design and differentiation, and how deep the platform integrations go.

Often, client product teams arrive leaning toward a particular framework. We help validate that instinct by digging into the product roadmap, platform requirements, and the organization’s long-term engineering model while clarifying how the capabilities and tradeoffs of these platforms have evolved in recent years.

We’ve seen cross-platform frameworks unlock real leverage when teams need to ship fast across iOS and Android, but it’s not always a cost-cutting shortcut. The decision of which toolkit to adopt reshapes staffing, governance, and long-term maintenance. Done well, these changes can yield faster releases, fewer parallel roadmaps, and a lower long-term operating burden.

Understanding the contenders

Today’s mobile teams have more architectural options than ever. Cross-platform frameworks promise shared codebases across iOS and Android, while native development continues to offer the deepest integration with each platform.

The ecosystem includes a range of approaches. Frameworks like Ionic or Capacitor extend web applications into mobile environments. .NET MAUI (formerly Xamarin) brings Microsoft’s ecosystem into cross-platform development. Kotlin Multiplatform allows teams to share business logic while keeping fully native interfaces.

In practice, however, most organizations evaluating modern mobile architecture end up comparing three primary paths: Flutter, React Native, and fully native iOS and Android development.

Flutter provides its own UI framework and rendering engine. Teams build interfaces in Dart, and Flutter draws the interface itself rather than relying on each platform’s native UI components. The result is a high degree of visual consistency: one set of UI primitives, one layout model, and a unified approach to animation across iOS and Android.

React Native takes a different approach. Teams build interfaces with React components (using JavaScript or TypeScript), which are translated into native UI components on each platform. In practice, React Native aims to preserve a native feel by leaning on platform UI elements and APIs while still sharing a large portion of application logic.

Native iOS and Android development skips the abstraction layer entirely and builds directly on each platform’s frameworks and APIs (SwiftUI/UIKit on iOS; Jetpack Compose on Android). This remains the most direct path to new OS features and to the conventions that make each platform feel like itself.

These architectural differences shape everything that follows: how consistent the interface can be across platforms, how easily teams access platform-specific features, and how much code can realistically be shared between iOS and Android.

Flutter: Consistency, Control, and Design-Driven Experiences

Flutter is our most common recommendation when a distinctive and compelling UI is a primary differentiator: custom motion, custom transitions, and a unified visual system that needs to stay consistent across iOS and Android over time. That consistency is built into Flutter’s technical architecture: one rendering pipeline and one set of UI building blocks that Flutter controls directly rather than relying on each platform’s native UI components. 

For early-stage teams with clear cross-platform needs, that can translate into faster iteration and fewer parallel implementation decisions, since the UI system is built once and shipped consistently across both platforms.

Flutter’s performance reputation still comes up in some architecture conversations. Early versions of the framework faced criticism around scrolling performance and animation smoothness, and those impressions still linger in parts of the industry. In practice, modern Flutter applications can be extremely performant when built well, and many of the early limitations have long since been addressed.

These strengths are particularly valuable in products where the interface is part of the storytelling or experience.

That was a key reason we built the Meow Wolf app in Flutter. The product called for an interface that masquerades as its own operating system, complete with custom status bar symbols and “applets” that behave like little experiences inside a fictional OS. Flutter let us build that bespoke UI once, then ship it consistently on iOS and Android without “skinning” two separate native toolkits.

The app also had to bridge physical and digital experiences. We used BLE beacon interactions and geofences to detect when someone left an exhibit and then unlock post-visit story and behind-the-scenes content. Where Flutter needed deeper platform hooks, we built native functionality and connected it back through Flutter Channels, including a custom geofence management tool when third-party libraries didn’t meet background-processing requirements.

Another mobile app we chose to build with Flutter is Fennel, a cross-platform investing app we brought to life from the ground up.

The product differentiates itself with values-led decision-making within the user flow, including an ESG (Environmental, Social, and Governance) Wheel that surfaces 200+ ESG data points and shareholder voting that lets investors access and cast votes directly from the app. Flutter gave us a consistent, design-forward UI across iOS and Android while we iterated quickly on a new brand system and feature set.

One consideration organizations should keep in mind is the ecosystem around Dart, Flutter’s programming language. While the language is approachable, it is far less common than JavaScript or TypeScript in most organizations. Teams adopting Flutter often rely more heavily on dedicated Flutter expertise rather than extending an existing internal talent pool.

React Native: Aligning Mobile with the React Ecosystem

React Native often makes the most sense when mobile development needs to align closely with an existing React ecosystem. This is especially common in larger organizations and enterprises where mature web teams, shared design systems, and established engineering workflows already revolve around React and TypeScript, often with existing accessibility standards, analytics patterns, and tooling already in place. React Native can extend that ecosystem to mobile while still building native interfaces.

It’s also worth emphasizing that React Native apps are not simply web applications wrapped in a mobile shell. The framework primarily renders native UI components, even though teams can embed web content where appropriate.

One concrete example is our work with Goosehead Insurance. We chose React Native to align with Goosehead’s existing React-based web platform and deliver a single cross-platform codebase that could scale alongside their enterprise systems and internal expertise. Goosehead’s backend systems centered on Salesforce, so we also built a dedicated API layer (using NestJS) to orchestrate data flow and business logic between the mobile app and Salesforce, while keeping the experience fast and reliable. That architecture supported a customer experience where clients can pull up policy details in seconds instead of waiting on hold.

When the product required truly platform-specific behavior like adding digital insurance cards to Apple Wallet, we implemented targeted native modules in Swift (iOS) and Kotlin (Android) while keeping most of the UI and product logic shared. That hybrid approach matched the organization’s staffing realities and existing tooling, without giving up native fit where it mattered.

In terms of trade-offs, React Native can introduce additional operational complexity in comparison to Flutter, including dependency management, native build toolchains, and ongoing ecosystem upgrades. Performance considerations can also arise from React Native’s architecture, which coordinates UI logic in JavaScript with native platform components.

React Native has improved meaningfully in recent years, including changes to how JavaScript and native code interact. The newer architecture is designed to reduce overhead in communication between those layers, which can improve responsiveness in some situations. However, it isn’t a universal performance fix, and results still depend on how frequently the application needs to coordinate work between JavaScript and native components.

Native: When Platform Capability Matters Most

Native is often right when platform capability is a core constraint or advantage. In practice, this usually happens when platform-specific features begin to dominate the product roadmap.

Of course, if the audience is focused primarily on a single OS, an iOS-first or Android-first native release can be the fastest path to traction, even when a second platform might follow later, once the product proves itself. The same logic applies when the hardware is fixed: an iPad-only field tool, an Android tablet kiosk, or a dedicated device environment where teams need tight control and minimal abstraction.

In cross-platform products, native often becomes the right choice when the app’s roadmap depends heavily on lower-level OS features: complex Bluetooth workflows, background location and geofencing, real-time camera or audio processing, AR frameworks (ARKit/ARCore), biometrics, Apple Wallet / Google Wallet, health integrations, or home-screen widgets. Cross-platform stacks can support many of these, but they often require more native modules and custom edge-case handling, which increases long-term maintenance risk and complexity, and can also introduce performance overhead in demanding scenarios.

Our work with Warby Parker represents a good example of the native advantage. We built the iOS app to feel unmistakably at home on the platform, leaning into iOS interface conventions and interaction patterns rather than forcing a one-size-fits-all UI. On the commerce side, we integrated Apple Pay to make checkout fast and frictionless, which is exactly the kind of system-level capability that’s simplest to implement and maintain when the app is built directly on the platform.

Native development provides the deepest access to platform capabilities, but it also means maintaining two separate codebases and development workflows. This is an intentional trade-off many teams accept when platform capability becomes central to the product.

Choosing the Right Stack

In practice, choosing between these approaches is rarely about which framework is “best.” Instead, the decision often hinges on three factors.

First, the product experience. If a product depends on a highly customized interface or a unified visual system across platforms, Flutter can be a strong fit. Because Flutter controls its own rendering layer, teams can implement complex motion systems and custom UI once and reproduce them consistently across iOS and Android.

Second, product requirements. When the roadmap depends heavily on platform-specific APIs, hardware integration, or system-level features, native development is often the most reliable path forward, even at the cost of maintaining separate implementations across iOS and Android. It allows teams to take advantage of new OS capabilities immediately and maintain experiences that feel fully aligned with platform conventions.

Third, the organizational ecosystem. Teams with established React expertise, shared design systems, and mature web infrastructure may find React Native provides the most development velocity and is a natural extension of how they already work. It empowers web and mobile teams to share patterns, tooling, and development practices while still delivering native-like mobile apps.

In practice, the challenge is balancing these factors against each other. A thoughtful architecture decision is not about chasing a particular framework. It is about choosing the approach that best supports the product, the platform, and the organization behind it.

For teams navigating that decision, we’re always happy to help evaluate the tradeoffs. If your team is weighing different mobile architectures and development approaches and wants a recommendation grounded in roadmap and operating reality, reach out.

The post Choosing the Right Cross-Platform Mobile Technology appeared first on Fueled.

• ClassifAI: Fueled’s AI plugin for WordPress, supporting real-world editorial and publishing workflows since 2018.
• AI Experiments: the official WordPress reference plugin, where Fueled leaders are helping define how AI integrates natively into the CMS.

In their latest releases, ClassifAI and AI Experiments continue to raise the bar for how AI is integrated into WordPress.

ClassifAI: Mature AI capabilities designed for editorial and content teams

Since its launch in 2018, ClassifAI has been built around the realities of modern content operations. It started with capabilities like automatic tagging, image classification, and smarter content connections, and it’s continued to evolve as AI capabilities expanded. Many of the ideas now being explored in the AI Experiments effort trace back to lessons learned while building ClassifAI, years before generative AI became mainstream.

Recent releases reflect the pressures modern publishing teams face: producing more content without sacrificing quality, improving discovery and recirculation across deep archives, and adopting AI in ways that align with privacy, governance, and operational control.

Content generation for editorial workflows

ClassifAI’s content generation features bring AI-assisted writing directly into WordPress, helping editorial teams move faster on the parts of publishing that slow production down:

• Draft and refine faster: accelerate first-pass copy and quick rewrites without leaving the editor.
• Reduce repetitive work: support tasks like short summaries, alternate phrasing, or structure suggestions that otherwise get repeated across teams and channels.
• Keep control in the workflow: generation happens where content is reviewed, edited, and approved, making it easier to apply editorial standards and governance.

For content creators, the impact is practical. Fewer context switches, faster turnaround, and more consistency when multiple teams are producing content at volume.

Just as importantly, generation in ClassifAI pairs naturally with what the plugin has long done well: classification and metadata automation. When WordPress can both help create content and help structure it (through enrichment signals like taxonomy and other organization tools), teams spend less time on manual cleanup and more time on crafting quality content.

Enhanced content recommendations

ClassifAI’s recommendation features surface genuinely relevant related content—supporting editors assembling story packages and powering recirculation modules that keep audiences engaged.

Rather than relying on categories, tags, or manual curation, ClassifAI uses embedding-based matching to identify content related by meaning, not just shared taxonomy. In a large archive, that makes a real difference:

• Better related links and modules, even when taxonomy is inconsistent or content spans multiple beats.
• Stronger recirculation across deep libraries, without requiring editors to hand-curate every connection.

More useful editorial suggestions, because recommendations can reflect topic similarity, not just shared tags.

The result is a more helpful WordPress workflow. Editors get smarter suggestions when building pages, and publishers can improve discovery and internal linking without adding ongoing operational overhead.

Expanded model and platform support, including local and open-source options

Enterprise adoption of AI does not follow a uniform path; each organization operates within its own approved providers, security requirements, and infrastructure constraints. For instance, while some organizations prioritize speed and convenience with hosted providers, others require tighter control over privacy, cost predictability, or infrastructure strategy through self-hosted or local options.

A notable example is support for local and open-source models like Ollama, which can now power features such as the Smart 404 recommendation experience. This flexibility allows organizations to adopt AI-powered recommendations without requiring data to flow through a single hosted provider.

WooCommerce features, robots.txt controls

A few smaller updates include:

WooCommerce product-based title and excerpt generation marks ClassifAI’s first expansion into commerce-oriented workflows. It signals how applied AI can extend beyond editorial publishing into support for product catalogs, merchandising workflows, and commerce-adjacent content operations.

Simple robots.txt controls, providing a clearer path for publishers who want to limit access from common AI scraping bots and better express crawling preferences as governance concerns grow.

How ClassifAI fits into what’s next

ClassifAI began as an independent R&D initiative built to serve evolving client needs and move WordPress forward as a modern platform. Going forward, it will operate in conjunction with and build upon the official WordPress AI initiative.

ClassifAI is expected to evolve in parallel with AI Experiments, incorporating shared infrastructure like the Abilities API and WP AI Client as they mature. Its focus will remain on specialized, enterprise-oriented applications that are unlikely to land in an official reference plugin, including advanced editorial workflows like the smart 404 handling and rule sets developed in partnership with Penske Media.

AI Experiments: A reference model for how AI can integrate into WordPress

AI Experiments is an official project of the WordPress AI Team, chartered to explore and demonstrate how AI can integrate natively into WordPress through reference implementations that can be tested and serve as a model across the ecosystem.

Fueled has played a central role from the project’s inception, moving it from early concepts into practical, testable implementations that reflect real CMS workflows. That leadership is part of a broader commitment to building WordPress itself, and to shaping shared standards that benefit publishers and product teams across the platform.

Expanding experiments beyond title generation

The initial AI Experiments release introduced title generation as a lightweight example of AI embedded directly into the editorial workflow. Since then, the project has expanded into a broader set of reference implementations that demonstrate how AI can enhance core publishing tasks within WordPress.

Content summarization, providing concise summaries that can be reused across experiences and channels.

Featured image generation, enabling teams to explore early approaches to visual ideation inside WordPress.

Alt text generation, supporting accessibility goals while reducing repetitive editorial overhead.

Excerpt generation, supporting faster creation of summaries for archives, newsletters, and distribution workflows.

Collectively, these experiments provide working examples of how AI can integrate into WordPress in editorially useful, workflow-aware, and extensible ways.

And it’s worth reiterating the intent: the AI Experiments plugin is an early-stage project, aimed at both demonstrating and testing WordPress’s new AI capabilities. It’s especially useful for developers and early adopters who want to see how these frameworks work in practice, or explore simple, no-setup enhancements like title suggestions.

Putting WordPress AI into practice

AI Experiments offers a clear window into how WordPress AI is being shaped, providing reference implementations that help establish patterns the ecosystem can build on.

ClassifAI represents the applied counterpart: a production-ready plugin with a broader feature set, proven in demanding content environments where reliability, control, and scalability matter.

Our work bringing AI into WordPress and digital content extends beyond editorial workflows. Recent highlights include AI-enabled improvements to site search through ElasticPress.io that enhance discovery across large content libraries.If your organization is ready to put AI into its content workflows, or your team is developing AI-powered products or integrations for WordPress and needs an experienced partner, reach out.

The post Fueled Leads the Continued Advancement of Applied AI in WordPress appeared first on Fueled.

To help publishers adapt and lead through this change, Fueled and WordPress VIP have released a new white paper: From Pageviews to Product: How Digital Publishers and News Media Thrive as Traffic, Trust, and Revenue Rewire in 2026.

Drawing on our vast experience working with a wide range of publishers — from global brands like The New York Times, Rolling Stone, and POLITICO, to regional and mission-driven newsrooms like CalMatters — this paper lays out six macro trends shaping the future of digital publishing, and provides actionable strategies for navigating them.

Download the white paper

Six Macro Trends Reshaping Publishing in 2026

1. Monetization Models Are Fragmenting

Publishers are reducing reliance on traditional ad models and building revenue portfolios that increasingly elevate subscriptions, affiliate commerce, memberships, events, and even content licensing for AI. The paper explores how leading publishers are using first-party data and flexible monetization tech stacks to rebalance their revenue portfolios, and why the future belongs to publishers who can orchestrate multiple revenue streams effectively.

2. Generative AI Is Transformative

AI is a force reshaping creation, personalization, and discovery, from AI-generated headlines and summaries to “generative engine optimization” (GEO) strategies for visibility in AI-powered search. Discovery is increasingly fragmented, and referral clicks are harder to come by. The paper digs into how AI can increase efficiency while preserving editorial standards, and what it means for referral traffic, audience trust, and content value.

3. More Channels, More Formats

Newsletters, TikTok, YouTube Shorts, podcasts, aggregators, and AI-native feeds have become essential distribution channels. Publishers are also investing in interactive formats like quizzes, polls, games, and calculators to drive engagement and repeat visits. The paper explores how teams are developing platform-native content strategies and CMS infrastructure that support multichannel delivery and scalable content repurposing, to meet audiences where they are and diversify revenue streams.

4. From Reach to Depth

Publishers are investing in first-party relationships: newsletter subscribers, app users, and known audiences they can retain and personalize experiences for. This section outlines strategies for lifecycle marketing, personalization, and community building that deepen engagement and increase retention.

5. Legal and Regulatory Complexity

Privacy laws, accessibility requirements, AI usage rights, and content authenticity standards are now foundational to operating in digital publishing. Beyond risk management, many of these compliance areas overlap with more “spiritual” issues around consumer trust and credibility. The paper outlines the most pressing regulatory shifts and how forward-looking teams are designing compliance into their platforms and workflows from the ground up.

6. Infrastructure Modernization

To keep pace with new channels, content demands, AI capability, and regulatory pressures, publishers are rebuilding their digital foundations. Composable CMS architectures, API-first delivery, and integrated AI tooling are becoming standard. The cost to keep pace with bespoke in-house platforms is higher than ever. Fueled and WordPress VIP bring firsthand perspectives on what modernization looks like in practice, from rethinking editorial workflows and personalization systems to enabling scalable governance around AI and compliance.

Translating Trends Into Action

From Pageviews to Product distills insights from our work with publishers at every scale: from the most recognizable names in global media to emerging digital outlets and regional newsrooms. It reflects how modern publishing organizations are evolving strategically, operationally, and technically to navigate a landscape defined by rapid change.

More than a trends report, this white paper outlines concrete action plans for publishing stakeholders, from editorial to product to revenue, looking to move forward. Each section pairs strategic insight with practical next steps, designed to help teams prioritize, pilot, and build with confidence.

Fueled helps media organizations evaluate their current state and identify the highest-impact opportunities across monetization, content workflows, AI readiness, and platform infrastructure. Whether the focus is near-term optimization, longer-term roadmap, or simply capital investment in CMS and technology, our teams help clarify priorities and build toward what’s next. Let’s talk.

The post White Paper: Digital Strategies for Publishers and News Media as Traffic and Revenue Rewire appeared first on Fueled.

From direct caregivers like hospitals and treatment centers, to healthcare-adjacent nonprofits, publishers, and startups, Digital marketers and product leaders are challenged to integrate AI responsibly, without introducing new risk.

To help bridge the gap between innovation and accountability, we collaborated with experts at WP Engine with experience spanning both healthcare digital marketing and the deployment of AI tooling for websites. The result is a white paper grounded in real-world implementations and shared customer insight. From AI Hype to Assured AI: A Framework for Trust‑Centric Healthcare Digital Marketing & Content introduces a governance-first approach to safely and measurably bring AI into digital experience stacks across healthcare.

Download the white paper

A Framework for Healthcare That Moves Beyond Theory

Assured AI is a practical model shaped by each of our experiences working with healthcare organizations of all sizes, from household-name institutions like Mayo Clinic and Stanford Medicine, to regional providers and advocacy groups like the California Association of Hospitals & Health Systems and Breakthrough T1D. These are organizations where governance, privacy, and public trust are foundational to any digital innovation.

The core idea is simple: Assured AI = Policy + Process + Platform. By making AI features observable, reversible, and auditable from the start, health systems and healthcare marketers can deploy high-impact use cases, from governed chat and semantic search to editorial assistance and personalization, without compromising trust or compliance.

The paper outlines how healthcare organizations can:

• Integrate AI into existing workflows without sidelining human oversight
• Maintain HIPAA, FTC, and emerging state-level compliance across content and tracking
• Keep infrastructure isolated and secure, with the ability to roll back safely when needed
• Provide transparency to visitors: what’s powered by AI, what isn’t, and where the content is sourced from

This is AI architecture designed for how healthcare operates: multidisciplinary, high-stakes, and under scrutiny.

Beyond policy and process, the paper outlines concrete technologies that healthcare organizations can start implementing today. Fueled’s ClassifAI plugin brings governed, in-editor AI capabilities to WordPress environments, with full audit trails and flexibility around model choice. WP Engine’s AI Toolkit introduces scalable features like Smart Search and a managed vector database, designed for retrieval-based AI interactions. Together, these tools help digital teams move from experimentation to measurable, governed deployments that reduce risk and improve the patient experience.

Putting Assured AI into Practice

The white paper outlines a solution architecture informed by real-world work: WP Engine’s secure, managed infrastructure — including multi-environment workflows, rollback support, and an AI toolkit built for scale and governance — paired with Fueled’s governed editorial tooling, digital strategy, and user-centered design expertise. Together, our paper demonstrates how caregivers and healthcare adjacent organizations can move from experimentation to trusted, measurable deployments.

We’ll also be continuing the conversation live in an upcoming webinar hosted by WP Engine, alongside our shared healthcare client Vida Health. WP Engine’s Thierry Muller, VP of AI Products will join Phil Crumm, our Managing Partner for Content Solutions, and Vida Health CMO Tamara Bohlig, to share practical frameworks and real-world insights to help marketing, digital, and IT leaders move confidently from AI hype to AI assurance.

If your healthcare team is exploring how to bring AI into content, infrastructure, or patient-facing experiences responsibly, we’d love to talk.

The post White Paper: A Framework for Trust‑Centric AI in Healthcare Content & Marketing appeared first on Fueled.

Engage is a great fit for smaller sites and growing businesses that want best in class website search, without enterprise-grade pricing. It opens the door for more WordPress sites to offer faster and better search results, scalable performance gains for WordPress and WooCommerce sites with large content and product databases, and AI-powered features like semantic search and search summaries that can provide quick answers.

At $350 for a year, growing e-commerce sites may find that ElasticPress Engage quickly pays for itself, by reducing customer friction and churn, and defraying WordPress hosting costs by offloading the most server intensive operations.

ElasticPress Transforms WordPress Search

At its core, ElasticPress takes over the out-of-the-box WordPress search experience, and plugs it into modern infrastructure that’s dramatically faster, more accurate, and scalable. 

This turbocharged backbone unlocks instant site search and content filtering for visitors, with results that are typo-tolerant, relevancy-ranked, context-aware, and highly customizable by site owners. For WooCommerce-powered stores with a large number of SKUs, ElasticPress can vastly improve product discovery and speed up site navigation and product sorting. 

In the WordPress admin, ElasticPress also takes over complex queries to make managing and navigating product and content libraries more efficient, speeding up site management work and reducing resource-intensive drains on WordPress hosting.

In 2025, we upgraded ElasticPress with an OpenAI integration offering:

• Semantic search capabilities: search results that understand intent and meaning, not just keywords.
• AI-generated answers: no-click-needed summaries in response to informational queries atop search results.

While slated to become core ElasticPress.io features in the future, advanced AI features currently require an OpenAI key, and may incur separate OpenAI API usage fees. 

Learn more about all of the features and capabilities ElasticPress brings to WordPress.

Expanding Access to Modern Search

The previous entry point for our ElasticPress.io plans was $79/month; a price suited to more established publishers and ecommerce stores, or agencies managing multiple environments. The new $29/month Engage plans (with an annual commitment) open up ElasticPress to a much wider market.

Growing WooCommerce stores who want to grow with instant search results and fast filtering that won’t grind the site to a halt.

Marketing and brand sites with tighter budgets that still call out for smarter search results across their content libraries.

Teams experimenting with AI search and answers on a scalable, proven platform.

The Engage plan includes all ElasticPress features, including access to AI capabilities (with an OpenAI API key), for a single site. It doesn’t support staging environments or higher end indexing or search volumes, which we’ve found to be a non-issue for its target audience. 

Try ElasticPress Engage

From improving product filtering, to helping your site affordably scale up to growing demand, to getting visitors quickly to the content and products they’re looking for, to adding AI-powered discovery, our team is excited to expand our reach and turbocharge more WordPress sites.Learn about all of our plans and set up a no-hassle free trial at ElasticPress.io.

The post ElasticPress.io Makes Better WordPress, WooCommerce Search More Affordable with New Plans appeared first on Fueled.

At Fueled, we partner with some of the world’s most recognizable brands as well as ambitious upstarts to make products that don’t just launch, but grow and scale. In a recent Authority Magazine interview, I shared the five principles that have become foundational to how our project teams approach product growth.

These are practical, outcome-driven principles shaped by real-world experience that have included helping companies like Victoria’s Secret and Ikon Pass evolve their digital ecosystems.

1. Solve a Real Problem First

Growth starts with clarity. The most successful products don’t try to be everything to everyone. In plain language, they identify a real customer need and solve it with intention.

At Fueled, we start by listening, and interrogating the premise. What are people actually trying to accomplish? Where are current solutions falling short? Who is being underserved?

Victoria’s Secret Rewards

Victoria’s Secret came to us with a clear opportunity: evolve from transactional marketing toward deeper, loyalty-driven customer relationships. Building a modern rewards program for a brand with over 65 million customers across multiple banners, channels, and experiences required more than a points system.

Our team led the rebrand and redesign of VS Rewards, a digital loyalty program that integrates directly into the e-commerce experience and the Victoria’s Secret mobile app. We designed a clearer, more compelling value exchange, and a loyalty experience that better reflects where the brand is today.

The challenge was retention and re-engagement at scale. The solution was a seamless, meaningful incentive structure designed to create long-term customer value. 

2. Design for Repeat Value

Retention drives growth. While a splashy launch can grab attention, long-term success comes from products designed with habits and repeat value in mind.

We focus on building features and feedback loops that keep customers engaged, whether that’s through fresh content, smart personalization, or evolving utility. From commerce platforms to consumer apps, we think in cycles, not just sprints or launches.

3. Reduce Friction Ruthlessly

Friction is where momentum breaks. Every moment of hesitation or confusion is a risk to conversion, and to loyalty. Great products make it easy, not just to use the product, but to love it.

Ikon Pass Mobile App

We partnered with Alterra Mountain Company to overhaul the Ikon Pass mobile experience: the go-to app for skiers and riders navigating 50+ destinations.

The previous app was underperforming. Our job was to reimagine it as a truly helpful tool across the full customer lifecycle: from pre-season pass activation to on-mountain navigation and trip planning.

We redesigned the onboarding flow, created a dynamic new map experience with real-time lift and trail status, and streamlined access to perks and offers. The result is longer sessions, higher retention, and a 1.5-star jump in the App Store rating.

4. Align Teams Around Outcomes, Not Outputs

Outputs don’t equal impact. Teams often get caught up in delivery velocity, shipping features for the sake of progress. But features don’t matter unless they move real metrics.

At Fueled, we encourage product teams to define what success looks like before scoping a solution. Are we improving conversion? Increasing retention? Reducing churn?

That clarity creates alignment across product, engineering, design, and leadership, and sets the foundation for more meaningful iteration.

5. Use Technology Intentionally — Especially AI

Technology is not the strategy. We’re seeing an acceleration in AI and automation across the product landscape. The question isn’t whether to use these tools, it’s why and how.

Our approach is to apply emerging tech where it solves a real business problem or enhances the customer experience: AI-powered personalization, smarter search, more adaptive content delivery. We don’t treat AI as an add-on. It’s weaved, sometimes invisibly, into products where it can drive real value.

Read the Full Interview

At Fueled, we help ambitious companies build digital products that people return to, talk about, and rely on, and that teams can confidently grow. If you’re looking for a partner to help build and grow what’s next, let’s talk.

The post Driving Product Growth, by Design: a Conversation with Authority Magazine appeared first on Fueled.

AI has saturated every channel with content, options, and noise. What used to signal impact and drive results—volume, speed, scale—now blurs into the background. In this reality, the brands that stand out won’t be the ones producing the most. They’ll be the ones publishing and crafting with the most care.

6 for 2026 is Fueled’s latest report on what’s ahead for digital product, content, and brand strategy. It’s an analytical and cerebral snapshot of the themes I’m tracking as Senior Director of Research & Design, and a provocation to design with more discernment, responsibility, and intent.

1. Selection Beats Scale: Brands built on judgment, not volume, will rise. What matters is knowing what not to say.
2. Personal Systems: Design must support changing contexts, not fixed personas.
3. Artificial Age: In a world of synthetic content, emotional resonance and coherence are what build trust.
4. Attention is Advantage: Attention isn’t just scarce, it’s under attack. The brands that can help people focus and cut down on the noise will have a competitive edge.
5. Optimization is Killing Us: Real-life flows aren’t neat and linear. The most impactful experiences will be less rigid and more forgiving.
6. From Human-Centered to Life-Centered: Brands that don’t only speak to impulsive and immediate individual needs, but appeal to a larger purpose and impact on the world around them will do well.

The report unpacks each trend, offers real-world examples of brands who are getting it right, and lays out concrete recommendations. It’s a call for a refreshed approach in an increasingly complex world.

The post From More to Meaningful: 6 Shifts Reshaping Content & UX Strategies appeared first on Fueled.

On the surface, it’s a beautifully designed recipe app. Underneath, it’s a clear example of how Fueled’s heritage in mobile product design and 10up’s legacy in publishing platforms, structured content, and WordPress combined to create something stronger than either could have built alone: a standout experience already earning praise for its polish and utility.

Good Housekeeping UK came to us with a clear opportunity: bring their library of more than 4,000 triple-tested recipes to life in a mobile experience designed for everyday use. The challenge wasn’t just technical. It meant rethinking how long-form editorial content gets structured and surfaced in a format built for utility. It meant designing an experience that felt fast, polished, and intuitive — all within the constraints of a hybrid platform. And it meant coordinating teams across time zones and disciplines, something our teams have spent years getting right.

The new Good Housekeeping Kitchen app brings swipe-to-discover recipes, a step-by-step Cooking Mode, and smart personalization into a seamless mobile experience, powered by real-time content from Good Housekeeping’s WordPress-powered website. It gives editors the flexibility to shape what’s featured and when from inside WordPress, and gives cooks an app that feels personal, not generic.

And we delivered it with less than 600 hours of work.

The result is a product that feels as trustworthy and approachable as the brand behind it. A tool designed not just to showcase content, but to support the everyday act of making something good. It’s a model of what happens when editorial vision, technical depth, and product design are aligned from the start, and it’s proof that thoughtful, cross-disciplinary work can still move fast.

Check out the app on iOS or Android, read the story behind it, and get cooking.

The post The New Good Housekeeping App Showcases Fueled’s Unified Expertise appeared first on Fueled.

At Fueled, we’ve learned that the most effective research isn’t siloed at the start of a project. It’s embedded into every phase of project delivery and iteration. My new white paper, Beyond Handoffs: Making Research a Core Design Capability, explores the shift from traditional research phases to a continuous model where insights are delivered throughout.

Research That Moves With the Work

Traditional UX research phases often follow a waterfall model: research happens, then design begins, then engineering. But that structure assumes that everything we need to know to deliver the optimal outcome can be discovered before design even starts. In practice, that’s rarely the case.

Instead, our team has adopted a Just Enough Research approach, inspired by Erika Hall’s book of the same name: do just enough discovery to inform the first design sprint, then continue to test, iterate, and refine as the product takes shape. It’s faster, more responsive, and leads to better outcomes.

In our most effective engagements, user research and design are paired from day one, working in tandem through iterative cycles and experimentation. Daily insight drops from research inform ongoing creative exploration, allowing the team to evolve the product without delays or rework.

For example, in a recent project for a nationwide insurance agency, early data showed that visitors were abandoning the flow during the initial quote. Rather than spend weeks upfront hypothesizing why in the abstract, we embedded research into the sprint cycle focused on onboarding, alongside design and engineering. We did “just enough” upfront research, via early interviews, to uncover that asking for personal information, like phone number or home address, too early in the flow was a turn-off.

Designers proposed an update with reordered questions, leading with more innocuous prompts like ZIP code and vehicle type. Engineering made the change, while our researchers studied the real world impact. 

Even micro-copy mattered. Phrases like “coverage exclusions may apply” were found to create confusion and erode trust. In testing proposed design changes, customers responded far more positively to plainspoken language like “this policy doesn’t cover flood damage” — a change that made them feel confident and informed.

These changes emerged not from a massive preliminary research phase, but from small, embedded touchpoints throughout the project.

Integration Doesn’t Mean Inflation

One misconception we often face is that continuous research means more time or budget. But in practice, it means redistributing the same time and resources more effectively. Rather than burning through 100 hours in a single upfront phase, we distribute those hours across the life of the project. We test hypotheses in the moment, in context, and in a way that actually de-risks the work and is more efficient.

This approach not only improves velocity, it also empowers teams to make smarter design decisions in the moment, not just in retrospect. It means fewer expensive course-corrections down the line, and more confidence at every review. 

Knowing When to Go Deep

There are still moments where a more traditional discovery phase makes sense. Some clients, like government agencies or regulated industries, need an extensive upfront understanding of their ecosystem before design can begin. 

In one recent project with a state labor department, our team led a six-month research engagement to help the client understand how to serve a complex user base, spanning multiple languages, access levels, and legal requirements.

These deep dives remain valuable. But even in those contexts, we look for ways to test interactions as the design takes shape, whether it’s validating the path to an application or improving the clarity of eligibility requirements. The point is not to abandon early research entirely; it’s to stop treating research practices as something that stops and starts between building phases.

Making Research a Core Design Capability

As Fueled’s Senior Director of Research and Design, bringing these disciplines closer together has become a central focus. We’re building a model where insight and intuition move in lockstep, sprint by sprint. The result is a design practice that moves faster, builds smarter, and connects more meaningfully with the people our clients serve.

Our new white paper, Beyond Handoffs: Making Research a Core Design Capability, offers a blueprint for UX and design leaders looking to bring this mindset to their teams. From rituals to research operations, it details how we make this approach work across engagements large and small.

If you’re looking for a partner who builds digital products grounded in evidence, designed to perform, and built to resonate, get in touch.

The post White Paper: Delivering Better Products Faster with Continuous Research appeared first on Fueled.

At this time of year, as we celebrate the holidays and prepare for a new year, clients doing socially consequential work that builds a better future for all are top of mind. One such client project is One Small Step, an initiative from longtime client StoryCorps that invites Americans with differing political beliefs to sit down for a recorded conversation, not to debate, but to listen. The goal isn’t to agree, but to understand. That mission has felt especially resonant lately, and it’s why I wanted to learn more about the impact One Small Step is having, one conversation at a time.

I sat down with Jonathan Webster, Managing Director of the One Small Step initiative, to spotlight the work his team is doing, why civic bridge-building and connection matters, and how our team at Fueled has helped to make their growing reach possible.

Q&A with Jonathan Webster, Managing Director of One Small Step

Fueled: To start, for those who aren’t familiar, can you introduce StoryCorps and the One Small Step initiative?

Jonathan: StoryCorps archives the stories of everyday Americans for storage in perpetuity at the Library of Congress, and has done so for over 20 years. In that time, StoryCorps has created the single largest collection of human voices anywhere on the planet.

One Small Step is one of several initiatives, and it focuses on bringing Americans back together by forming human connections across lines of difference, with the goal of turning down the temperature and reinforcing the reality that Americans are capable of having these conversations.

We’re invited into communities where people take a courageous step into these spaces, and we have the receipts to show people can—and do—connect across political differences. Listening to them is hopeful. The vulnerable sharing of personal experience, the “why” behind what someone believes, builds authenticity and human empathy. It’s not a message that gets reinforced often. 

Fueled: We’d love to hear a story about a particularly memorable conversation or connection!

Jonathan: One story that jumps to mind is from Columbus, Georgia. We met two gentlemen, Wane, the former president of the local NAACP chapter, and Alton, the former Party Chair of the local Republican party. They were vaguely aware of each other, and likely saw each other as counterforces. We brought them into a one-on-one conversation that starts with personal storytelling and empathy. Through the process, they made a connection, understood each other’s roots in the community, and discovered striking similarities. They became friends and have had several conversations since!

Fueled: What role does digital play in supporting the One Small Step program?

Jonathan: One Small Step originally started with a model of live, facilitated conversations. Facilitators are experts at inviting people into vulnerable spaces and navigating the conversation. But it isn’t as scalable, and there’s also an accessibility component; people need to be able to do this whenever and wherever they can. As demand increased nationally, and as it became increasingly important for our national wellbeing to expand the program’s reach, we needed a way to enable the experience digitally. 

Now, One Small Step is entirely digital first. When someone comes into the program, they can easily sign up and step through an online workflow that gathers their information and begins the matching process. 

Of course, our web presence helps to explain our story and purpose, and amplify the reach of our most inspiring stories. But most significantly, our digital platform automates the experience by providing matches, enabling people to reach out, chat, and schedule a conversation at scale. It’s a guided space, and also a brave space, and it’s a digital community we’re creating in direct partnership with Fueled. 

Fueled: What role has Fueled played in that digital transformation journey?

Jonathan: Fueled was critical from the outset in helping lay the foundation, shaping the process and user journey, and making a big undertaking more approachable. We did workshops to refine the overall objective and break it down into a more specific game plan, including how this would fit into StoryCorps’ broader ecosystem. And of course, implementation and build.

Our collaboration continues beyond just site maintenance, including meaningful refinements to the interface based on data, and developing a more flexible algorithm to drive matches based on what we’re learning about which matches lead to the most successful outcomes.   

Fueled: Heading into the holidays, certainly a time when connection and community tends to be on the mind, what would you like people to know, and what can they do to support your mission?

Jonathan: The holidays can be a difficult time for mental health and loneliness. In many ways, what we’ve built here is a tool for human connection. The community coming in the door is incredibly diverse, but unified by empathy, a service orientation, and a commitment to the idea that this experience is valuable. 

If someone is looking for a channel for human connection during the holidays, or just believes in the power of speaking to those we might not normally share a space with, there’s a whole community of people out there who want to connect across differences. Come to us. We’ll help make those connections and put people into a space for a meaningful conversation and practice. You can go to TakeOneSmallStep.org, go through the sign-up process, and we’ll provide matches as soon as possible. 

Start Connecting 

Our team feels incredibly inspired and privileged to support One Small Step in an increasingly critical mission to bring more people together. For anyone looking to participate in the program, or simply be inspired by some of the constructive conversations they’ve shared, you can:

For teams interested in building digital experiences that make participation easier, broaden reach, and support a mission at scale, we’d love to chat.  

The post “One Small Step” Brings Diverse Perspectives Together Through Dialog appeared first on Fueled.

To demonstrate how these tools can work in practice, the WordPress AI team, led by contributors from Automattic, Google, and Fueled, introduced an early working build of the AI Experiments plugin. Fueled led the design and development of version 0.1, defining its product direction and engineering implementation.

This plugin not only adds practical applications of AI into the WordPress UI, but models how AI ought to be integrated into WordPress going forward, leveraging these new and official building blocks.

A real-world showcase for creators and developers

The AI Experiments plugin serves two key purposes. First, it offers editorial features that solve common publishing problems in a simple and seamless way. Second, it provides developers and product teams with a working reference for how to build using new and official AI frameworks.

Each feature (or “experiment”) added to the plugin is meant to be used by content teams, but also studied by developers. For example, the plugin illustrates how to use the WP AI Client to call external LLMs, which removes the need for developers to include their own external service connection code within their plugins or other custom AI integrations. The experiments plugin also acts as a proving ground for the architecture itself, helping improve the very tools it’s built on.

The plugin’s launch feature, title generation, integrates directly into the post title field in the block editor. With one click, editors are offered a set of suggested titles generated by AI from the content. These suggestions aim to improve clarity, tone, or engagement, depending on what the editor is looking for. It’s designed to be intuitive: no configuration, model selection, or extra UI. Just helpful suggestions, right where they’re needed.

More experiments are on the way. Features planned for for future releases include:

• Contextual tagging
• Content summarization
• Excerpt generation
• Alt text suggestions
• Image generation

These are the kinds of baseline capabilities we expect in a modern CMS like WordPress. Rather than having dozens of third-party plugins trying to solve the same problem, the larger goal is to offer a single, trusted approach that handles the basics well. That frees up the broader ecosystem — agencies, plugin developers, and enterprise teams — to focus on more innovative or specialized AI use cases, while minimizing end user confusion and complexity.

From ClassifAI to Core

Many of the ideas being explored in AI Experiments have roots in our work on ClassifAI, our open source plugin we released years before ChatGPT or generative AI became mainstream. From automatic tagging to image classification and smart 404 suggestions, ClassifAI has long served as a proving ground for what responsible, editorially useful AI can look like inside the CMS.

ClassifAI was an R&D project built to meet the evolving needs of our clients, and to help move WordPress forward as a modern platform. We’re now bringing that experience directly to the core AI effort, helping to shape shared standards and accelerate progress across the ecosystem.

Looking ahead, we expect ClassifAI to evolve in parallel with the official tools, incorporating shared infrastructure like the Abilities API and WP AI Client as they mature. Its focus will remain on more specialized applications of AI for enterprise use cases, such as the smart 404 handling and editorial rule sets we developed in partnership with Penske Media, going beyond the scope of what’s likely to be included in an official plugin.

Start using AI inside WordPress

The AI Experiments plugin is an early-stage project, aimed at both demonstrating and testing WordPress’s new AI capabilities. It’s a useful tool for developers and early adopters who want to see how these frameworks work in practice, or explore simple, no-setup enhancements like title suggestions.

For teams looking for a mature, production-ready solution with a richer feature set, ClassifAI remains the more complete option today. It’s stable, well-supported, and already in use across high-scale editorial environments.Want to explore what’s possible today, or contribute to what’s next? Check out the plugin, or get in touch to talk through your needs.

The post Making AI Experiments: The Official Reference Plugin for WordPress AI appeared first on Fueled.