Growth is different for all people, and it’s defined by the choices we make every day to learn, adapt, and lead. As part of our Growth for Everyone profile series, we’re excited to showcase the career journey of Oana Solyom, a Lead Business Consultant, who truly embodies continuous growth and learning.

Her path, from game testing to leading in anatomical pathology, serves as a reminder that growth often begins with curiosity and a willingness to explore new horizons. Whether guiding development teams in Romania, shaping product features for a global healthcare client, or diving into complex regulatory frameworks, Oana brings passion, precision, and a deep sense of purpose to her work.

READ MORE: Learn About Perficient’s Award-Winning Growth for Everyone Initiative

A Career Sparked by Curiosity and a Drive to Build

Before entering software development, Oana found her passion rooted in the mechanics of technology and the thrill of creation. She began her professional journey immersed in the interactive realm of video games.

“I’ve always been drawn to the more technical side of things, even before I worked in software. I started as a game tester because I play a lot of video games. I wanted to play video games for a living, but I really liked being part of creating something.”

This early role as a game tester ignited a deeper ambition: to build tangible digital experiences. Oana soon combined this drive with a desire to learn more about the field of medical software. The opportunity at a small medical software startup allowed her to create impactful solutions that directly help people. “When I found out about the medical field, I was super excited about being a part of creating medical software and devices. I think this is impactful because all the software really helps people.”

The startup environment provided Oana with the flexibility to explore various roles. During her eight years before joining Perficient, she became a Test Lead and then took on system design and product strategy. Currently, she is a Lead Business Consultant at Perficient supporting our product development teams in Romania and serves as a product owner for her client. Her growth stemmed from hands-on learning and an advanced understanding of the healthcare industry.

“It was just a step-by-step thing. From testing, I found out I could do more. I became a Product Owner, and now I’m on the Product Management team.”

Oana supports three development teams in Romania, collaborating closely with her client in a combined product ownership and product management capacity. She defines features, maintains quality, and aligns releases with business goals. Her journey exemplifies continuous evolution, driven by a passion for building impactful solutions.

“The thing I enjoy the most is the creative side of the process because I have to think about users constantly, including how they would feel about a new feature, how they would handle it, and how they would use it. I also enjoy problem solving, like figuring out how to make most people happy and ensuring that teams succeed when problems arise during development.”

READ MORE: Discover Product Development Insights from Our Colleagues

Powering Innovation in Healthcare: Oana’s Anatomical Pathology Project Work

Oana’s work focuses on improving workflows in anatomical pathology laboratories, which handle the critical steps of specimen processing before diagnosis. Anatomical pathology involves analyzing physical specimens, managing samples, and processing data efficiently.

There are four main areas of focus in anatomical pathology:

1. Tracking and maintaining an accurate record of specimen samples
2. Improving patient custody by reducing errors and minimizing mislabeling risk
3. Providing actionable data and insights into lab operations
4. Streamlining processes to increase efficiency

By optimizing the pre-digital (analytical) phase in her project work, Oana ensures a strong foundation for accurate digital diagnostics processing. She works on a specimen tracking system for path lab, an informatics and workflow solution that streamlines specimen tracking, labeling, and case management. The benefits include increased efficiency, reduced errors, better resource management through real-time analytics, and faster turnaround times.

READ MORE: Learn How Perficient Is Powering Digital Pathology Data and Workflows

Understanding the Connection Between Anatomical and Digital Pathology

Digital Pathology is a rapidly evolving area of medical technology that combines imaging, software, and Artificial Intelligence (AI) to improve diagnostic accuracy and efficiency. This builds on anatomical pathology by transforming the tissue samples tracked for diagnosis into high-resolution images for AI-assisted interpretation. The digitized slides are applied to AI algorithms where they are flagged for potential issues and reviewed for diagnostic errors. This evolution makes diagnosis faster and more accurate.

Oana helps shape software that makes complex pathology workflows simple and intuitive for clinical teams. For eight years, Oana has supported a critical project for anatomical pathology labs through product ownership, which includes preparing new features and the next steps for a product release.

Extensive self-study proved to be most beneficial to the project, revealing that every lab operates differently and requires adaptable workflows. Guided by a customer-first mindset, her career reflects a commitment to trust and alignment with user interests and product success.

“At the end of the day, the people who will be using our software are going to be the ones most impacted by the choices we make. I think that mindset has brought me to where I am today. I want my team to succeed because their success means success for both us and the client in delivering great results. I put customers first, and that gives our clients more trust in us.”

EXPLORE MORE: Perficient is Leveraging AI-Driven Product Development to Accelerate Innovation

Driving Impact and Achieving Milestones

Oana and her dog, Sylvie.

Oana is a proactive force in her own career development and a significant contributor to her projects. Each year, she sets personal goals and shares them with her manager, creating a shared understanding of her ambitions. One significant milestone was her rapid advancement to Product Owner. While serving as a Requirements Manager, she set an ambitious five-year goal to become a Product Owner and achieved it in just two years.

Her rapid move into a strategic role – typically reserved for client-side specialists –underscores her commitment to growth. Oana’s accomplishment highlights her dedication, including extensive self-study and learning about areas like histopathology labs and customer visits, even if they are not part of her daily responsibilities. She also took courses with scaled agile training, as well as a course on design thinking, to support the teams that she partners with and meet the requirements for successful delivery. Earning that level of confidence and responsibility marked a major personal achievement.

Beyond her personal milestones, Oana’s impact extends through her dedication to process improvement and deep knowledge:

• Process Implementation: A strong advocate for efficient processes, Oana and her team participated in a transition from waterfall to agile methodology for feature definition, significantly enhancing delivery and flexibility.
• Extensive Knowledge and Support: Oana’s comprehensive product expertise and willingness to offer support across various areas, including regulatory affairs, make her a sought-after resource, greatly contributing to the product’s success.

Growth Through Exploration: Learning, Adapting, and Owning the Journey

Oana’s career growth has been significantly shaped by her willingness to explore new areas and take initiative. What began as a testing role evolved into a deep dive into product development, driven by her curiosity and desire to contribute more meaningfully. As she transitioned into systems design and product ownership, she studied complex medical workflows, regulatory requirements, and agile methodologies.

For those early in their careers or considering a shift, Oana offers valuable advice:

• Keep your options open: Oana emphasizes exploring all opportunities within a project or company as you might discover a passion for something unexpected.
• Explore beyond your first role: She initially planned a career in testing but found her true calling in product development, realizing she wouldn’t have been as happy staying on a purely technical path.
• Approach conflict resolution pragmatically: When problems arise, Oana assesses the impact and determines necessary sacrifices, whether it is time, scope, or the team’s workload. She focuses on measuring the outcome to decide the best approach and accepts that perfect solutions aren’t always possible.

In her experience, growth comes from staying curious, adaptable, and taking ownership of your development.

Finding Balance and Fulfillment Beyond the Screen

Outside of work, Oana finds balance in the simple things—reading, gaming, and spending time with her dog, Sylvie. These moments help her stay grounded and energized.

Oana’s journey, from game tester to a leader in product development, is a powerful reminder that growth doesn’t always follow a straight line. It’s about being open to change, embracing new challenges, and finding fulfillment in both your work and your personal life. Her evolution reflects what’s possible when you lead with curiosity and commit to continuous learning.

MORE ON GROWTH FOR EVERYONE

Perficient continually looks for ways to champion and challenge our workforce, encourage personal and professional growth, and celebrate the unique culture created by the ambitious, brilliant, people-oriented team we have cultivated. These are their stories.

Learn more about what it’s like to work at Perficient on our Careers page. Connect with us on  LinkedIn here.

In today’s marketing landscape, speed and precision aren’t luxuries—they’re expectations. Real-time engagement has become the baseline, and marketers need tools that can respond the moment a customer acts.

Having worked across a range of marketing automation platforms, I’ve seen how each handles this challenge differently. What stands out in Dynamics 365 Customer Insights – Journeys is how it brings real-time responsiveness and data-driven decision-making into a single, unified flow without excessive workarounds or patchwork integrations.

This post shares how real-time journeys can simplify campaign delivery, improve timing, and enhance how teams design and manage customer experiences, particularly when the pressure is on to scale fast and stay compliant.

Why Real-Time Journeys Are a Game Changer

In many traditional platforms, journey logic runs on scheduled evaluations or requires syncing data between systems. Real-time journeys flip that: they listen to user actions as they happen and respond without delay.

This means cleaner architecture, less manual upkeep, and better alignment between marketing and sales.

Key Advantages

Event-Based Triggers That Actually Work

Form submissions, link clicks, custom interactions—they all kick off journeys in real time. No batch processing or lag.

Segmentation That Doesn’t Live in a Silo

Unlike other tools where segmentation often lives outside the campaign builder, CIJ uses unified Dataverse data. I can build segments based on behaviors, preferences, and even CRM activity without exporting lists or building middle-layer syncs.

Clear, Flexible Branching

From a user experience standpoint, the journey builder is intuitive but also powerful. I can design complex logic with conditions, delays, and channel preferences, and the flow stays clean and understandable.

Built-In Consent Management

Compliance and consent aren’t afterthoughts. They are built into every journey. This simplifies cross-channel delivery while keeping you on the safe side of privacy regulations.

Channel-Ready (and Expandable)

Out of the box, you can orchestrate journeys across email, SMS, push notifications, and even custom channels if needed.

Example Use Case: Real-Time Inquiry Follow-Up

Let’s say you work for a university admissions team. Your marketing strategy includes a lead form where prospective students can request information about academic programs. These inquiries need to be followed up quickly and efficiently—ideally with personalized communication and a clear path toward scheduling a campus visit.

Here’s how a real-time journey in Dynamics 365 could automate that experience:

• A student fills out the “Request Info” form on your website
• Within seconds, they receive a personalized email acknowledging their request
• If they click a specific CTA (like “Schedule a Visit”), they’re routed into a journey branch that sends visit prep material
• If they don’t click after 2 days, they receive a gentle follow-up email
• Behind the scenes, the contact’s record is updated, and an alert is logged in CRM for the admissions advisor

No manual intervention. No delays. No data syncing. Just a clean journey that responds to interest in real time, while keeping your team informed.

Why This Matters

If you’re in marketing ops or campaign strategy, real-time journeys simplify things you’ve likely hacked together before:
– Real-time reactions without external tools
– Unified data access without integration overhead
– Journey paths that are scalable, visual, and respectful of consent

This isn’t just a shift in tooling. It’s a shift in how we build customer experiences.

Final Thought

With real-time journeys, I’m not just building email campaigns. I’m designing responsive experiences that meet users where they are. If you’ve worked with other automation platforms, you’ll feel the difference right away.

Perficient is proud to be named a Major Player in the IDC MarketScape: Worldwide Experience Build Services 2025 Vendor Assessment (Doc #US52973125, October 2025) and IDC MarketScape: Worldwide Experience Design Services 2025 Vendor Assessment (Doc #US52973225, October 2025). These IDC MarketScapes assessed providers, offering a comprehensive framework including product and service offerings, capabilities and strategies, and current/future market success factors.

“We believe being recognized by IDC for Experience Design and Experience Build reinforces the impact we have on behalf of clients creating personalized, seamless interactions that accelerate growth. In today’s experience-driven economy, that’s the competitive advantage that matters,” says Erin Rushman, general manager of digital marketing and experience design operations at Perficient.

What This Inclusion Means for Perficient

Being named a Major Player, we believe, underscores our dedication to transforming customer experiences and empowering businesses through personalized, seamless, and impactful interactions. Perficient combines strategy and research with human-centered design to help organizations craft agile, customer-focused solutions that thrive in dynamic markets. By leveraging data-driven insights, personalization, AI, and more, we deliver end-to-end experiences that deepen engagement and drive measurable business impact.

According to the IDC MarketScape for Experience Design Services, “Perficient has strong capabilities in digital offering design and offers leading-edge experience design services backed by a global innovation network.” The report also notes, “In conversations with Perficient’s reference clients, the three areas where experience design services buyers commended the vendor highly were for the quality of its professionals, for its industry specific capabilities, and differentiation as a vendor.”

The IDC MarketScape for Experience Build Services states, “As an independent digital experience agency, Perficient combines business and technology transformation capabilities, including a robust collection of supporting assets and tools, with a focus on the design and build of customer experiences. Perficient has strong personalization capabilities.”

Additionally, Perficient was named a Major Player in the IDC MarketScape for Customer Experience Strategy Consulting Services 2025 Vendor Assessment (Doc #US52973025, September 2025). We believe this inclusion reflects our commitment to delivering AI-first solutions that transform customer experiences through scalable, high-impact innovations. It establishes Perficient as a trusted partner, driving unmatched success in the experience-driven market of tomorrow.

Read the News Release: Perficient Named a Major Player in Three IDC MarketScapes For AI-First Approach to Customer Experience

What This Inclusion Means for Our Clients

Perficient continues to be a leader in experience strategy and design, helping clients align vision, accelerate innovation, and achieve lasting transformation. We enable businesses to embed AI into processes and deliver personalized customer experiences at scale. By expanding and strengthening alliances with partners, we ensure our solutions remain innovative and leading-edge, empowering clients to stay ahead in a dynamic market.

Exceptional CX is essential for growth and loyalty. Our expertise across platforms and global delivery ensures brands can quickly adapt, innovate, and meet rising customer expectations. Explore our expertise to see how we can be a partner in your experience journey.

Nowadays, a person cannot live without some interaction with artificial intelligence, ranging from mobile apps to enterprise tools that use data and algorithms to help businesses make better decisions. What exactly are the main types of AI workloads? Let’s break them down in simple terms using real examples:

Natural Language Processing: How AI Understands Human Language

NLP is the name given to computers reading, understanding, and responding to human language.

Real-Life Examples

• Chatbots: Customer support bots reply to your queries instantly.
• Sentiment Analysis: AI shows brands whether posts on social media mention them positively or negatively.
• Language: Tools like Google Translate convert text between languages.

Computer Vision: Teaching Machines to See

With Computer Vision, machines can comprehend and interpret images and videos much like humans do.

Real-Life Examples

• Facial Recognition: Unlock your phone with your face.
• Object Detection: Self-driving cars identify pedestrians and traffic signs.
• Medical Imaging: This application enables doctors to detect diseases in X-rays or MRI scans using AI.

Predictive Models: AI Capable of Predicting the Future

Predictive models use historical data to predict future outcomes.

Real-Life Examples

• Sales Forecasting: Businesses predict monthly revenue.
• Fraud Detection: Banks detect suspicious transactions.
• Customer Churn Prediction: Companies predict which customers are likely to leave.

Conversational AI: Smart Chatbots & Virtual Assistants

Conversational AI is the technology behind systems that enable machines to have conversations with you in natural language.

Real-Life Examples

• Azure Bot Service: Customer support.
• Cortana: Virtual assistant provided by Microsoft.
• Customer Service Bots: You know, those helpful chat windows on websites.

Generative AI: Creating New Content with AI

Generative AI generates new text, images, or even code from learned patterns.

Real-life Examples

• GPT-4: can write blogs, answer questions, and even help with coding.
• DALL-E: Creates striking images out of textual prompts.
• Codex: Computer code from natural language instructions

Why Understanding AI Workloads Matters

Artificial Intelligence is no longer relegated to the pages of science fiction; it’s part of our daily lives. From Natural Language Processing powering chatbots to Computer Vision enabling facial recognition, and from Predictive Models forecasting trends to Generative AI creating new content, these workloads form the backbone of most modern AI applications.

A proper understanding of these key AI workloads will help businesses and individuals leverage AI to improve efficiency, enhance customer experience, and remain productive in a digitally evolving world. Whether you are a technology-savvy person, a business leader, or just an inquisitive mind about AI, knowing these basics gives you a clear picture of how AI is shaping the future.

Additional Reading

• What is Artificial Intelligence (AI)? / Blogs / Perficient
• What is Microsoft Copilot Studio? / Blogs / Perficient

At Sitecore Symposium 2025, the Women in Digital panel delivered a powerful discussion on what it means to lead through transformation in today’s rapidly shifting digital landscape. The conversation centered on how women leaders navigate disruption from pandemic pivots to the rise of AI while scaling trust, driving innovation, and fostering inclusion.

Featured Panelists:

• Sarah Hamilton, SVP Performance Marketing, Sitecore
• Amanda Murawski, Executive Director of Web Strategy, Embry-Riddle Aeronautical University
• Molly Schnagl, Owner, Tomegan Marketing Group

Megan Mueller Jensen, Senior Solutions Architect in Perficient’s Sitecore practice moderated the panel. MJ guided the conversation with a series of thought-provoking questions on emerging technologies, balancing innovation with daily operations, mentorship and inclusivity, and empowering women to lead confidently in an evolving digital landscape.

Embracing Change as a Constant

The panel emphasized that change is inevitable and often uncomfortable. From pandemic-driven shifts to remote work to today’s rapid adoption of AI, leaders must normalize uncertainty and frame it as an opportunity for growth. Establishing routines, maintaining structure, and leaning on community support were highlighted as essential strategies for sustaining productivity and well-being.

Building Resilient Teams Through Empathy

A central theme: human-first leadership. The pandemic underscored the importance of checking in on people—not just projects. Sarah shared a favorite saying that really resonated with me, “We’re all in different boats, but in the same storm.”

Small gestures, like personal notes or care packages, can go a long way toward building trust and loyalty during challenging times. Creating psychological safety, plus offering resources such as coaching and peer mentoring, remains critical for supporting whole-person growth and retention.

Strategic Imperative for Women Leaders:

Digital transformation isn’t just about technology—it’s about people. Leaders who combine empathy with innovation will not only navigate disruption but set the standard for inclusive, future-ready organizations.

Navigating the AI Revolution with Confidence

AI dominated the conversation as both a disruptor and an enabler. While concerns about job security are real, the panel encouraged viewing AI as a tool that automates low-value tasks and frees teams to focus on strategic work. Sarah reminded attendees, that AI has been around since 1956 and that “marketing is about people relating to people and not just selling products.” She added that she learned a lot more from talking with customers at Sitecore Symposium than from any database or data set.

Leaders were encouraged to promote curiosity, integrate learning into work hours to prevent burnout, and communicate openly about both opportunities and concerns.

Supporting Women Through Life’s Complexities

The panel addressed the realities of managing teams balancing demanding careers with other priorities outside of work. Amanda shared the importance of getting to know your staff and looking at them as friends. She said leaders “…have to acknowledge that there is a life outside of work and that affects how you show up.” Take the opportunity to learn about your people.

Flexibility emerged as a retention strategy, supported by micro-moments of connection such as informal check-ins and weekly newsletters. Organizations that offer compassion during personal crises see loyalty and performance soar. As Molly shared, offering grace during difficult life moments pays dividends: people “show up stronger…come back and are higher producers.”

Next Steps for Industry Leaders

1. Identify low-value tasks ripe for AI automation.
2. Create learning pathways for emerging tech within business hours.
3. Audit your team’s psychological safety and support systems.
4. Build a culture of flexibility and trust to retain and grow future female leaders.

Let’s Continue the Conversation

We’re grateful to our partners at Sitecore for helping bring this impactful discussion to the Symposium community. It was wonderful to see both familiar and new faces this year! We left the breakfast inspired and energized.

Thank you to our panelists, attendees, and to our friends at Sitecore for making this event a success and a true highlight of Perficient’s presence at Symposium. We look forward to continuing these important conversations and supporting each other in our digital journeys.

See you at Sitecore Symposium 2026!

In recent years, the evolution of React Server Components (RSCs) has signaled a dramatic shift in the way developers approach front-end architecture. By moving key rendering tasks to the server, RSCs promise not only to reduce the size of client-side JavaScript bundles but also to improve initial load times and overall user experience. This article looks at how React Server Components have changed. It looks at common design patterns, how they work better, and what could go wrong. With anecdotal evidence from industry case studies and practical code examples, intermediate developers will gain insights into how RSCs are being adopted in production environments and why they matter in today’s fast-paced web landscape.

1. Common Design Patterns Demonstrated in React Server Components

React Server Components introduce a new set of design patterns that capitalize on streaming, suspense, and data fetching—all while reducing the client-side footprint. Several battle-tested patterns have emerged as reliable blueprints for implementing RSCs in production.

Stream the Shell and Hydrate the Islands

One effective pattern is to stream a “shell” of the page immediately while using placeholders (Suspense boundaries) for parts of the UI that fetch data at a slower pace. This approach allows users to see the basic layout instantly, while interactive “islands” are hydrated incrementally as data becomes available. This method creates the perception of speed and dramatically reduces initial load times.

Filesystem-Based Routing and Granular Error Boundaries

Frameworks like Next.js leverage the app directory to automatically treat components as server components by default, providing a powerful mechanism for filesystem-based routing. This design pattern not only simplifies error handling by providing natural error boundaries but also integrates suspense boundaries seamlessly. Here, each route becomes self-contained and can fetch its own data without affecting the global bundle size.

Server Actions for Data Mutations

Server Actions are an emerging pattern that allows developers to push mutations directly to the server. Using the “use server” directive, form submissions or interactions such as button clicks trigger server-side functions without bundling additional client-side JavaScript. This can lead to thinner client bundles and ensures that sensitive credentials remain securely on the server.

Direct Data Fetching in Server Components

Traditional approaches require fetching data on the client or through additional API endpoints. RSCs, however, allow direct data fetching on the server side using familiar APIs (such as fetch or axios). For example, a practical guide demonstrated using a Server Component to fetch a list of blog posts from a mock API—a technique that drastically simplifies the data-access pipeline and reduces other layers of complexity.

Hybrid Component Models: Balancing Static and Interactive Elements

A key best practice is to limit the number of interactive components and keep non-interactive elements as server components. This hybrid approach ensures minimal client-side code while preserving necessary interactivity via client components (triggered with “use client”). By carefully demarcating which elements require hydration and which do not, developers can optimize performance without sacrificing functionality.

2. Performance Wins and Trade-offs

React Server Components offer significant performance benefits—but these gains come with trade-offs that must be understood and managed.

Reduction in JavaScript Bundle Size

By shifting the rendering logic to the server, RSCs inherently reduce the amount of JavaScript sent to the client. This reduction has measurable impacts: in one case study, a reduction of up to 62% in JavaScript bundle size was observed, enabling sites to render almost three times faster than traditional client-rendered solutions.

Faster Initial Load and Improved INP

Metrics such as Largest Contentful Paint (LCP) and Interaction to Next Paint (INP) benefit significantly from the server-first approach. When the client receives pre-rendered HTML without heavy hydration, the time-to interactive state shrinks considerably. One notable example saw INP drop from approximately 250 milliseconds to just 175 milliseconds, which directly improves user responsiveness and overall satisfaction.

Streaming and Suspense for Incremental Rendering

Streaming of server-rendered HTML using Suspense reduces perceived delays by allowing parts of the page (the shell) to render immediately while data is loaded in the background. This granular rendering approach ensures that even lengthy data-fetching operations do not block the display of critical UI elements. The trade-off, however, is that developers must design their component hierarchy carefully to ensure that suspense boundaries are embedded granularly and logically consistent.

Trade-Offs When Mixing Client and Server Components

Although the promise of RSCs is substantial, their benefits are most evident when the application is architected with a clear division between server and client responsibilities. If an application is a tangled mix of both—where expensive client-side code is intermingled with server-rendered content—the anticipated performance gains may be negated. Furthermore, improper handling of shared dependencies can lead to larger-than-expected client bundles, undermining the primary benefit of using RSCs.

Table 1: Comparative Analysis of Rendering Approaches in React Applications 

Code Example: A Simple Blog Post List

Below is an example of a Server Component fetching data from an API, showcasing how RSCs can reduce the client-side payload:

// app/components/BlogPostList.jsx
"use server";

interface Post {
  id: number;
  title: string;
  body: string;
}

async function getBlogPosts(): Promise<Post[]> {
  try {
    const response = await fetch("https://jsonplaceholder.typicode.com/posts", {
      next: { revalidate: 3600 }, // Cache for 1 hour
    } as any);
    if (!response.ok) {
      throw new Error("Failed to fetch posts");
    }
    return response.json();
  } catch (error) {
    console.error("Error fetching blog posts:", error);
    return [];
  }
}

export default async function BlogPostList() {
  const posts = await getBlogPosts();
  return (
    <div>
      <h2>Blog Posts</h2>
      <ul>
        {posts.map((post) => (
          <li key={post.id}>
            <h3>{post.title}</h3>
            <p>{post.body}</p>
          </li>
        ))}
      </ul>
    </div>
  );
}

Code Example: Server Component for Fetching and Displaying Blog Posts

3. Potential Pitfalls and Challenges in Production

Despite the promise of React Server Components, developers should be aware of several challenges and pitfalls when deploying RSCs in production.

Mixing Client and Server Components

One of the most common pitfalls is an improper mix of client and server components. Since RSCs do not ship interactivity by default, overusing client components can negate performance benefits. Developers must therefore be judicious in marking components as “use client” and ensure that only essential interactive parts are hydrated on the client side.

Shared Dependencies and Bundle Bloat

When server and client components share large dependencies, those libraries may still end up in the client bundle. This occurs when a client component inadvertently imports a module used by a server component, resulting in unnecessary code duplication on the client. Refining the granularity of your components and managing dependencies carefully are critical to avoiding this pitfall.

Granularity of Components

Breaking down the UI into too many small server components can lead to increased network traffic, as each component may trigger individual data fetching and serialization. While component reusability is a strong suit of React, over-fragmentation needs to be balanced with performance considerations. Developers should strive for an optimal balance between component granularity and efficient rendering.

Handling Data Serialization

Data passed from server components to client components must be serializable to JSON. Complex objects, functions, or non-enumerable properties can lead to runtime errors or performance bottlenecks. It is advisable to pass only essential and simple data structures between components.

Managing Server Actions

While Server Actions offer a powerful alternative to traditional client-side state management and API calls, they introduce new architectural dimensions. Ensuring fast round-trip times and providing immediate user feedback (such as with loading states or optimistic UI updates) is crucial. Server Actions should be used mostly for non-critical interactive elements where the delay is imperceptible; otherwise, excessive round-trip delays can undermine the user experience.

Table: Real-World Performance Metrics Comparison

Table 2: Comparative Performance Metrics from Real-World Case Studies.

Conclusion

The evolution of React Server Components in production represents a significant leap forward in frontend architecture. Developers can now enjoy reduced JavaScript bundle sizes, faster initial load times, and a more responsive user experience—all achieved by moving the heavy lifting to the server while strategically hydrating only the parts of the UI that require interactivity.

React 19 was released on 25 April 2024 and it is based out of React 18. This release introduces major improvements and removes some features to enhance developer experience and application performance. Migrating is a straightforward approach, but you need to watch for removed features. In this blog, I share my experience in migrating React to version 19.

Key Features added in React 19

1. Optimized Concurrent Rendering:React introduced concurrent rendering in version 18. In React 19, they further improved it by scheduling algorithm dynamically to adapt user interactions.

const root = ReactDOM.createRoot(document.getElementById('root'));
root.render(<App />, { adaptiveScheduling: true });

2. New Hooks introduced

• • useActionState -> Update state based on the result of form submission.
  • useFormStatus -> Gives status information of the last form submission.
  • useOptimistic → Lets you  to optimistically update the UI.

3. Actions API: React introduced Actions to handle mutations and state updates. It acts as an async function that gets called on form submission.

Deprecations & removals to consider

• React removed String Refs. Use callback refs or createRef instead.
• createFactory, render, element.ref and ReactDom.hydrate were removed.
• React removed propTypes and defaultProps from package.

Step by step instructions for React 18 to 19 migration

Step1: Audit packages

Audit your package.json file and ensure it supports React 19. If not, upgrade the packages to the supported version.

Note: It is highly recommended to keep packages with the latest version.

Npm run audit

Step2: Update React version

npm install react@^19.0.0 react-dom@^19.0.0

Step3: Run Codemods

npx codemod@latest react/19/migration-recipe

Codemods will update the following

• Replace ReactDOM.render with createRoot or hydrateRoot.
• Convert String refs to callback refs or useRef.
• Remove legacy Context APIs (contextTypes, getChildContext).

Step4: Address breaking issues

• We used Material UI, where Grid2 was not supported. We switched from Grid2 to Grid.
• React removed String Ref, so we replaced it with createRef.
• We upgraded to the modern Context API like createContext and contextType.

Step5: Test and validate the application

Run the application and test the end-to-end flow. Look for performance, server-side rendering, lazy loading impacts as well.

Step6: Post migration cleans up

Update lint/eslint rules according to react 19.Remove unused imports and packages. Add dev notes for the breaking issues to faced/resolution took while migrating

Reference:

1. React 19 Upgrade Guide – React
2. Built-in React Hooks – React
3. React 18 to 19 Migration – Codemod.com

Large language models are powerful communicators but poor historians — they generate fluent answers without guaranteed grounding. Retrieval‑Augmented Generation (RAG) is the enterprise-ready pattern that remedies this: it pairs a retrieval layer that finds authoritative content with an LLM that synthesizes a response, producing answers you can trust and audit.

How RAG works — concise flow

• Index authoritative knowledge (manuals, SOPs, product specs, policies).
• Convert content to searchable artifacts (text chunks, vectors, or indexed documents).
• At query time, retrieve the most relevant passages and pass them to the LLM as context.
• The LLM generates a response conditioned on those passages and returns the answer with citations or source snippets.

RAG architectures — choose based on needs

• Vector-based RAG: semantic search via embeddings — best for unstructured content and paraphrased queries.
• Retriever‑Reader (search + synthesize): uses an external search engine for candidate retrieval and an LLM to synthesize — balances speed and interpretability.
• Hybrid (BM25 + embeddings): combines lexical and semantic signals for higher recall and precision.

Practical implementation checklist

• Curate sources: prioritize canonical documents and enforce access controls for sensitive data.
• Chunk and preprocess: split long documents into meaningful passages (200–1000 tokens) and normalize text.
• Select embeddings: evaluate cost vs. semantic fidelity for your chosen model.
• Tune retrieval: experiment with top‑k, score thresholds, and reranking to reduce noise.
• Prompt engineering: require source attribution and instruct the model to respond “I don’t know” when evidence is absent.
• Maintain pipeline: set reindex schedules or event-driven updates and monitor for stale content.

Risks and mitigations

• Stale or incorrect answers: mitigate by frequent reindexing and content versioning.
• Privacy and IP exposure: never index PII or sensitive IP without encryption, role-based access, and auditing.
• Hallucinated citations: enforce a “source_required” rule and validate citations against the index.
• Cost overruns: optimize by caching commonly used contexts, batching queries, and using smaller models for retrieval tasks.

High-value enterprise use cases

• Sales enablement: evidence-backed product comparisons and quoting guidance.
• Customer support: first-response automation that cites KB articles and escalates when required.
• Engineering knowledge: searchable design decisions, runbooks, and architecture notes.
• Compliance and audit: traceable answers linked to policy documents and evidence.

Metrics that matter

Measure accuracy (user-verified correctness), time-to-answer reduction, citation quality (authoritativeness of sources), user satisfaction, and escalation rate to humans. Use these to iterate on retrieval parameters, prompt rules, and content curation.

Example prompt template

“You are an assistant that must use only the provided sources. Answer concisely and cite the sources used. If the sources do not support an answer, respond: ‘I don’t know — consult [recommended source]’.”

Conclusion

RAG converts LLM fluency into enterprise-grade reliability by forcing answers to be evidence‑based, auditable, and applicable. It’s the practical pattern for organizations that need fast, helpful automation without fiction — think of it as giving your model a librarian and a bibliography.

Automation has become a core part of modern work, allowing teams to reduce repetitive tasks, save time, and improve accuracy. Whether it’s generating weekly reports, organizing files, processing large amounts of data, or interacting with web applications, automation helps individuals and companies operate more efficiently. Among all programming languages used for automation, Python is one of the most widely adopted because of its simplicity and flexibility. 

Why Python Is Perfect for Automation 

Python is known for having a clean and readable syntax, which makes it easy for beginners to start writing scripts without needing deep programming knowledge. The language is simple enough for non-developers, yet powerful enough for complex automation tasks. Another major advantage is the availability of thousands of libraries. These libraries allow Python to handle file operations, manage Excel sheets, interact with APIs, scrape websites, schedule tasks, and even control web browsers – all with minimal code. Because of this, Python becomes a single tool capable of automating almost any repetitive digital task. 

What You Can Automate with Python 

Python can automate everyday tasks that would otherwise require significant manual effort. Simple tasks like renaming multiple files, organizing folders, or converting file formats can be completed instantly using small scripts. It is also commonly used for automating Excel-based workflows, such as cleaning datasets, merging sheets, generating monthly summaries, or transforming data between formats. Python is equally powerful for web-related automation: collecting data from websites, making API calls, sending automated emails, downloading content, and filling out online forms. For more advanced uses, Python can also automate browser testing, server monitoring, and deployment processes. 

Setting Up Your Python Automation Environment 

Getting started is straightforward. After installing Python, you can use an editor like VS Code or PyCharm to write your scripts. Libraries required for automation can be installed using a single command, making setup simple. Once you have your environment ready, writing your first script usually takes only a few minutes. For example, a short script can rename files in a folder, send an email, or run a function at a specific time of the day. Python’s structure is beginner-friendly, so even basic programming knowledge is enough to start automating everyday tasks. 

Examples of Simple Automation 

A typical example is a script that automatically renames files. Instead of renaming hundreds of files one by one, Python can loop through the folder and rename them instantly. Another example is an automated email script that can send daily reminders or reports. Python can also schedule tasks so that your code runs every morning, every hour, or at any time you choose. These examples show how even small scripts can add real value to your workflow by reducing repetitive manual tasks. 

Best Practices When Building Automation 

As you begin writing automation scripts, it helps to keep the code organized and reliable. Using virtual environments ensures that your project libraries remain clean. Adding error-handling prevents scripts from stopping unexpectedly. Logging enables you to track what your script does and when it executes. Once your automation is ready, you can run it automatically using tools like Task Scheduler on Windows or cron on Linux, so the script works in the background without your involvement. 

How Companies Use Python Automation 

Python automation is widely used across industries. IT teams rely on it to monitor servers, restart services, and handle deployment tasks. Business teams use it to generate reports, clean data, update dashboards, and manage document workflows. Marketing teams use automation for scraping competitor information, scheduling social media posts, or tracking engagement. For developers, Python helps with testing, error checking, and system integration via APIs. Across all these areas, automation improves efficiency and reduces human error. 

Conclusion 

Python is an excellent starting point for anyone who wants to begin automating daily tasks. Its simplicity, combined with its powerful ecosystem of libraries, makes it accessible to beginners and useful for professionals. Even basic automation scripts can save hours of work, and as you grow more comfortable, you can automate more complex processes involving data, web interactions, and system management. Learning Python for automation not only makes your work easier but also adds valuable skills for professional growth. 

For organizations still running Adobe Experience Manager (AEM) on premises, the decision to modernize your digital experience platform is no longer a question of if, but how. As digital expectations accelerate and MarTech stacks evolve, staying on legacy infrastructure can limit your ability to innovate, scale, and compete. While replatforming to a new CMS may seem tempting, migrating to Adobe’s cloud-native AEM as a Cloud Service (AEMaaCS) offers a smarter, future-proof path forward.

Cloud Isn’t Just a Cost, It’s a Multiplier

At first glance, cloud migration may appear to be a significant investment. But when you factor in the total cost of ownership of on-prem infrastructure—hardware, maintenance, upgrades, security, and downtime—the economics shift. AEMaaCS eliminates the need for costly version upgrades and reduces operational overhead through auto-scaling, automated updates, and built-in security.

Replatforming to a new CMS may seem like a fresh start, but it often comes with hidden costs: retraining teams, rebuilding integrations, and losing years of content and customization. Adobe’s cloud offering allows you to preserve your investment in AEM while unlocking new efficiencies.

Architecture That Scales With You

AEMaaCS is built on a modern, containerized, microservices-based architecture that supports continuous delivery and scalability. Unlike monolithic on-prem deployments, Adobe’s cloud service is designed for agility, enabling faster deployments, real-time updates, and seamless integration with Adobe’s broader Experience Cloud ecosystem.

This architecture also supports global delivery with built-in CDN capabilities, ensuring performance and reliability across regions. For enterprises with complex digital footprints, this is a game-changer.

Innovate Without Rebuilding

One of the biggest risks of replatforming is the time it takes to regain momentum. With AEMaaCS, you can innovate faster by leveraging Adobe’s AI-powered features like Smart Tags, Content Automation, and personalization tools, all without waiting for the next upgrade cycle.

Adobe’s roadmap is tightly aligned with the future of digital experience: composable architecture, headless content delivery, and AI-driven insights. Migrating to AEM as a Cloud Service ensures you’re not just keeping up, you’re staying ahead.

Future-Proofing Your MarTech Stack

Adobe’s cloud-native platform is designed to integrate seamlessly with other Adobe Experience Cloud solutions like Adobe Analytics, Target, and Journey Optimizer. This alignment enables unified data, consistent customer journeys, and faster time-to-value across your marketing stack.

Choosing a different CMS could introduce integration challenges, data silos, and a fragmented customer experience. AEMaaCS offers a cohesive foundation that supports your long-term digital strategy.

Perficient Named as a Major Player for Worldwide Adobe Experience Cloud Professional Services |Learn More

The Cost of Charting a New Course

Replatforming to a non-Adobe CMS may seem like a clean break, but it often leads to unexpected complexity. You’ll need to rebuild your content models, rewire your integrations, and retrain your teams. Worse, you risk losing the deep Adobe expertise and ecosystem advantages you’ve built over time.

In contrast, migrating to AEMaaCS allows you to evolve without disruption. You retain your content, components, and workflows while gaining the benefits of a modern, cloud-native platform.

Evolve, Don’t Abandon

The future of digital experience is agile, intelligent, and cloud native. Adobe has made it clear that AEMaaCS is the strategic direction for the platform, with continuous innovation and support focused there. For existing AEM customers, the smartest move isn’t to start over; it’s to evolve.

By migrating to Adobe’s cloud, you’re not just upgrading your infrastructure; you’re unlocking a platform that’s built for what’s next.

Your map to smoothly migrating to AEM as a Cloud Service | Learn More

Ready to Evolve Your AEM Platform?

We’ve seen it all. With years of experience implementing Adobe solutions across industries, our team knows what it takes to migrate from AEM on-prem, Adobe Managed Services, or even a different platform entirely. In fact, we led the first large-scale customer deployment to AEM as a Cloud Service.

Whether you’re looking to modernize your infrastructure, reduce technical debt, or unlock new capabilities, we can help you make the move with confidence. Talk to our Adobe experts to get started.

For years, developers have debated whether PHP is on its way out. With newer languages gaining traction, the question persists: Is PHP dead? The reality is more complex. PHP remains a cornerstone of web development, but its role has shifted as competitors emerge.

PHP by the Numbers

• 74% of websites with a known server-side language still run on PHP as of July 2025.
• WordPress, Drupal, Magento, and Facebook continue to rely heavily on PHP.
• Packagist, the PHP package repository, now hosts over 400,000 packages, showing strong community engagement.

These statistics alone prove that PHP remains a cornerstone of web development.

Why PHP Is Still Relevant

• Continuous Updates: PHP 8.4 was recently released, introducing async-friendly features and performance improvements.
• Framework Ecosystem: Popular frameworks like Laravel and Symfony keep PHP modern, offering elegant syntax and robust tooling.
• CMS Dominance: WordPress, which powers over 40% of all websites, is built on PHP. As long as WordPress thrives, PHP will remain indispensable.
• Adaptability: PHP has shown resilience by evolving with trends such as cloud-native development, AI integration, and microservices.

The Competition Factor

• It’s true that JavaScript (Node.js), Python, and Go have gained traction for modern web apps. They often appeal to startups and developers seeking cutting-edge solutions.
• However, PHP’s low barrier to entry, massive ecosystem, and proven scalability make it hard to replace entirely.

The Future of PHP

Looking ahead, PHP is expected to:

• Embrace async programming for better scalability.
• Integrate more seamlessly with AI-driven applications.
• Continue powering enterprise-level CMS and e-commerce platforms.

Rather than dying, PHP is quietly evolving to meet the demands of modern web development.

Conclusion

PHP is not dead—it’s alive, evolving, and still dominant. While newer languages may capture the spotlight, PHP’s widespread adoption, active community, and adaptability ensure it remains a vital part of the web’s backbone.

So, the next time someone asks “Is PHP dead?”, the answer is simple: No, it’s still kicking—and powering most of the internet.

A health insurance model built for yesterday won’t meet the demands of today’s consumers. Expectations for seamless, intuitive experiences are accelerating, while fragmented systems continue to drive up costs, create blind spots, and erode trust.

Addressing these challenges takes more than incremental fixes. The path forward requires breaking down silos and creating synergy across plans, while aligning technology, strategy, and teams to deliver human-centered experiences at scale. This is more than operational; it’s strategic. It’s how health insurers build resilience, move with speed and purpose, and stay ahead of evolving demands.

Reflecting on recent industry conversations, we’re proud to have sponsored LeadersIgnite and the 2025 Inter-Plan Solutions Forum. As Hari Madamalla shared:

“When insurers share insights, build solutions together, and scale what works, they can cut costs, streamline prior authorization and pricing, and deliver the experiences members expect.”– Hari Madamalla, Senior Vice President, Healthcare + Life Sciences

To dig deeper into these challenges, we spoke with healthcare leaders Hari Madamalla, senior vice president, and directors Pavan Madhira and Priyal Patel about how health insurers can create a competitive edge by leveraging digital innovation with inter-plan collaboration.

The Complexity Challenge Health Insurers Can’t Ignore

Health insurance faces strain from every angle: slow authorizations, confusing pricing, fragmented data, and widening care gaps. The reality is, manual fixes won’t solve these challenges. Plans need smarter systems that deliver clarity and speed at scale. AI and automation make it possible to turn data into insight, reduce fragmentation, and meet mandates without adding complexity.

“Healthcare has long struggled with inefficiencies and slow tech adoption—but the AI revolution is changing that. We’re at a pivotal moment, similar to the digital shift of the 1990s, where AI is poised to disrupt outdated processes and drive real transformation.” – Pavan Madhira, Director, Healthcare + Life Sciences

But healthcare organizations face unique constraints, including HIPAA, PHI, and PII regulations that limit the utility of plug-and-play AI solutions. To meet these challenges, we apply our PACE framework—Policies, Advocacy, Controls, and Enablement—to ensure AI is not only innovative but also rooted in trust. This approach ensures AI is deployed with purpose, aligned to business goals, and embedded with safeguards that protect consumers and organizations.

Still, technology alone isn’t enough though. Staying relevant means designing human-centered experiences that reduce friction and build trust. Perficient’s award-winning Access to Care research study reveals that friction in the care journey directly impacts consumer loyalty and revenue.

More than 45% of consumers aged 18–64 have used digital-first care instead of their regular provider, and 92% of them believe the quality is equal to—or better.

That’s a signal healthcare leaders can’t afford to ignore. It tells us when experiences fall short, consumers go elsewhere, and they won’t always come back.

For health insurers, that shift creates issues. When members seek care outside your ecosystem, you risk losing visibility into care journeys, creating gaps in data and blind spots in member health management. The result? Higher costs, duplicative services, and missed opportunities for proactive coordination. Fragmented care journeys also undermine efforts to deliver a true 360-degree view of the member. The solution lies in intuitive digital transformation that turns complexity into clarity.

Explore More: Empathy, Resilience, Innovation, and Speed: The Blueprint for Intelligent Healthcare Transformation

Where Inter-Plan Collaboration Creates Real Momentum

When health plans work together, the payoff is significant. Collaboration moves the industry from silos to synergy, enabling human-centered experiences across networks that keep members engaged and revenue intact.

Building resilience is key to that success. Leaders need systems that anticipate member needs and remove barriers before they impact access to care. That means reducing friction in scheduling and follow-up, enabling seamless coordination across networks, and delivering digital experiences that feel as simple and intuitive as consumer platforms like Amazon or Uber. Resilience also means preparing for the unexpected and being able to pivot quickly.

When plans take this approach, the impact is clear:

• Higher Quality Scores and Star Ratings: Shared strategies for closing gaps and improving provider data can help lift HEDIS scores and Star Ratings, unlocking higher reimbursement and bonus pools.
• Faster Prior Authorizations: Coordinated rules and automation help reduce delays and meet new regulatory requirements like CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F).
• True Price Transparency: Consistent, easy-to-understand cost and quality information across plans helps consumers make confident choices and stay in-network.
• Stronger Member Loyalty: Unified digital experiences across plans help improve satisfaction and engagement.
• Lower Administrative Overhead: Cleaner member data means fewer errors, less duplication, and lower compliance risk.

“When plans work together, they can better serve their vulnerable populations, reduce disparities, and really drive to value based care. It’s about building trust, sharing responsibility, and innovating with empathy.” – Priyal Patel, Director, Healthcare + Life Sciences

Resilience and speed go hand in hand though. Our experts help health insurers deliver both by:

• Designing for agility with composable architectures, MVP+ delivery models, and intelligent automation that accelerates time-to-value while maintaining regulatory integrity.
• Aligning digital transformation with value-based care goals, enabling organizations to shift from volume to value through strategic investments that integrate cloud platforms, interoperable systems, and advanced analytics.
• Operationalizing AI responsibly to support equitable, secure, compliant, and scalable AI adoption.

This approach supports the Quintuple Aim: better outcomes, lower costs, improved experiences, clinician well-being, and health equity. It also ensures that innovation is not just fast, but focused, ethical, and sustainable.

You May Also Enjoy: Access to Care is Evolving: What Consumer Insights and Behavior Models Reveal

Accelerating Impact With Digital Innovation and Inter-Plan Collaboration

Beyond these outcomes, collaboration paired with digital innovation unlocks even greater opportunities to build a smarter, more connected future of healthcare. It starts with aligning consumer expectations, digital infrastructure, and data governance to strategic business goals.

Here’s how plans can accelerate impact:

• Real-Time Data Sharing and Interoperability: Shared learning ensures insights aren’t siloed. By pooling knowledge across plans, leaders can identify patterns, anticipate emerging trends, and act faster on what works. Real-time interoperability, like FHIR-enabled solutions, gives plans the visibility needed for accurate risk adjustment and timely quality reporting. AI enhances this by predicting gaps and surface actionable insights, helping plans act faster and reduce costs.
• Managing Coding Intensity in the AI Era: As provider AI tools capture more diagnoses, insurers can see risk scores and costs rise, creating audit risk and financial exposure. This challenge requires proactive oversight. Collaboration helps by establishing shared standards and applying predictive analytics to detect anomalies early, turning a potential cost driver into a managed risk.
• Prior Authorization Modernization: Prior authorization delays drive up costs and erode member experience. Aligning on streamlined processes and leveraging intelligent automation can help meet mandates like CMS-0057-F, while predicting approval likelihood, flagging exceptions early, and accelerating turnaround times.
• Joint Innovation Pilots: Co-development of innovation means plans can shape technology together. This approach balances unique needs with shared goals, creating solutions that cut costs, accelerate time to value, and ensure compliance stays front and center.
• Engaging Member Experience Frameworks: Scaling proven approaches across plans amplifies impact. When plans collaborate on digital experience standards and successful capabilities are replicated, members enjoy seamless interactions across networks. Building these experiences on solid foundations with purpose-driven AI is key to delivering stronger engagement and loyalty at scale.
• Shared Governance and Policy Alignment: Joint governance establishes accountability, aligns incentives for value-based care, and reduces compliance risk while protecting revenue.

Success in Action: Empowering Healthcare Consumers and Their Care Ecosystems With Interoperable Data

Make Inter-Plan Collaboration Your Strategic Advantage

Ready to move from insight to impact? Our healthcare expertise equips leaders to modernize, personalize, and scale care. We drive resilient, AI-powered transformation to shape the experiences and engagement of healthcare consumers, streamline operations, and improve the cost, quality, and equity of care.

• Business Transformation: Activate strategy for transformative outcomes and health experiences.
• Modernization: Maximize technology to drive health innovation, efficiency, and interoperability.
• Data + Analytics: Power enterprise agility and accelerate healthcare insights.
• Consumer Experience: Connect, ease, and elevate impactful health journeys.

We have been trusted by the 10 largest health systems and the 10 largest health insurers in the U.S., and Modern Healthcare consistently ranks us as one of the largest healthcare consulting firms.