Sivakumar Sivaraman

🚀 Excited to share my latest blog on the MuleSoft site: “Beyond the Hype: Build a Practical AI Gateway with MuleSoft.” In this post, I cover how to make AI secure, governed, and cost-efficient by: ✅ Applying authentication & rate limiting ✅ Securing prompts with PII redaction ✅ Routing requests to the right AI models

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Shantanu Narayen’s 18 year tenure as CEO at Adobe is a reminder of how rare long-term stewardship has become in Silicon Valley. During his time with the company, the company’s stock increased more than 6x and its business model fundamentally changed. The most important decision of his tenure was moving Adobe from selling boxed software like Creative Suite to a subscription platform through Creative Cloud. At the time it was controversial. Today, it is considered one of the most successful SaaS transitions in the history of enterprise software, turning Photoshop, Illustrator, and Acrobat into one of the most profitable recurring software ecosystems ever built. The respect he commands across the industry says a lot about how difficult that transformation actually was. Microsoft CEO Satya Nadella even posted publicly congratulating Narayen on a “legendary run,” praising both his leadership and the way he expanded what creators and businesses could do with software. In an industry that is often intensely competitive, that kind of recognition from peers is not given lightly. There are only a few CEOs in the world who truly get to define one era of software and then help set the stage for the next. Narayen did it by turning Adobe into a SaaS powerhouse. However, the next leader will have to answer a harder question. What does a creative software company look like when AI becomes part of the creative process itself? #Adobe #Leadership #SaaS #AI #Technology

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Is the initial rush with AI finally over? Are we finally realizing that LLMs are not a panacea for all problems? Has "generative AI aura" begun to fade?

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What if your homepage hero optimized itself automatically? AEM <> Decisioning Recipe #1 Retail: Let AI Show Each Visitor the Best Homepage Experience One of the most powerful capabilities in Adobe Journey Optimizer Offer Decisioning is letting AI choose the best experience automatically. Combined with AEM + structured content, marketers can simply add content while the system continuously optimizes the experience. Here’s the pattern. 1️⃣ Create the Placement (AJO) Create a web placement representing the location of the experience. Example: Placement: Homepage Hero • Channel: Web • Content type: HTML / JSON • Location: Homepage hero slot 2️⃣ Create the Decision Create a decision that returns the best offer. Example: Decision: Homepage Hero Decision The decision evaluates: • Audience eligibility • Business rules • AI ranking 3️⃣ Generate the Surface / Decision Scope Example: web://luma/homepage/hero This identifier is used by the experience layer to request the decision. 4️⃣ Configure the AEM Page (one-time setup) Example page properties: Container ID: hero-container decisionScope/surface: web://luma/homepage/hero Offer Type: Single Show/Hide Div: Show Div The AEM<>Decisioning Accelerator reads this config and: • Calls Offer Decisioning • Retrieves the best offer • Renders it in the hero • Falls back to default if needed After this setup, developers rarely touch the page again. 5️⃣ Create Offers in AEM Offers are built in Experience Fragments (XF): • Designers create hero variants • Firefly / GenAI can generate imagery • Layout stays brand consistent When published, XFs automatically generate Content Fragment representations. 6️⃣ AJO Consumes the AEM Content Through the AEM ↔ Offer Decisioning integration, these appear in the AJO Offer Library. Marketers can: • Select offers • Add them to a collection • Use the collection in the decision 7️⃣ Let AI Choose the Best Offer Enable AI ranking in the decision. Offer Decisioning evaluates signals like: • Profile attributes • Audience membership • Behavior signals • Engagement history Result: Every visitor can see a different homepage hero optimized for performance. Why this matters Traditional personalization requires ongoing development cycles. With AEM + Offer Decisioning + structured content, personalization becomes: • Content-driven • AI-optimized • Marketer-controlled Coming next in the Recipe Series • AI Powered Personalized Product Grid Array • Loyalty-tier personalization • Geo-aware homepage experiences • Cart-abandonment rescue offers Powered by AEM <> Decisioning Accelerator — enterprise personalization in weeks, not months. ::: #AdobeExperienceManager #AdobeJourneyOptimizer #Personalization #MarTech #AIinMarketing

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New whitepaper from engineers at Alluxio & Salesforce just published! In this whitepaper, Venkata Pradeep Panchumarth and Sreeram Garlapati from #Salesforce; David Zhu, Yuyang Wang, and Bin Fan from #Alluxio explains how distributed cache delivers the same low latency I/O performance compared to AWS S3 Express One Zone with much lower costs. Read now to save now: https://lnkd.in/gdbKwtxS

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Excited to be part of AI+ Renaissance. Personally, I believe we are at an inflection point. AI is no longer about copilots that assist. It is about agents that act. Systems that reason across ambiguity. Systems that operate inside real business workflows. At Rippling, we are building AI into the operating rhythm of HR, payroll, and finance. Not as a feature. Not as a demo. But as production infrastructure. The hard problems now are not model quality. They are agency, control, verification, and trust. Looking forward to pushing this conversation forward with others who are building for reality, not hype.

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18 Years of Vision: A Reflection on an Era at Adobe After 18 years at the helm, Shantanu Narayen has decided to step down as CEO of Adobe. 18 years is more than a tenure. It’s an era. When he became CEO in 2007, Adobe looked very different. Software came in boxes. Products were sold once. Updates arrived every few years. Then came a bold decision that many doubted. Adobe moved from boxed software to the cloud. Photoshop. Illustrator. Premiere Pro. All transitioned to Creative Cloud, turning a traditional software company into a subscription-driven platform. At the time, it looked risky. Today, it’s taught in business schools. During those years, Adobe didn’t just evolve its products. It reshaped its identity. Revenue grew from roughly $3B in 2007 to over $23B+ annually. Adobe expanded from creative tools into digital marketing and customer experience platforms. Its market value climbed from about $20B to hundreds of billions at its peak. But perhaps the bigger transformation was cultural. Adobe stopped thinking like a product company. It started thinking like a platform for creators and businesses worldwide. And now, as Narayen steps aside, Adobe stands at another turning point. Artificial Intelligence. Generative tools. Creative automation. New ways of building, designing, and telling stories. The next chapter will be written in AI. But the foundation of that chapter was built over the last 18 years. Leadership transitions are often described as endings. But the best ones feel more like passing the baton in the middle of a race. Because companies like Adobe don’t move in decades. They move in eras. And this was one of them. ​Shantanu Narayen's 18-year journey at Adobe is a testament to his exceptional leadership, vision, and dedication. He has transformed Adobe into a global powerhouse, and his impact on the creative and technology industries will be felt for years to come. As we pay tribute to his remarkable tenure, we can look forward to seeing what the future holds for Adobe under his continued guidance. The question now isn’t just who becomes the next CEO. It’s: What will the next 18 years of creativity look like? #Leadership #Adobe #Innovation #TechnologyLeadership #FutureOfWork

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Freshworks is growing fast. But is it getting harder to stay simple? In FY24, Freshworks crossed $720M in revenue. It launched new products. Acquired companies. Pushed deep into AI with Freddy. But here’s what also happened: • Net dollar retention fell to 103% from 108% • Customers found some tools too complex • Teams were stretched across too many priorities • 660+ employees were let go in a global restructure Growth isn’t the problem. Staying clear while growing — that’s the real challenge. Here’s how I’d enable Freshworks to fix this — using my WISES model: W — Watch the User Journey → As we add more products, is onboarding still smooth? → Do support teams know what’s confusing users? ✅ Map the experience. Remove friction early. I — Involve Leaders in the Frontline → Are execs hearing churn calls? → Are we acting on real customer feedback? ✅ Customer pain must reach decision-makers. S — Streamline with Innovation → Is Freddy AI helping reduce internal complexity — not just impressing the market? → Are devs building tools to improve service, not just new features? ✅ Use innovation to simplify, not stack. E — Eliminate Dead Weight → Which products or features are outdated or underused? → Where are we spreading teams too thin? ✅ Cut what’s not working. Focus on what is. S — Stay Aligned with the Soul → Freshworks started for SMBs. Are we still serving them well? → Are our values still visible in how we build and support? ✅ Don’t lose the heart that made you great. Guiding Thought: You don’t win by building more. You win by scaling what works — and staying true to what matters. Freshworks has momentum. But momentum needs direction. What would you enable if you were in their seat? #PathsNotPrescriptions #Freshworks #SaaS #B2B #ProductStrategy #CustomerExperience #WISESFramework #EnablerThinking

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AI-Powered Boomi Code Review: Where Integration Meets Intelligence. Excited to share a project where I integrated multiple LLMs to automate semantic code reviews of #Boomi components: 🔹 MCP Server (Node.js) connects to Boomi Platform APIs and orchestrates the review process. In memory implementation keeps track of last 10 review history and suggests specific improvements. The system supports both static and dynamic code validation rules, allowing custom validations when needed. 🔹 GPT-4 Mini analyzes component XML and provides feedback on design and best practices 🔹 Claude 3.7 Sonnet serves as the user interface, presenting results and enabling interactive discussions This approach has reduced integration defects and accelerated our review process compared to manual reviews, while ensuring consistent governance across all integrations. This setup showcases real agent orchestration, LLM specialization, and AI-powered integration governance — pushing the boundaries of enterprise automation with conversational AI. 📌 Skills: Node.js, Boomi Platform APIs, OpenAI API, Claude, prompt engineering, LLM pipelines #boomi #mcp #ipaas #api

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Go beyond basic automation. Discover how Oracle Fusion Applications bring AI agents right into your core business systems for smarter insights and real business outcomes: https://lnkd.in/gZFiC4FH

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