Independent Analysis: AI, SaaS, and Revenue Growth Strategy

The Return of the House Call: What 'Forward Deployed' Really Says About AI By Shashi Bellamkonda | Product Strategy and Business Value Movement 1: The Raw Feedback of the House Call More than a decade ago, working for Network Solutions meant my teams and I would visit customer workplaces. We weren't there to install a new feature; we were there to see the real pain—the kind of network friction and workflow bottlenecks that never showed up in a clean report. We were listening for the ouches and the uh-ohs . This idea—embedding deeply to understand the customer's mess—is not new. It's a core component of building products that truly resonate. The tension then, and now, was always the same: Do you spend your time solving that customer's immediate problem, or do you use the visit to solve the collective problem for everyone? Movement 2: Two Competing Pressures When a company today says "we're hiring forwar...

AI's Biggest Win: Why the Best Hurricane Forecast Is Actually an Economic Tool By Shashi Bellamkonda | Risk and Business Strategy The Real Story Is Not Weather, It's Money When Google DeepMind’s AI model was the best at predicting the Atlantic hurricane season this year, that sounds like a science story. But for business leaders, it's really an economics story. The best use of AI is when it's Analytical and Predictive. It doesn't just look at past data; it tells you exactly what will happen next. This level of certainty changes everything about how companies spend money on risk - from insurance to building new facilities. From Hours of Waiting to Minutes of Planning The old, physics-based weather models were slow. They took hours to run on massive computers. Google’s AI is fast; it can make a 15-day forecast in about a minute. Why does speed matter? Because it gives you ...

The CIO/CTO Playbook for Agentic AI: Strategic Takeaways from Microsoft Ignite The era of Agentic AI is no longer a concept—it's a strategic imperative. For CIOs and CTOs evaluating platforms like Microsoft Fabric, Microsoft Foundry, and Azure Copilot, the key to successful implementation lies in maximizing efficiency, maintaining robust governance, and ensuring your organization’s data and operations are future-ready. Here are the primary implications for technology leadership: 1. Future-Proofing the Data and AI Estate (Microsoft Fabric & Foundry) Mandate a Unified Data Strategy: The rise of Agentic AI makes it critical to eliminate data silos. Technologies like OneLake offer a clear path to unify data across all clouds (AWS, GCP, Azure, on-prem) into a single, governed, and open-format data estate. This is the prerequisite for reliable, grounded AI. Prioritize Semantic Knowledge: AI agents a...

 We often treat AI as a speed tool. We use it to write emails faster or analyze data quicker. We are simply optimizing our current tasks. During our recent Small Biz Breakdown discussion, a different perspective emerged. Gen Z is not using AI to be faster at work. They are using it to skip the work entirely. They use tools to bypass the manual execution so they can focus purely on the strategy and the complex storylines. They have moved the bottleneck from "production" to "imagination." This is the business value most leaders miss. If your organization is using AI merely to reduce hours, you are playing a small game. The real competitive advantage is using AI to handle complexity that was previously too expensive or difficult to manage. Don't just clear the queue. Move the bottleneck.

Talking Headless Show with Emma Flanagan And Rebecca Wettemann I extend my deepest gratitude to my exceptional guests this week: Emma Flanagan , AR Leader at OpenText , and Rebecca Wettemann , CEO and Principal Analyst at Valoir . Your commitment to elevating the Analyst Relations (AR) and technology analyst community provided strategic clarity for us all. The Strategic Mandate: Building Executive Credibility The conversation with Emma and Rebecca offered clear perspective on moving AR from a tactical function to a strategic lever for business growth. For CEOs and CMOs , the message is direct: Analyst Relations is an integral part of your product roadmap and market validation, not merely a PR exercise . Speak the Language of Value: AR must move beyond checklist coverage. Success requires the AR team to translate analyst insights into direct business language that informs product roadmaps and M&A decisions. ...

Java Made Me Poor, Frustrated, and Ultimately Right Why Thoma Bravo's big bet on Azul just woke up the 2003 version of me Posted by Shashi Bellamkonda | November 28, 2025 I have a confession. In the early 2000s I bought 100 shares of Sun Microsystems. Today those shares buy me exactly one pumpkin spice latte… maybe. I also spent nights writing e-commerce shopping carts in JSP and servlets, cursing every single getter and setter known to mankind. I eventually ran away from object-oriented programming screaming. So when my good friend Christi Olson posted on LinkedIn last week that Thoma Bravo just took a majority stake in Azul, I almost scrolled past it. Then I stopped. And smiled. Because Java – the language I loved to hate – is having the last laugh, and it's laughing all the way to the bank. Java never died. It just went invisible. While we were busy arguing about Node vs Go vs Rust on Twitter, Java quietly kept running: 90% of Fortune 500 compa...

Shashi Bellamkonda Nov 27, 2025 • Data Security Analysis Cyera's Billion-Dollar Secret: The Data Security Solution That Pays for Itself Cyera is solving the data security and cost crisis by using AI to find risky, orphaned data. The non-obvious insight: they're not just selling security—they're selling a financial efficiency engine that unifies data, identity, and access in the agentic era. The Cobweb-Filled Corner That's Costing You Millions Let's be honest: your company's data security budget is massive, but the real risk isn't the data you monitor; it's the data you've forgotten about. We're talking about that orphaned, unclassified data sitting in cobweb-filled corners of your cloud environment. This old data is a compliance time bomb and an absolute drain on storage costs. The non-obvious business consequence of the Age...

220 Million Paying ChatGPT Users by 2030 220 Million Paying ChatGPT Users by 2030? Let's Talk Math! OpenAI projects 220 million paid subscribers by 2030. Here's what that really means for creators, small businesses, and all of us—told with kindness and real numbers. Every once in a while a number comes along that makes me spit out my chai. This week it was this one from The Information: OpenAI quietly expects 220 million people to pay (mostly $20/month) for ChatGPT Plus within the next five years. Two hundred and twenty million. That's like every single person in Russia + Brazil deciding tomorrow that ChatGPT is worth twenty bucks a month. Wild, right? So of course I had to grab my calculator, call a couple of my favorite growth friends, and figure out what this ...

The Information broke the news that ServiceNow is in advanced talks to acquire the identity security startup Veza for over $1 billion signals a structural shift in how enterprises manage risk and digital transformation. This potential acquisition is not merely a security enhancement; it is a strategic investment to secure the transactional integrity of the entire Now Platform. The Core Problem: Securing Non-Human Identities The biggest challenge in the shift to AI-driven workflows is authorization. Every new AI agent, automation script, and service account represents a Non-Human Identity (NHI) that requires granular, auditable access permissions. Uncontrolled access by these identities is the largest operational risk of Generative AI. Strategic Business Value: Authorization as the Foundation A Veza acquisition would allow ServiceNow to own the answer to the core security question: “Who can and should take what action on what data?” Workflow Resilience:  Veza’s Authoriza...

The New Ambient Agent: Will We Really Talk More Than We Type at Our Desks? By Shashi Bellamkonda | Enterprise AI Strategy Analysis The Great Conversation: Why Voice Works in the Car, But Not the Cube The conversation around AI usage is shifting: we happily talk to assistants like ChatGPT during long drives or at home, treating them like a search engine or personal concierge. But at the desktop, where the real work happens, voice just hasn't become a thing. Why? Because the corporate office—full of noise, co-workers, and professional protocols—is a fundamentally different environment than your car. Microsoft's "Hey Copilot" voice wake word is the key technical advance that unlocks ambient AI in the enterprise. But the non-obvious business consequence isn't about the tech; it's about whether the enterprise culture will adopt it. Will we truly talk more than we type? The Zero-Friction Workflow Multiplier ...