Dan Patino

Years ago, I led a high-profile tech project. We had the right tools, the right people, and what I thought was the perfect plan. We missed the deadline. Not by hours. Not by days. By weeks. In the world of enterprise tech, that’s not just a miss — it’s a dent in credibility. I spent weeks dissecting the failure. The logs, the decisions, the assumptions. It was uncomfortable. Painful. And honestly, my ego hated it. But here’s what I realized: Every “perfect” plan is built on imperfect information. Every failure is a stress test for your adaptability. That project taught me: Build for flexibility, not perfection. Listen twice as much as you explain. Treat deadlines as guardrails, not handcuffs. Because I learned that success is built on the blueprint of mistakes — if you’re willing to look at them without excuses. Every miss tells me something about my blind spots, my decision-making, and even my limits. Sometimes it’s technical. Sometimes it’s about communication. Always, it’s about growth. Because the truth is — failure is not the opposite of success. It’s the debugging process of life. If you’re not failing, you’re not learning who you really are. and If you’ve never failed, you’re probably playing too safe. #Leadership #FailureLessons #Technology #GrowthMindset #Architecture #Resilience

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When I first started in tech, we feared automation would wipe out entire roles. Today, AI is doing things we once called “impossible”: Writing functional code in minutes Predicting failures before they happen Handling support tickets without human eyes ever reading them So the question comes back: Will AI take our jobs? The honest answer: It might take the tasks, not the purpose. Here’s what I’m seeing in IT right now: Coding → shifting from writing every line to designing smarter prompts Testing → moving from manual test cases to AI-driven continuous validation Support → becoming more about handling edge cases AI can’t interpret Architecture → evolving into orchestrating both humans and machines AI doesn’t remove the need for people — it changes what “valuable” means. The skills that survive aren’t just technical. They’re the ones AI can’t replicate: critical thinking, empathy, complex problem framing, and making trade-offs in ambiguity. If you’re in IT, your real risk isn’t AI taking your job. It’s you staying in a role that AI is learning faster than you are. AI won’t replace you. But someone using AI better than you will. Do you Agree ?

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Stop looking for high-ranking people with fancy titles. Start looking within your own family. Sometimes the best experts are sitting at your dining table. I took a week off to reconnect and clear my thoughts. Met my friends, family, and brothers. It turned out to be one of the best weekends I’ve had in years. I’ve always wanted to start a podcast but never did—not because of time, but because of self-doubt. Who would join? How would I find skilled people? So I looked outside—LinkedIn, events, strangers. And then my younger brother said something simple: “Why don’t you start with friends and family?” It wasn’t a new idea, but it felt different this time. It came with support. I called my brother, Anshul Gautam. “Bhiya, I need your help. I’m planning a podcast.” He just said, “Okay, aaja. We’ll do it.” No overthinking. No conditions. When I reached home, the welcome was warm. Lunch on the table, smiling faces, and a clear plan. He wasn’t just a guest; he was a guide—showing me podcasts, explaining formats, helping shape topics. While he spoke, I realized—he’s not just my brother. He’s a mentor. Calm, thoughtful, simplifying everything. We picked a topic: How technology evolved from 2008–2012 to now. He laughed, “Okay, if that’s what you want. Let’s do it.” People call him introverted, but I saw a confident, stage-ready person. We set up the camera, chairs, microphones. Harder than it looks, but we figured it out. Once we started, the script disappeared. The conversation flowed—no ego, no filters. He said something that stayed with me: > “AI can do so much today, but never forget to understand the depth of the code. Technology shifts will keep coming—automation, AI, something else tomorrow. Go with the flow. Learn. Teach. That’s how you survive.” We spoke for an hour, lost in conversation. And then—the punchline—I forgot to hit record. No episode, no content. But a priceless memory. Lesson: Stop chasing strangers. Sometimes the best conversations start at home. Thank you Anshul Gautam

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𝐓𝐡𝐞 𝐑𝐞𝐚𝐥 𝐌𝐨𝐝𝐞𝐫𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 Many IBM i modernization challenges aren’t about technology limitations. They’re about application structure. Over time, RPG systems often evolve into tightly coupled designs where business rules, data access, and process flow are all intertwined. This makes integration difficult — even when the platform itself is capable. 𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗺𝗶𝘀𝘁𝗮𝗸𝗲 𝗶𝗻 𝗜𝗕𝗠 𝗶 𝗺𝗼𝗱𝗲𝗿𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Companies start with the UI. Green screens become web screens. Start here instead: • Extract service programs • Define domain boundaries • Expose business logic through APIs Once the architecture is modern… the UI becomes easy. Breaking functionality into service programs is often the first meaningful step toward modernization. It allows logic to become reusable, testable, and ready for API exposure. 𝑾𝒉𝒂𝒕 𝒎𝒐𝒅𝒆𝒓𝒏𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒔𝒕𝒆𝒑 𝒈𝒂𝒗𝒆 𝒚𝒐𝒖 𝒕𝒉𝒆 𝒃𝒊𝒈𝒈𝒆𝒔𝒕 𝒘𝒊𝒏?

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#ServiceNow If you continuously look for opportunities to optimize your platform performance, you might need to consider. ✔️ In ServiceNow, 𝐠𝐬.𝐬𝐞𝐭𝐂𝐚𝐧𝐧𝐨𝐭𝐂𝐚𝐧𝐜𝐞𝐥(𝐭𝐫𝐮𝐞)➡️ Used to prevent a transaction from being canceled during its execution, ensuring that all related operations complete without interruption. This is particularly useful when dealing with operations that involve multiple interdependent updates, where partial completion could lead to data inconsistencies or other issues. #ServicenowDeveloper #ServiceNowCommunity

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15 years ago, being an ATG (now oracle commerce) developer meant sitting with heavy, physical manuals. There was no Stack Overflow to save you. If the answer wasn't in those pages, you were on your own. Looking back, my career has been a series of shifts: * Dev to Build/Release Engineer. * SRE to Cloud & Platform Engineering. Each step felt like a natural progression until the "AI era" hit. Suddenly, the pace changed. Today, my workflow is a mix of different languages and tools that used to take years to master individually. Now? I’m writing Ansible over morning coffee, Terraform by mid-day, and Python logic during lunch. By the time I’m having my evening chai, I’m deep in cloud troubleshooting. I’m not sharing this to brag. I’m sharing it because I’m not doing this alone. I’ve realized that AI isn’t a replacement for the foundation I built over 15 years—it’s an amplifier. I like to think of it through the lens of the Mahabharata: AI is the Gandiva (the bow), but you are still Arjuna. The bow is powerful, but it needs the archer's intent, experience, and direction to hit the mark. AI is just the mode. If you’re feeling a bit uneasy about where the software world is headed, my advice is to stop viewing AI as a threat and start seeing it as your gear. Embrace it, lean on your foundations, and use it to write your next chapter. #SoftwareEngineering #AI #CloudComputing #TechJourney #CareerGrowth #SRE #ContinuousLearning

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🚀 Stop celebrating output. Start measuring outcomes 🚀 Many teams still equate “busy” with “impact.” But real progress isn’t measured by how many features we ship — it’s measured by the value we create and the problems we solve. When we focus on outcomes, we build with purpose, prioritize what truly matters, and create meaningful change for our users and our business. 👉 Read full article here: (https://lnkd.in/eh5KabrU) Let’s build value, not only features

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We talk a lot about what AI does, but it's even more fascinating to understand how it thinks. It's easy to call the output of modern LLMs "magic," but the genius is in the engineering. The "Transformer" architecture revolutionized the field because it wasn't just a linear improvement on old tech, it was a new way of processing language. The secret ingredient is "self-attention." Instead of just looking at the last few words to guess the next one, the model looks at the entire sentence at once, weighing the importance of every word in relation to every other word. This is one of the clearest, step-by-step explanations I've seen of how it all fits together. Great post, Eduardo Ordax!

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TOGAF and Zachman are great but by themselves they don’t make good architecture. Good solutioning does. Frameworks help, but they don’t replace clear thinking, sound decisions, and architecture people can actually use. That’s where Enterprise Architecture proves its value.

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Build intelligent employee onboarding with Gemini Enterprise. See how with this example use case: a laptop request for new employees. First, use the Agent Development Kit (ADK), Agent Engine, and Application Integration to build custom agents that connect to your enterprise systems (such as ITSM, ERP, and CRM). Once built, these agents are published to the Gemini Enterprise agent gallery, where employees can easily access and interact with them. The result is a more personal employee onboarding experience. Read on to learn how to connect conversational AI with your essential enterprise systems ➡️ https://goo.gle/4qWYM8h #GoogleCloud #Google #Alphabet #Cloud

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Following the executive slide deck I shared earlier this week, I'm sharing the full white paper on how the Single Responsibility Principle, Open/Closed Principle, Liskov Substitution Principle, Interface Segregation Principle, and Dependency Inversion Principle — together with modular monoliths and Capabilities as a Service — can provide a practical architectural foundation for modern wireless carriers. The paper focuses on how carriers can use a more disciplined, capability-based architecture to: • Accelerate new service delivery • Strengthen AI readiness and deployment • Reduce operating expenses through increased operational efficiency • Improve network and service quality • Improve end-to-end performance • Increase monetization of existing assets across the network and service stack • Enable end-to-end service orchestration It also explores why this architectural approach is especially relevant now, as carriers work through declining margins, high operating costs, technical debt, fragmented tools, manual processes, and persistent performance and service quality issues across 5G and emerging 6G environments. Topics include: • Modular monoliths versus distributed services • Capability-based architecture • Multi-actor carrier operating models • Radio Access Network performance monitoring and optimization • Service-aware smart orchestration • The expanding role of AI, Machine Learning, and automation teams I'd welcome your thoughts, especially from leaders in wireless architecture, operations, performance engineering, service orchestration, and carrier transformation. #5G #6G #RAN #Telecom #Wireless #NetworkArchitecture #AI #MachineLearning #Automation #ServiceOrchestration #Cloud #MLOps

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