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In most cases, vendors aren’t yet offering truly agentic AI with real autonomy, some critics say, but are instead pitching simpler AI chatbots, assistants, or add-ons to large language models (LLMs) as agentic AI. Many so-called agents are just LLM wrappers or “glorified LLM workflows,” says Zach Bartholomew, VP of product at Perigon, provider of an AI-powered and context-based search tool. The agent bandwagon There’s a lot of “agent-washing” in the IT industry right now, says Chris Shayan, head of AI at Backbase, a banking software vendor. “I’ve sat through dozens of vendor pitches where basic automation was rebranded as autonomous agents,” he says. “Many solutions being marketed as agents are actually just traditional algorithms with better interfaces, and there’s a world of difference that CIOs and CTOs are struggling to navigate.” source

Gopalkrishnan, who is the CIO of six of the bank’s eight lines of business, says Bank of America operates a hybrid “hosting strategy” based on a virtual private cloud the bank has operated for years and public clouds as needed. BofA has relationships with Microsoft, AWS, Google, and other clouds, but like many bank CIOs, Gopalkrishnan prefers to keep workloads close for cost and security reasons. “We have been very effective at scaling it, which lets us get to a point where we’re not paying for bursty volumes,” Gopalkrishnan says, adding it has been “interesting” to see repatriation efforts of some organizations away from cloud computing. “We’ve always said we’re not going to over-index and over-swing the pendulum,” the CIO says. “Our view is we essentially have a hosting strategy. We’ve got multiple availability zones in our virtual private cloud. We extensively use our virtual private cloud, and as need be, we can burst into public clouds based on the use cases, either for other software providers or for ourselves.” source

Keith Shaw: Taken off, right? Taylor Pechacek: They have, yeah—definitely. Keith Shaw: Today, you’re going to show us some agentic AI capabilities. Taylor Pechacek: Yes, very excited about this. We’re constantly improving the product, and today we have a major release around how to build agents on the Postman platform. Keith Shaw: That’s a huge topic. So who is this really designed for? I’m guessing software developers, but are there others within a company who could benefit from this? Taylor Pechacek: Great question. It’s really aimed at our core market—developers. But there are many types: backend, frontend, QA, platform engineering, DevOps. And since we’re a collaboration platform, APIs are central to modern software development, which also includes product managers, designers, solution engineers, and sales teams. Agents will also help non-developers start building by making it more accessible. It expands beyond our developer core to help a broader audience improve their workflows. source

The data piece was simple: the basic facts of the flight and the running chat between the attendants, pilots, gate agents, and the operations people associated with the flight. We fed that information — with additional data on weather, for example — into the AI model, to generate a good draft customer message. The trick then was to have it understand the nuances of United Airlines’ communications style and what we wanted to emphasize. That’s where prompt engineering came in, not to train the model to understand flight data, but to use the words United prefers. Let’s take safety, for instance. We can emphasize safety with without scaring people, and the AI tool is learning to make the right word choice. We were excited to discover that in addition to learning how to craft the message, the AI model was very good at looking back in time to bring previous flight data into the current situation. Even our human storytellers didn’t include reasons for flight delays, and that kind of information can be very useful to a customer. source

However, neither provider explicitly discloses its results in the ERP sector. Instead, Apps Run The World made estimates based on public records, cloud and non-cloud business models in its supplier database, and the results of annual surveys including supplier feedback. Oracle customers are being milked harder According to the analysts, the reason for the change in leadership is simple math. Oracle, for example, has more than 100,000 customers in the entire ERP segment (which includes both financial management and industry-specific back-office solutions), each of which contributed an average of $87,700 last year. In contrast, SAP only generated an average of $61,429 with each of its 141,399 ERP customers, or around 30% less per customer. Apps Run The World puts the average turnover of a customer with Oracle Fusion Cloud ERP at $257,286 and one with SAP S/4 HANA at $253,100. At the same time, the analysts point out that Oracle grew by 17.7% in 2024, while SAP only grew by 13.7%. source

I find these same concepts relate directly to the strategy, design, and execution of technology projects. There is a tremendous amount of creativity on how business strategy, process engineering, data and analytics, software, and hardware all come together to solve business problems and meet customer needs. Once designed, these solutions have to be secure, scalable, and highly available. As a result, precise execution is critical. Being on beat and hitting the right notes is the product of many takes in the recording studio, just as writing and testing code is critical to ensuring the final product is the highest possible quality. At the same time, playing music in a band and leading a technology organization both require continual attention and adaptability. In music, that might come in the form of improvising and responding to the dynamics of your bandmates during a live performance. You have to be nimble in those situations, and it takes a lot of practice and experience to build your chops and be able to listen and adjust in the moment. This is something we’re all too familiar with as technology leaders. Especially with the speed of change and innovation, you have to make smart calls under pressure and be able to navigate quickly evolving business priorities, unexpected challenges, and new opportunities. Does playing music help you process complex problems and see patterns differently? If so, how? source

“That’s 100% accurate,” says Patrick Buell, chief innovation officer at Hakkoda, an IBM company. “Tuned, open-source small language models run behind firewalls solve many of the security, governance, and cost concerns.”  Tom Richer, a former CIO and founder of Intelagen, a Google Partner that develops and deploys specialized vertical AI solutions, says the Gartner report aligns with what he is seeing in the field. “General-purpose LLMs have their place, but for specific business problems, smaller, fine-tuned models deliver better results with greater efficiency especially in regulated industries,” Richer says. “The main driver towards SLMs is the hallucination risk of LLMs. The tendency of general-purpose LLMs to generate inaccurate or nonsensical information, especially when dealing with specific or nuanced business contexts, is a significant barrier.” source

As for security, MCP agents are subject to all of the risks that come with any type of LLM-based technology. They have the potential to leak sensitive data because any resources that are available to an MCP server could become exposed to a third-party AI model. A potential solution is to avoid third-party models by hosting models locally (or on a server located behind a firewall) instead, but not all models support this approach, and it adds to MCP setup challenges.  MCP servers could also potentially carry out actions that you don’t want them to perform, like deleting critical resources. To control for this risk, it’s important to apply a least-privilege approach to MCP server design and management by ensuring that they can only access the minimum resources necessary to support a target use case. The capabilities of MCP servers are limited to the level of security access available to users, so by restricting user privileges, admins can restrict MCP security risks. MCP and the future of AI in DevOps To be sure, MCP is not perfect. But it constitutes a huge leap forward in terms of how DevOps teams can leverage AI. It’s also a technology that’s here and now, and that DevOps engineers can start using today. Going forward, it’s likely that MCP will become as integral to DevOps as technologies like CI/CD. source

Since leaving the jungle, humans have divided themselves into categories — a set of we’s. We 8.2 billion humans would be materially healthier, wealthier, happier, and safer if we could constructively and empathetically reconcile the hopes, dreams, and fears of the many we’s that make up our species. Anthropologists and philosophers who study collective behavior embrace the premise that “we” has three foundational components: the individual (who am I?), the social (how do I want others to see me?), and the collective (who are we?). (George Akerlof and Rachel Kranton’s Identity Economics: How Our Identities Shape Our Work, Wages, and Well-Being is one such source.) Before CIOs can understand IT in the collective (the “who are we?”), they must have a strong handle on their own personal identity. I have long argued that a critical piece of CIO success is autobiographical. CIOs need to be much more transparent. Your IT organization must know who you are — your values, what you care about, how much you care about it, and even your personality quirks. source

Through your early career, you’ll want to focus on starting out in roles such as IT support technician, systems administrator, cloud developer, cloud engineer, cloud administrator, DevOps engineer, network administrator, or cloud security analyst. These roles will help you gain the right skills, knowledge, and expertise to continue down a cloud-related career path. Establish a career plan with your manager and communicate your intentions of becoming a cloud architect, and find the right mentors who can guide you on your career path. As a cloud architect, you may find yourself on an Individual Contributor (IC) path, which is an alternative to leadership that still allows you to grow and develop your career. As an IC, you’ll evolve into a subject matter expert in your field of expertise, assisting with high-level development and implementation plans for cloud solutions. Continuous learning will be a priority on the IC path, ensuring you continue to grow and develop your expertise and learn about new and emerging tech. Others will find themselves on a management path, leading teams of cloud architects and engineers, ensuring they stay on track and budget when it comes to cloud infrastructure. For those on the leadership path, continuous learning will also be important, but soft skills will become a priority. Your focus will be less on the technical aspects of the cloud and more on leading teams, encouraging collaboration, and communicating to key stakeholders the benefits of cloud adoption. source