The rapid rise of AI tools like ChatGPT, Gemini, and Perplexity is transforming how consumers interact with brands and make purchasing decisions. These tools are quickly becoming the go-to resources for research, leading to higher conversion rates and more informed buying choices. As traffic from AI technologies continues to surge, brands must adapt to stay relevant in this evolving landscape. Leaves falling - search box - Created with Adobe Express Enter Adobe’s innovative LLM Optimizer, an AI-first tool designed to help brands navigate the complexities of this new reality and ensure they capitalize on the benefits of AI-driven engagement. Here’s how LLM Optimizer can drive significant value for your brand through Generative Engine Optimization (GEO): 1. Gain Insights into Your Brand's Current Standing. LLM Optimizer empowers brands to understand their visibility in AI-driven search results. By providing comprehensive reports on current mentions, citations, and recommendations in ...

 Part I of this series, published in May, discussed the definition of MLOps and outlined the requirements for implementing this practice within an organisation. It also addressed some of the roles necessary within the team to support MLOps. Lego Alike data assembly - Generated with Gemini   This time, we move forward by exploring part of the technical stack that could be an option for implementing MLOps.  Before proceeding, below is a CTA to the first part of the article for reference. Assembling an MLOps Practice - Part 1 ML components are key parts of the ecosystem, supporting the solutions provided to clients. As a result, DevOps and MLOps have become part of the "secret sauce" for success... Take me there Components of your MLOps stack. The MLOps stack optimises the machine learning life-cycle by fostering collaboration across teams, delivering continuous integration and depl...

 These days, simply mentioning “AI” isn’t going to win anyone over. Clients expect authentic, data-driven results—not just bold claims or industry jargon. The expanding reach of AI brings some real concerns with it, such as errors, bias, and privacy risks are all in the mix. If those issues aren’t addressed, trust can erode quickly. It also affects an organisation’s dynamics, operations, and culture—regardless of size—including shifts in client relationships as expectations evolve. What can set a tech-consulting firm apart, among other things, is the dedication to building AI solutions on foundational values like fairness, transparency, accountability, privacy, security, and reliability. In other words, Responsible AI can be hard work, and it is a genuine differentiator. If an organisation can ensure the solutions implemented are ethical, clear, and consistently trustworthy, then it is likely it will foster customer confidence and loyalty. Photo by Google DeepMind from Pexels ...

In one of our previous articles it was highlighted how DevOps manages the End-to-End application cycle, leveraging agility and automation. CI/CD pipelines, collaboration and transparency, monitoring and automation are part of the list on how DevOps leverages and facilitates agility. What if then we bring those to support ML? That is how MLOps comes to the table and starts making sense! Lego Alike data assembly - Generated with Gemini A big tech corporation, or a startup, nowadays will see how it is becoming a requirement to incorporate AI and Machine learning (ML) in their operations. ML components are key parts of the ecosystem, supporting the solutions provided to clients. As a result, DevOps and MLOps have become part of the "secret sauce" for success.  What is MLOps Just to bring the definition of what you probably know (or put together based on the above) MLOps focuses on the life-cycle management of machine learning models. It combines machine learning with traditional ...

 Have you ever been in a conversation that you feel at best is just a waste of time; at worst, that the other person does not care? Have you been the messenger in some of them, the recipient in another? We’ve all been there; at times with family, with friends, at work. When at work, has this ever happened to you in a group meeting, at a one-on-one; when giving or receiving feedback?   Photo by Christina Morillo via Pexels   I knew the type of manager I wanted to be from the start of my mentorship. As I continued to navigate the waters, it became increasingly clear that the path I had chosen was appropriate, and therefore, the type of future colleagues I wanted to be surrounded by, and the type of mentors I wanted to continue seeking guidance from.  For me, the path has always been of being a leader over a manager. I believe I can attribute that, first and foremost, to my family’s values and  principles, and the way my parents raised us. Secondly, my path in the ...

Tech is evolving faster than ever in this AI era, that it feels every week there is something new to talk about, and what you learn weeks back is no longer relevant, or “that AI tools” already has gone through changes that you need to catch up with in order to stay relevant.  Fear not, embrace the challenges and learnings, and find applications for it that are good and ethical for this present, and the hereafter.  The new “craze” is AI agents, and for good reason!  Image generated with NightCafe In contrast with AI chatbots, an AI agent can execute tasks on your behalf. If you are thinking “ that this could be agents that we leave running independently for many days for a group of deliveries ”… Well then you are correct! Are there risks? Should we talk about trust and accountability? The answer for both is yes. I already hinted at it a couple of paragraphs above, when I wrote “ good and ethical ”. AI (Artificial Intelligence) agents are software that work autonomously,...

Companies are in need of the metrics that will allow them to stay in business by making sure they meet the expectations of their customers. The name of the game is higher customer satisfaction by winning their trust and loyalty. To do so, you want to provide good products and services. Therefore you need to find ways to monitor performance, drive continuous improvements and deliver the quality expected by the consumer in this highly competitive market. Photos from AlphaTradeZone via Pexel and Spacejoy via Unsplash SLAs, SLOs and SLIs are a good way to achieve the above. They allow clients and vendors to be on the same page when it comes to expected system performance. If we go one level deeper, vendors/providers work on NFRs (Non-Functional Requirements) when working on their solutions. NFRs define the quality attributes of a system. I bring them up because the relationship between them and the SLAs is that they provide, in a way, foundational aspects for the SLA-SLO-SL...

 Conflicts are a part of our daily lives and are often unavoidable at work. Therefore, it's essential to have the tools to effectively manage conflicts and leverage them to our advantage - to spur new ideas, challenge and strengthen our beliefs, and evolve our perspectives when necessary. However, conflicts often trigger our fight-or-flight response and can cause chronic stress and mental fatigue and diminish our productivity. Having the right tools can help us face conflicts confidently.  AI Generated with Microsoft Copilot + Designer by Beolle   Recently, I took a course from Harvard ManageMentor® * to enhance my conflict resolution skills. I summarized the key takeaways from the course in the framework below to help you better prepare for resolving conflicts. The framework consists of six (6) parts Identify the type of conflict   Identify your own and your counterpart's conflict styles   Determine how you want to address the conflict   Prepare to resolve...

 If you are wondering what the differences between the SRE and DevOps are, as well as how these roles work with ITOps within an organisation then you are not alone; and best of all you are on the right blog post. Often enough business units in a company get confused, assigning the ServiceNow or Jira tickets or any other ticketing system of your preference, to the wrong group, and even having the incorrect expectations when doing resourcing. Let us go through definitions, insights and scenarios that will help you understand the difference. DevOps software development operations - AI Generated When it comes to DevOps and SRE, then you might be wondering which practice came first. While SRE may have originated a bit earlier, internally at Google, DevOps came first publicly as a practice and started to be used by companies. A few years later was when Google decided to open SRE to the world after the publication of the "Site Reliability Engineering" book. Therefore, technically sp...