Mohammed Feisal Ismail, Principal Consultant, Sapience Consulting 

As artificial intelligence becomes embedded across DevOps and Site Reliability Engineering (SRE) toolchains, many mid-career professionals are re-evaluating what it means to “stay relevant”. The challenge has evolved beyond simply keeping up with new platforms or learning the latest automation techniques. Instead, it now involves developing the judgment, perspective, and business awareness needed to apply powerful technologies with purpose.  

In this article, Mohammed Feisal Ismail draws on his experience advising organizations through complex digital and operational transformations. He explores how DevOps professionals can navigate this shift and why humility, critical thinking, and foundational knowledge matter more than ever.  

AI is increasingly integrated into almost every major DevOps and SRE platform. Engineers may not fully grasp the underlying models or algorithms, yet they are already using AI-enabled features in deployment pipelines, monitoring environments, and incident response workflows.  

This shift presents both opportunities and risks. On one hand, AI unlocks vast amounts of telemetry, performance data, and actionable insights. On the other hand, it adds complexity. Making sense of that data, knowing what to trust, and deciding when to intervene are now challenges.  

At its core, engineering has never been about tools for their own sake. The word itself originates from the Latin ingeniare, meaning “to devise or solve problems through insight and experience.” The danger today is applying AI just because it exists, not because it solves a real problem. Engineers can easily fall down the rabbit hole, chasing shiny solutions that don’t address real business needs. Solutions without purpose quickly lose their value. 

Remaining relevant means asking tough questions: What exactly are we automating? What are we improving? Which business problems are we genuinely solving? 

Why systems thinking matters more than tool mastery 

With AI handling routine operational tasks, certain skills are naturally becoming less critical. For example, manually building pipelines or performing basic automation can now be done faster and more consistently by AI-assisted platforms.  

However, higher-order skills cannot be easily outsourced. Skills such as systems thinking, risk awareness, and the ability to anticipate failure are essential. Modern DevOps and SRE professionals must think like defenders as well as builders, wearing a “black hat” to predict how things might go sideways, considering security, resilience, and unintended consequences alongside speed and efficiency. 

Equally important is a shift in mindset. Technical mastery alone is no longer sufficient. Engineers must understand how the products and services they support contribute to business objectives. This requires moving beyond a fascination with tools to adopt a more business-minded perspective focused on value, outcomes, and trade-offs.  

The importance of communication skills in the age of AI  

AI has made communication skills more critical than ever. The ability to influence, negotiate, and translate complex technical concepts into language that business leaders can understand is invaluable.  

DevOps and SRE professionals often need to “code-switch”, translating technical benefits and risks for business leaders so that AI’s limitations, failure modes, ethical considerations, and governance challenges are clearly understood.  

In this environment, relevance is less about being an AI expert and more about helping an organization make informed decisions on where, when, and how to apply AI.  

Developing skills through curiosity and self-awareness 

Staying ahead begins with honest self-appraisal. Professionals must recognize both what they know and, importantly, what they do not know, including gaps in their knowledge that they may not yet be aware of.  

Continual learning is essential. Conferences, seminars, webinars, and peer networks expose engineers to new ideas and perspectives. Mentorship is especially valuable, particularly from those who have seen technology evolve across multiple waves and who can offer guidance beyond the latest trends.  

At the heart of all this is curiosity. The ability and willingness to learn quickly remain the most valuable attributes a DevOps or SRE professional can possess. Curiosity fosters experimentation, critical thinking, and adaptability, all of which are essential in an AI-accelerated world. 

Where capability gaps still undermine AI-driven operations  

Capability gaps exist at both individual and organizational levels. At the individual level, professionals must know when to use AI and when not to. Over-reliance on automation risks eroding foundational skills and critical thinking. As the saying goes, “artificial intelligence can breed natural stupidity.” This understanding is crucial; when AI systems fail or behave unpredictably, it is these fundamental skills that save the day. 

At the organizational level, governance is paramount. Automation and AI should strengthen controls, rather than bypass them. Clear policies and guardrails are necessary to prevent misuse, regulatory breaches, or unintended security risks. Allowing AI to make unchecked decisions can have significant operational consequences.  

When AI helps, and when it hurts  

AI is often deployed to improve metrics such as mean time to repair, service reliability, and delivery speed. When well managed and supplied with high-quality data, it can effectively achieve these goals.  

However, poorly managed AI can backfire. Poor-quality data, incorrect assumptions, or excessive reliance on automation can prolong outages and complicate recovery. In these situations, organizations must fall back on their most valuable asset: skilled and confident individuals who can intervene when needed. AI can enhance operations, but it cannot replace human judgment.  

Certification, experience, and credibility 

Experience, of course, is invaluable. It reflects lessons learned, mistakes made, and problems solved in real-world conditions. But experience alone can be difficult to validate objectively. This is where certification matters.  

Independent, third-party validation provides a baseline assurance of knowledge. It does not replace experience, but it signals credibility, allowing professionals to demonstrate insights, cultural fit, and practical expertise. For employers, certifications, such as those provided by the DEVOPS INSTITUTE, offer confidence that candidates possess the foundational knowledge necessary for meaningful contributions.  

However, every professional starts from a different “base camp”, with unique aspirations, whether in technical leadership, people management, or advanced SRE practice. Effective career roadmaps begin with self-reflection. Professionals should assess their current skills, define their long-term goals, and select learning paths that align with them. Foundational courses offer grounding, while advanced leadership or specialized education supports progression into more senior or niche roles.  

Ultimately, the key is alignment; learning investments should reflect where individuals are today and where they aspire to go next.  

The biggest mistake in trying to “AI-proof” a career 

One of the most common misconceptions in this AI era is that DevOps and SRE professionals must become AI experts. They do not. You don’t have to be the mechanic to drive the AI car. Successful AI adoption depends on collaboration. Engineers only need enough understanding to work effectively with data scientists and AI specialists, not to replace them.  

Another misconception is the belief that everything can be delegated to AI. The reality is that human oversight, contextual judgment, and cross-functional collaboration remain crucial. That’s why the most successful professionals know when to rely on AI and when to take direct action themselves.  

Looking ahead: humility, fundamentals, and shared frameworks 

One quality stands out above all others: humility. Recognizing knowledge gaps, maintaining strong foundational skills, and applying AI within clear governance frameworks are not signs of caution; they are hallmarks of professional maturity. Together, these elements enable DevOps and SRE professionals to use advanced technologies with intent, accountability and confidence. 

In an environment defined by constant change, long-term relevance will belong to those who invest in shared frameworks, continuous education, and a common language that connects technology, culture, and business outcomes. By combining human judgment with AI-driven insight, organizations and the professionals within them will thrive as AI adoption accelerates.