For the past 15 years, I've worked as a production database administrator, progressing through roles including Team Lead DBA and Principal DBA, though never formally holding a manager title. Reflecting on all the managers and companies I have worked for over the years, I have seen “the good” and “the bad”. I wanted to take some time here to reflect and identify the key elements that contributed to my job satisfaction and professional growth. Why did I enjoy those places, and how will artificial intelligence (AI) impact future IT management decisions?

Starting Off in IT

My journey in technology began as a junior database administrator within a large healthcare IT department. The initial team structure seemed robust and well-designed: a manager oversaw our group, which included a senior DBA who served as our technical mentor, two mid-level DBAs, a mid-level contractor, and me. The senior DBA was a strong personality and leader and proved invaluable in guiding us through the intricacies of our assigned projects while our manager handled the broader coordination and planning.

Unfortunately, within just three months, internal politics led to a dramatic reshaping of our team. The two mid-level DBAs were terminated, the contractor's agreement wasn't renewed, and our senior DBA departed. Although the manager quickly brought in two new mid-level DBAs to fill the gaps, the scale and complexity of our responsibilities were daunting, especially given our limited collective experience.

For some time, it was me, a very inexperienced DBA, and two contractors running a large database environment that included 5000 databases and several hundred servers. We began the search for a new DBA manager. During the subsequent search for a new manager, I was fortunate to participate in the interview process. After meeting with numerous candidates, a pattern emerged in their responses to our question about management style. Most struggled to articulate a clear philosophy, offering vague generalities that left us increasingly discouraged. However, the final candidate gave a simple yet profound response: "It's all about people, process, and tools." This response has stayed with me ever since and has become how I judge if a team is going to be successful.

A Deep Dive Into People, Process, and Tools

In preparing for writing this post, I searched for "people, process, and tools." I discovered that this framework has roots going back to the 1960s and can be attributed to Harold Leavitt and his diamond model. Leavitt's original model consisted of four interdependent elements: people, structure, technology, and tasks. According to this model, changes to any one element would necessarily affect the others. Over time, the elements of structure and tasks were consolidated into what we now call "process," resulting in the streamlined "people, process, and tools" framework we recognize today.

People

In my IT career, I've experienced both high and low-performing teams. What distinguished the people in these situations? High-performing teams had layers of technical competence—team members each brought varied skill sets that created a well-rounded team. The success of the team took precedence over individual achievement. When skills gaps emerged, management took the initiative to provide training to maintain our high functionality.

How many times have you asked for training only to hear there's no budget? How often have colleagues left an organization due to a lack of professional development opportunities? This reminds me of a Richard Branson quote. The Virgin Group founder once said, "Train people well enough so they can leave, treat them well enough so they don't want to."

Process

As mentioned earlier, process is a consolidation of structure and tasks. In every organization where I've worked, the process was drastically different, yet with a few key commonalities. In high-performing teams, the process was clearly defined, added tangible value, and generated reliable reporting. In contrast, low-performing teams operated with nebulous processes that seemed arbitrary, often became punitive, and produced unreliable data that undermined effective reporting.

High-performing teams were consistently held accountable for following established processes, while low-performers rarely faced such accountability. When proper processes aren't adhered to—or worse, when no formal process exists—the consequences can be severe: data breaches, data loss, system outages, and overall poor performance of IT systems become rampant.

As an individual contributor throughout my career, I'm less concerned with the specific process or tool being used and more concerned with ensuring we have sensible processes that can be easily followed and that genuinely support our business objectives.

Tools

I hope this section doesn't come across as a sales pitch, despite my current role at a monitoring and observability software company. To junior IT professionals: during the interview process, if you discover a company has no coherent strategy around its tools, consider this a serious red flag. I've declined several job offers specifically for this reason. When a company isn't monitoring its environment, it isn't taking its IT systems seriously.

I have encountered this scenario with both current and prospective customers who believe developing their own monitoring solution will save money. I challenge them with these questions: What is your primary job responsibility—to develop tools, or to perform your actual role, such as database administration? What happens when the person who built the custom tool leaves the company? Who will support and maintain it going forward?

One of the largest organizations I worked for came to rely heavily on a homegrown tool—right up until the technology it was built on was deprecated by Microsoft, leaving them scrambling for alternatives.

An important consideration is how your toolset enhances both your processes and the people using them. Nothing undermines effectiveness more than a tool that generates an overwhelming storm of alerts, leading to alert fatigue and team members routinely sending notifications to the trash. Equally problematic are tools so complex that they go unused.

Remember: tools should make our jobs easier, integrate seamlessly with your processes, and enhance our technical skills—not replace them.

Impacts of AI

For years, companies have pitched ideas of automation and self-tuning systems that would supposedly make IT workers irrelevant. SQL Server 2005 was touted as "self-tuning," and we all know how that turned out.

With the advent of graphics processing units (GPUs) and the rise of companies like NVIDIA building these chips (now worth more than some small countries' national GDP), AI is clearly here to stay. Microsoft, Meta, Amazon, and Google are spending billions building AI infrastructure to train their models. Meanwhile, DeepSeek has disrupted this space, claiming to train its model for approximately $5 million. We're witnessing an "AI arms race" among these tech giants.

I am a fan of Scott Galloway and his Prof G podcast. This entrepreneur and NYU professor has spoken extensively about AI integration in the workplace. On Entrepreneur.com, Scott stated: "Just start using [AI], and your own mind will start figuring out ways to incorporate it. You're the warrior. This is a weapon, but you're the warrior."

In my work at SolarWinds, I needed to build a workload against the StackOverflow database. I asked one of the popular LLM tools to help, and after three iterations, what would have taken me hours or days was completed in 5 to 10 minutes.

While you often hear that "AI will come for our jobs," I see it as a workforce multiplier. Will some job classifications be impacted? Possibly, as AI enables greater efficiency, companies might require fewer people for certain roles.

The consistent message from SolarWinds leadership regarding AI has been: "What problem are you trying to solve?" While AI has become a marketing term, at SolarWinds, we focus on solving real problems with AI assistance.

The Future of IT Management

As we navigate the evolving landscape of IT management in the AI era, the fundamental principles of "people, process, and tools" remain as relevant as ever. AI doesn't replace this framework—it enhances it. The most successful IT departments will be those that thoughtfully integrate AI capabilities while maintaining their focus on developing their people, refining their processes, and selecting appropriate tools.

The reality is that AI won't make good managers obsolete; rather, it will amplify the difference between effective and ineffective leadership. Strong managers will leverage AI to empower their teams, automate routine tasks, and focus human talent on higher-value work that requires creativity, critical thinking, and interpersonal skills.

The future of IT management doesn't belong to those who simply adopt AI, but to those who thoughtfully integrate it into a people-first strategy—creating environments where professionals can grow, collaborate, and solve meaningful problems with increasingly powerful technological assistance. The most successful leaders will be those who use AI as another tool to build stronger teams, more efficient processes, and more resilient IT environments.

To learn more about people, process and technology, read the latest article by Cullen Childress on achieving operational resilience.