The last few years have reshaped the career ladder in the technology industry, especially in fields like software engineering, data engineering and data science. Generative AI has introduced powerful new tools for technical roles, and the rise of the “super IC” has coincided with flatter organizational structures. Many companies have reduced layers of middle management. In fact, U.S. public firms have cut these roles by about 6 percent since the pandemic peak, reflecting a shift toward leaner hierarchies and greater autonomy for technical professionals.
3 Reasons to Consider a Career in Technical Management
- Opportunity to influence the company’s technical and AI strategy.
- People skills and management remain vital in the age of AI.
- Chance to still engage in technical work with AI.
Despite these changes, technical roles that reach or influence the C-suite remain rare. So if you're considering whether to pursue a management path in tech, the question is more relevant than ever. Let’s break it down.
How Technical Management Is Changing With AI
The role of technical management has been evolving in two key ways with AI:
Managing AI and Engineering
Traditionally, technical managers were responsible for delivering quality code on time. This involved managing engineers, their work and motivations. Now, with AI-powered or assisted coding/data tools, managers must oversee the system of AI and engineers by guiding on which tools to use when, and setting standards and guardrails for AI-assisted coding. If AI is integrated within the solution, the technical manager is also responsible for ensuring that the AI models perform and are connected to the right data pipelines.
Held to Different Productivity Metrics
For decades, technical managers were evaluated by the velocity at which their teams shipped features and code. With companies like Microsoft sharing that 20-30 percent of their code is written by AI, these managers are now being evaluated by how much they can incorporate AI tools to achieve team productivity, as well as how cost efficient they can be with balancing engineering throughput and cost of AI services.
Why You Should Still Consider a Role in Technical Management
While AI has shifted the responsibilities of technical managers, they still have an integral role to play on the team. If you’re on the fence about moving from an individual contributor role to a management position, here are a couple factors you should consider:
1. People Skills Are Still a Core Advantage
No matter how much technology evolves, learning how to work with, influence and grow people remains essential. Most companies don’t operate with just one or two employees, and that doesn’t look like it will change in the future. If you want to scale impact across teams, functions and geographies, you need to know how to relate to people and bring them along with you. That’s where technical managers shine.
2. AI Strategy Needs Leadership
In many organizations, you’ll see one of two things: either the individual contributors (ICs) want to use AI tools or they’re building AI-driven products and struggling to gain traction with leadership, or executives are pushing for AI productivity gains without a clear plan. In the first case, managers become a key bridge to pitch AI ideas/prototypes to senior leaders and demonstrate the ROI to them. In the latter case, managers can help employees get comfortable with AI through learning material, AI champions within teams etc. as well as align efforts across functions, ensuring resources are deployed wisely. If you want to help steer your organization through the AI shift, management is still a really good way to do it.
Why You Might Not Consider a Career in Technical Management
1. Middle Management Is Shrinking
Since 2022, there’s been a notable contraction in layers of management, especially at large tech companies. The pressure to be lean and fast-moving means some middle management roles are increasingly vulnerable. If you enter management without a clear value proposition, such as your domain expertise or your management of diverse teams, etc., you may find yourself at risk of being laid off.
2. Individual Contributors Have Unprecedented Opportunity
Software engineers and data scientists today are expected to do much more than code or analyze data. Many are building end-to-end solutions, integrating with LLMs, designing robust infrastructure, and even shaping product direction. For highly technical professionals who thrive on problem-solving, staying on the IC path may offer more opportunities for deep focus and technical growth.
Why the Line Between IC and Manager Is Becoming Blurred
Today’s technical professionals are often expected to juggle multiple roles including writing code, mentoring teammates, shaping strategy and advocating for new solutions. With roles becoming more fluid, the question isn’t just “Should I become a manager?,” but rather:
What am I uniquely good at, relative to my peers?
- Are you the person who consistently solves the toughest technical challenges and builds scalable systems, while helping others do the same?
- Or, are you the one teammates rely on to drive consensus, influence decisions and navigate organizational dynamics?
Both paths are valid. The key is to recognize your edge and double down on it without abandoning the other side entirely. You will be best placed to succeed from a place of your unique strengths and contribute to the organization with this approach.
If your strength lies in technical problem-solving, consider staying on the IC path while broadening your influence. Communicate ideas clearly, mentor others and pursue the impact of a “10x engineer” — someone who not only delivers exceptional work but elevates the performance of the entire team. Stay current in your technical discipline and explore how AI tools can enhance both your process and your output.
On the other hand, if you choose management, don’t distance yourself from the technical work entirely. Roll up your sleeves when needed. If your team loses a key contributor, step in confidently. This hands-on credibility not only builds trust but reinforces your value. Managers who can answer technical questions on the spot without always relying on a senior IC earn lasting respect and influence.
Skills to Develop for Technical Management and IC Roles
Whether you pursue management or deepen your IC expertise, certain skills are now table stakes:
- Stay close to the technology: You don’t have to build every feature yourself, but you need to understand how it works and how it creates value. Constantly upskill yourself on what’s new and best practices including in generative AI, and think about how it can be applied within your company.
- Think strategically: Know your team's priorities, your company’s business model, and how your work fits into the bigger picture. For technical roles, this also includes understanding your system architecture, data warehouse design and engineering tools etc. as well as your management’s goals to scale this or achieve the other business goals of the company. Better yet, have an opinion on how the technology can be brought into the next generation of the company.
- Act like a leader: This isn’t just about titles but also influence, accountability, and initiative.
The career ladder might not be a ladder at all anymore; it could be a lattice, a jungle gym or something else entirely. In fact, as AI agents are emerging, the lines between IC and manager may continue to blur, since we will all be “managing” agents who can increasingly do more.
The key is to stay adaptable. The future of technical careers won’t be decided by rigid paths, but by your ability to keep learning, leading and delivering impact, whether through code, strategy, AI or people.
