Thanks to AI, ALL Software Developers and Engineers are now Technical and System Architects. Sure, it means having to write less code but it also means being able to accomplish more things faster — more optimizing, designing, orchestrating, and leading. It also means more effective work and less toil.
For decades I have worked at corporations and have been a strong advocate for the business analyst mentality. Everyone who wants to be valuable in the company, whether they are in sales, marketing, accounting, HR, or on the tech side will be most productive and most valuable if they think and act like a business analyst. Bridging the Gap is a great resource that explains the value business analysts bring to companies.
You may have the luxury of working in a larger company that actually hire dedicated business analysts, but for small businesses with smaller payroll budgets that doesn’t mean because you can’t afford a dedicated business analyst that you can’t advocate and train all of your employees to understand the benefits of applying the principles that embody effective business analyst functions.
Similarly on the innovation, tech, business systems and software side there is a new dynamic but along the same lines. “We’re all System Architects Now!” If you are in software development or you’re a software engineer you will be much more valuable if you bring a software architect mentality to every interaction and every project.
The rise of AI in software development is fundamentally reshaping the role of software engineers, prompting a shift from routine coding to higher-level architecture and system design. As AI automates more coding tasks, the value engineers provide is moving towards designing robust, scalable systems and deeply integrating advanced AI tools within complex business infrastructures.
How the Dynamic is Changing Software Creation
From Code to Architecture: AI excels at generating, completing, and testing code snippets, which reduces the demand for human effort on repetitive or well-defined programming tasks. As a result, experienced engineers are transitioning to roles as system architects, focusing on defining the architecture, integrating diverse technologies, and ensuring system resilience, scalability, and maintainability in AI-augmented environments.
AI as a Development Partner: Instead of replacing engineers entirely, AI acts as an intelligent collaborator. Engineers are spending less time on syntax and more on creative problem-solving, designing workflows, specifying requirements, overseeing large-scale integration, and making critical decisions about software quality, security, and performance.
Increased Complexity and Abstraction: As systems grow more sophisticated with distributed architectures, microservices, and cloud-native patterns, the expertise needed to orchestrate, monitor, and optimize these systems increases. AI tools amplify productivity by handling lower-level tasks, allowing human experts to concentrate on architectural “big picture” challenges.
Business Benefits of Retaining Experienced Engineers
Multiplying Impact with Deep Knowledge: Senior engineers understand the nuances, history, and context of enterprise systems. They can leverage AI tools to amplify their productivity—rapidly prototyping solutions, reviewing AI-generated code for correctness and security, and making judgment calls that require domain expertise and intuition built up over years.
Strategic Governance and Quality Control: AI may generate code, but it still requires experienced oversight to ensure solutions are robust, safe, performant, and compliant. Senior engineers set development standards, implement best practices, and are best positioned to scrutinize AI outputs for flaws or vulnerabilities that automated tools might overlook.
Faster Innovation, Lower Risk: By automating routine work, AI lets veteran engineers focus on innovation. This leads to quicker time-to-market for new features and less time spent on bug-fixing or maintenance. Their system-level thinking reduces the chance of strategic missteps, costly rework, or catastrophic failures.
Talent Development and Knowledge Transfer: Experienced engineers mentor less experienced colleagues and teach teams how to use, supervise, and adapt evolving AI tools. This ensures younger engineers don’t just become coders, but learn to think architecturally in partnership with AI.
Driving Business Transformation: The fusion of architectural expertise and AI is a powerful productivity multiplier, enabling businesses to tackle bigger challenges, enter new markets, and evolve more quickly in response to change.
In summary, while AI automates much of the “how” of software production, experienced engineers are increasingly responsible for the “what” and “why”—designing systems, governing standards, managing risk, and strategically guiding the business. Their combination of deep technical knowledge with the amplifying effect of AI tools is now one of the greatest multipliers for business productivity and long-term innovation.
This is lightning in a bottle for those business leaders who recognize the power of human knowledge, skills and experience and the rising AI and new tech ecosystems that are emerging.