Twenty years ago, I began my career at Accenture, and the world was completely different. I remember a colleague who had a thick Java or C# book on his desk while we were programming. At that time, there was no Visual Studio Code with its myriad extensions, no popular Stack Overflow, and no AI to assist us.
Even today, some people still maintain legacy systems in banks or government agencies — systems from an era when an Integrated Development Environment (IDE) could be as simple as a text editor.
For someone starting their career in tech today — especially as an intern in software engineering — the first experience in a corporate environment is incredibly exciting. They move from personal projects, tutorials, or university assignments to understanding what it's like to build enterprise-scale applications.
They interact with teams, learn about the business, and often specialise in one area, like frontend or backend development. For example:
- Frontend developers focus on frameworks like React or Angular
- Backend developers use tools like Node.js, Java, .NET, or Python
However, as AI increasingly dominates routine coding tasks, junior developers must start preparing for a world where code becomes a commodity — and architecture becomes a differentiator.
The Contrast Between Past and Present
In the past, developers invested countless hours mastering programming fundamentals before advancing to senior roles. Today, AI tools accelerate this journey by automating many common tasks.
Some companies are now experimenting with AI agents that automate tasks such as bug fixing or template generation. While this enhances productivity, it also puts pressure on junior developers to go beyond basic coding and think strategically about their career growth.
Core Fundamentals Still Matter
Even in an AI-driven world, developers need a deep understanding of software engineering principles. These fundamentals empower you to:
- Review and critically assess AI-generated code
- Take ownership and accountability for production-grade systems
- Build secure, maintainable software at scale
If you missed my last post on the risks of deploying unreviewed AI-generated code to production, check it out here:
Vibe Coding: Why You Shouldn't Trust AI-Generated Code in Production
Should You Shift Toward Architecture?
Absolutely. As code becomes more abstract (e.g., low-code platforms), developers should broaden their understanding of how software works end-to-end — including infrastructure, testing, security, and integration.
Example Roadmap from Backend Developer to Architect:
- Learn frontend development for full-stack context.
- Take ownership of CI/CD pipelines — understand builds and deployments.
- Explore QA beyond unit testing — learn about test automation.
- Understand cloud infrastructure and programmatic provisioning.
- Study secure coding practices and threat models.
This multi-domain exposure prepares you for roles such as:
- Full-Stack Developer
- Software Architect
- Solution Architect
What About Mobile Developers?
While mobile development (iOS/Android) is highly specialised, it can be isolating from broader trends. Some mobile engineers may lack exposure to:
- Enterprise-scale architecture
- CI/CD and infrastructure
- Full-stack workflows
Given that most companies have just one mobile app, developers in this area should consider expanding into cloud, backend, or integration work to broaden their career paths.
What About DevOps and SREs?
With pipelines now defined in YAML and embedded in codebases, many developers are learning DevOps concepts.
For DevOps engineers and SREs, now is a great time to:
- Learn infrastructure-as-code tools
- Dive into full-stack or backend development
- Explore platform engineering and observability
Their cross-functional skills make them great candidates for transition into broader solution roles.
What About Testers?
Testing is becoming increasingly automated. Tools like Katalon, AI-based test mapping, and open-source frameworks mean that testers must have coding skills to stay relevant.
Manual testers without technical growth risk being phased out. Instead, testers should consider:
- Learning test automation
- Exploring QA architecture
- Contributing to DevSecOps pipelines
Okay. What Should I Do Next?
Will all these roles still exist in 5 or 10 years? Or will they converge into hybrid roles where AI co-pilots assist human experts?
No one knows — but what remains true is this:
Stay curious. Stay adaptable. Keep connecting the dots.
The most valuable developers and engineers will be those who combine technical depth with architectural thinking — and who can effectively work alongside AI agents.
Final Thoughts
If you’re early in your career:
- Keep learning fundamentals.
- Explore beyond your comfort zone.
- Don’t just code — understand how systems fit together.
If you're more experienced:
- Think about becoming a solution architect, either as a generalist or within a specific domain.
- Master the language of business, scalability, and system integration.
What path are you taking in your software career? How are you preparing for AI-driven changes? Share your insights in the comments!
About the Author
Bruno Omizu is a Solution Architect with over a decade of experience in software engineering, solution architecture and technology leadership. He helps teams design and implement secure, scalable, and maintainable enterprise-grade systems across diverse industries.
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