The Future of Software Engineers. Embracing a New Era

The Future of Software Engineers. Embracing a New Era

2025-02-11 08:00:005 min read

Imagine an AI that writes code, tests it, and even deploys systems. It may sound like science fiction. But it could be our future. I have been a software engineer for 10 years. My career has been full of exciting projects, good work conditions, and great opportunities. When I started, my work was very challenging but also very rewarding. Today, technology is changing our field quickly, and our roles are changing in ways we could not imagine before.

In this post, you’ll explore the rapid evolution of AI in software engineering, learn about the emerging concept of the “Agentic SDE,” and consider how these changes might reshape our daily work and team dynamics.

The Rapid Evolution of AI in Software Development

Today, AI is changing our work very quickly. AI can now write code read technical documents faster than most people. Here is a simple timeline of some important events in AI:

  • October 2018 – BERT by Google:
    Google introduced BERT, a model that many later language models were based on.

  • February 2019 – ChatGPT-2 Released:
    This model mostly produced English text. It could also write simple code, but it was not specialized in coding yet.

  • June 2020 – ChatGPT-3 Released:
    GPT-3 greatly improved how computers understand and generate language. It helped write basic code, fix bugs, and offer coding advice. This model also inspired other models like Codex.

  • October 2021 – GitHub Copilot:
    GitHub Copilot used Codex to help developers by completing code automatically. It could read simple comments written in natural language and suggest code blocks. I found it very useful.

  • March 2023 – GPT-4 Released:
    GPT-4 improved even more in understanding language and context. It produced better code and solved problems more effectively.

  • October 2024 – Sonnet Released:
    Sonnet added design ideas with strong reasoning. It helped connect high-level design with working code. For me the best model to write code.

  • October 2024 – bolt.new:
    bolt.new is a tool that lets developers create excellent frontend applications using simple English commands. Many parts of projects like pepy.tech were built using bolt.new.

  • December 2024 – o1 Released:
    o1 is the first model that can reason step by step. It improves its answers over time to produce better results.

  • February 2025 – GitHub Copilot Agent Mode:
    This update lets Copilot automatically review and fix code, handle runtime errors, and suggest terminal commands. It makes developers much more productive (or useless?).

The Journey and Responsibilities of a Software Development Engineer

In the early days, becoming a good software engineer needed strong computer science knowledge, deep understanding of networks, system design, and the willingness to keep learning. Even though it was not always easy, these challenges made our work more fun and rewarding. They built the strong foundation for our diverse role as software developers.

A Software Development Engineer (SDE) has many important tasks, such as:

  • Design and Architecture: Creating maintanable and scalable system designs.
  • Code Implementation: Turning ideas and designs into code.
  • Testing: Making sure every part of the code works correctly now and in the future.
  • Code Reviews: Working together with other engineers to keep high-quality code.
  • Maintenance: Updating and improving existing systems.
  • Documentation: Writing clear docs for current and future team members.
  • Deployment and Operational Support: Leading software releases and making sure systems run smoothly.
  • Continuous Learning: Staying updated with new tools and industry trends.

This mix of technical rigor and multifaceted responsibilities not only built our expertise and shaped our early careers, but it also paved the way for the major changes we see in the software industry today.

Embracing the Agentic SDE

What Is an “Agentic SDE”?

An Agentic SDE represents the next evolution in our field. This role leverages advanced AI tools to:

  • Understand Complex Requirements:
    It figures out complicated needs without detailed step-by-step instructions.

  • Design, Test, and Deploy on Its Own:
    It uses past information, best practices, and real-time data to manage the whole development process by itself.

  • Work Together with Human Engineers:
    It helps by taking care of routine tasks, so human engineers can focus on creative and strategic work.

This mix of advanced AI and traditional software skills marks the start of a new era.

Redefining the SDE Role

The work of an SDE is changing in several important ways:

  • SDE as a Strategist:
    With AI handling routine tasks, human engineers can focus on solving hard problems, making smart decisions, and designing complete systems. Skills like creative design and overall planning become very important.

  • SDE as a Product Engineer:
    Future SDEs will not only write code but also help design products that meet real user needs.

  • Human-AI Collaboration:
    Even though AI can do many tasks on its own, human guidance is still needed for important decisions.

  • Accountability:
    Even if AI writes most of the code, humans are still responsible. We must ensure our systems are secure, ethical, and reliable.

  • Support and Troubleshooting:
    When unexpected problems arise that AI cannot solve by itself, a human must step in to fix the issues.

Redefining Teams in the Age of AI

In the past, a team might have had a manager, 6–10 developers, and a product manager. In the near future, companies might create smaller, multi-skilled teams. In these teams, one person might work both as an engineer and a product manager. This new combined role will require:

  • Strong Technical Skills:
    Good knowledge of computer science to use and control AI tools well.

  • Product Focus:
    The ability to balance technical work with decisions that benefit the user.

  • Good Communication Skills:
    Clear and effective communication is very important when working with both AI agents and other people.

As companies streamline operations, decisions will need to be made about whether to expand feature sets or focus on efficiency by reducing team size.

Future of teams

Conclusion

The path ahead will be challenging and exciting. Stay humble.

I invite you to share your thoughts. What excites you most about the future of our field? Have you experienced a shift in your work with the integration of AI tools?