Don't be a ticket engineer.

Imagine one day, you’re scrolling through your Jira tickets, and the latest ones are marked as resolved — by AI. Why wouldn’t it be? If it had access to the code, understands the requirements, and has been trained on previous human input, it’s perfectly capable of completing the task. You however, are left wondering: What’s the point of me doing this anymore?

This isn’t a hypothetical scenario anymore. As AI rapidly reshapes software development landscape, a large percentage of engineers face a clear choice: evolve and bring strategic value or risk being replaced.

With tools like ChatGPT, GitHub Copilot, and other LLM-based workflows, much of the repetitive coding, bug-fixing, and routine feature development can be automated. Engineers who focus solely on picking up tickets—narrowly defined tasks—are setting themselves up to become obsolete.

The Ticket Engineer Trap

Picture a typical workday in a large enterprise. You log in, grab a task from the backlog, implement a solution, and move on. There’s no room for reflection, no question of why this task is important or if there's a better approach. You’re simply executing orders, day in and day out. It’s a reactive, task-based routine — and it's where many engineers get stuck. These engineers are often the first to face layoffs when companies need to trim their teams.

1. AI excels at predictable tasks:

   AI shines when it comes to predictable tasks with explicit instructions. Give it a ticket with clear, well-defined requirements, and it will churn out code faster and often more accurately than you could. If your role is to execute these tasks, you’re competing directly with LLMs and ultimately, you’re losing.

2. There is no room for creativity or leadership:

   As a ticket engineer, you rarely get involved in the creative parts of the process — system design, architectural decisions, and product innovation. These are the areas where human ingenuity thrives and where AI still falls short. If you’re absent from these discussions, you're sidelining your career potential.

3. Limited ownership breeds stagnation:

   Limited ownership in development is akin to working at an assembly line, churning out parts without envisioning the final product. By only working within narrow boundaries, you miss out on broader, cross-functional experiences that can enhance your skill set—like product thinking, UX design, and business strategy. This lack of exposure can restrict your value within the team and your future opportunities.

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The solution: Be value-oriented.

For every ticket you pick up, pause for a moment and ask yourself:

• Why is this important?

• What value does it bring to the user?

• Is there a better solution?

By understanding the intent behind a task, you’ll not only be able to implement it more effectively, but you’ll also be able to propose better solutions or even eliminate unnecessary work. This is how you demonstrate strategic thinking as an engineer — not just by executing tasks but solving problems in a way that drives real impact.

1. Work cross-functionally

   If possible, work with designers and product managers to understand the bigger picture behind the tasks that you’re assigned. Early on in the design process, you could offer suggestions and even influence the final product rather than merely carrying them out. Consider yourself a user, foresee potential problems, provide suggestions for UI/UX enhancements, and make sure your work satisfies user needs.

2. Upskill in areas AI can’t easily replace

   Learn how to design systems that are scalable, effective, and maintainable to make sure you’re contributing at a level AI isn’t equipped to reach yet. Communication, leadership, and mentoring are also human-centric qualities that AI finds difficult to mimic. In technical discussions, code reviews, and team alignment, take the initiative.

3. Learn to leverage AI

   But don’t just view AI as competition—use it to your advantage. I could write an entire post about this one but the key here is in mastering AI tools to exponentially increase your productivity by automating mundane tasks, freeing you up to focus on more complex challenges.

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I recently came across a post on daily.dev by Saqib Tahir that helped me visualize the journey from task-oriented work to strategic ownership. The post breaks down the seniority progression into six levels:

• Level 1: Here’s the problem, the solution, and how to implement it.

• Level 2: Here’s the problem and the solution. Figure out how to implement it.

• Level 3: Here’s the problem. Figure out the solution.

• Level 4: Here’s a list of problems. Identify the most impactful one to solve.

• Level 5: Find all the problems and determine which are worth solving.

• Level 6: Predict future problems and create systems to prevent them.

This progression illustrates what I’m advocating for. Moving from executing tasks to becoming value-oriented is how you climb the seniority ladder. When you think beyond solving immediate problems—identifying, prioritizing, and even preventing them—you’ll not only evolve from being a ticket engineer but also elevate your contribution to the team and accelerate your career growth.

As an engineering lead at an AI-first company, I’ve seen firsthand the difference between engineers who simply follow orders and those who take ownership of their work. The latter group brings ideas, challenges assumptions, and drives projects forward in ways that no AI tool can. As professionals in a rapidly changing industry, being adaptable is what sets us apart.