I recently attended a great talk at ParisJUG hosted at Doctolib, where Patrick Chanezon spoke about:
“The transformation of the developer role with AI agents.”
This topic strongly resonated with my daily work as a Senior Java Engineer working with AI-augmented development.
Here are three reflections from my experience.
1. From Developer to Agent Manager
With the rise of AI agents, our role as developers is clearly evolving.
I find myself spending less time writing every line of code, and more time:
- defining context
- designing architecture
- guiding AI agents that implement solutions
In many ways, we are moving from:
Developer → Agent Manager
The value is shifting toward:
- orchestration
- validation
- system thinking
Writing code is no longer the bottleneck.
Thinking clearly is.
2. AI as a Mentor… but with a Risk
AI can dramatically accelerate learning.
For example, reading a 600-page technical book can take days or weeks.
With tools like NotebookLM, you can extract key insights in a few hours.
But from my experience, something is lost in the process.
Traditional reading improves:
- retention
- depth of understanding
- long-term intuition
The real risk is simple:
Delegating too much thinking to AI.
The right approach is:
- Use AI as a teammate, not a replacement
- Let it challenge your ideas
- But keep ownership of the reasoning
AI should amplify your thinking — not replace it.
3. The Hidden Topics: Dopamine and Cost
Two topics are often underestimated when working with AI:
Dopamine & Feedback Loops
AI creates extremely fast feedback cycles:
- you generate an idea
- AI implements it instantly
This is powerful, but it can also lead to:
- very long sessions
- mental fatigue
- reduced focus
Cost Awareness (AI FinOps)
Another key aspect is cost.
Without proper practices, usage can grow very quickly.
From my experience, a few simple habits help:
- switching models depending on the task
- using different agents for different needs
- writing precise prompts with strong context
This is essentially AI FinOps for developers.
Conclusion
AI agents are not replacing developers.
But they are clearly transforming our role toward:
- orchestration
- system-level thinking
- higher-level decision making
The real challenge is not adopting AI.
It’s learning how to use it ntelligently and responsibly
Thanks to Patrick Chanezon for the inspiring talk
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