8. September 2025 By Annette Kauppinen and Ville Vuorio
From Assistant to Collaborator - How AI Is Changing the Craft of Coding Part 2
Blog 2 of 6 — From Workflow Support to Organizational Shift: How AI Is Redefining Software Teams
In the first part of this series, we looked at how AI coding agents like Roo Code are helping developers move faster, stay in flow, and offload repetitive tasks. But while those benefits show up at the individual level, the most profound changes happen when AI tools begin to reshape how entire teams and organizations work.
As a consultant at adesso Finland, Ville Vuorio has seen this transition up close across multiple client projects. “It starts with productivity,” he explains, “but the moment AI becomes embedded in the delivery pipeline, it begins to change how teams function.”
AI agents beyond the IDE
In modern software teams, AI tools are no longer confined to suggesting code snippets inside an IDE. They're branching out—into CI/CD pipelines, documentation processes, test automation, even incident response. What once required multiple people across different functions can now be partially handled by specialized AI agents working behind the scenes.
AI Agent can help clients integrate AI agents that:
- Generate and maintain technical documentation
- Create test cases and validate outputs
- Assist in debugging and reviewing pull requests
- Suggest architecture improvements during design discussions
“This is where AI stops being just a tool and starts becoming part of the system,” Ville says. “It’s not just helping the developer—it’s supporting the whole software lifecycle.”
New team dynamics: who’s doing the work?
As AI agents become embedded in the workflow, the boundaries of team roles begin to shift. Code is still reviewed by humans, but the first draft might come from an agent. Documentation isn’t written from scratch—it’s suggested, edited, and published collaboratively. Testing is no longer just automated—it’s generated and maintained by intelligent assistants.
For client teams, this raises new questions:
- Who owns the AI-generated output?
- How do we maintain oversight when agents act autonomously?
- What happens to team dynamics when “teammates” aren’t human?
“These aren’t just technical questions,” Ville points out. “They’re cultural and organizational. The definition of collaboration is changing.”
Responsible integration requires structure
To make AI agents truly valuable—and safe—teams need more than access. They need governance.
This includes:
- Audit trails to track who (or what) did what
- Approval workflows for AI-generated changes
- Role-based access to ensure agents operate within proper boundaries
Platforms like Cline make this easier by offering team dashboards, permission models, and credit allocation—enabling organizations to treat AI agents like real contributors.
Ville has seen how this clarity improves trust. “Once a team understands how the agent works, where it fits, and what it’s allowed to do, they stop hesitating. They start collaborating.”
It’s not about replacing people—it’s about scaling them
For many organizations, the biggest value of AI isn’t speed—it’s scalability. A single team can now do more, not by adding headcount, but by adding capable digital teammates.
This is the real promise: developers still lead, decide, and create—but they’re no longer burdened by everything. The machine handles the routine. The human stays in control.
Leadership sets the tone
Adopting AI in teams isn’t just a technical decision—it’s a leadership one. In the projects Ville supports, success depends heavily on how change is introduced.
“The best results come when leaders give people space to experiment,” he says. “You don’t force AI on the team. You show what it can do and let them shape how it fits.”
That includes providing training, setting expectations, and creating feedback loops. It’s also about recognizing that not everyone will adopt at the same pace—and that’s okay.
Culture change takes time. But when it happens, it sticks.
This is part 2 of a 6-part blog series: From Assistant to Collaborator – How AI Is Changing the Craft of Coding
In Blog 3, we’ll explore the non-negotiables of AI adoption—security, privacy, and trust. Because no matter how capable your AI agents are, they must earn their place through transparency, control, and compliance.
