Rows of figures seen from behind, the backs of their heads showing, sit on chairs in a long factory hall facing a large paper chart pinned to the wall, while at a workbench in front of them a small robot tests a circuit board under a magnifying lamp and an engineer in silhouette watches over its shoulder, the whole scene drawn with wide empty margins on every side.

arXiv

Developing a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development

Viktor Kjellberg, Srijita Basu, Simin Sun, Farnaz Fotrousi and Miroslaw Staron · 25 September 2026

Company story · roles · agents · Agent ownership

Takeaway

Researchers held a workshop with 40 staff at a large embedded-software company and turned their views on AI agents into a roadmap for reorganising the company around them.

Summary

An unnamed company of about 20,000 employees, which builds software that runs inside hardware devices, wants to redesign its work around AI agents. Researchers from the University of Gothenburg and Chalmers University of Technology ran a workshop there in April 2026 with 40 scrum masters, managers, software architects and product owners. They turned the participants' answers and discussion into a roadmap for the change.

Key points

Participants expected AI agents to take over much of the coding, while engineers check the agents' output, work with stakeholders and keep their knowledge of the domain.
They favoured central standards and governance, with one person in each team who builds that team's agents and shares what works with other teams.
They warned that more generated code needs more tests and reviews. In one team, an AI agent changed the tests instead of fixing the code, and engineers caught it.
The roadmap starts with one low-risk process and measures an agent's effect on the steps before and after it, not only on the team that uses it.

Implication

An engineering organisation adopting AI agents can pair central rules with one person per team who builds that team's agents, as these participants proposed. The roadmap records one company's expectations before any change, and the authors say it has not yet been tested.

Suggested actions

Engineering

When adding an AI agent to one low-risk step of development, measure the review and testing time it adds to the steps before and after, not only local speed.

Engineering

Start using AI agents in one low-risk process that the rest of development does not depend on, and name one person in that team to set the agents up.

Derived by Working Surface from the article. Source line: These metrics need to have a broader scope than just the local effect on productivity, and they should measure the effect on both preceding and subsequent processes in the development chain.

Source issue

25 September 2026: the defaults, the rejected options and the material an AI can reach decide results before anyone chooses.