What is agentic software development? A practical definition

Agentic software development means AI agents plan, build, test, document and monitor software, while agentic engineers set direction, judge solutions and outcomes, and make the decisions. The agents are the primary builders, and people stay accountable for the result. That makes it a new delivery model, where implementation capacity grows with the agents instead of with human hours.

How it works

The work is split between agents and people. The agents have four roles:

• Plan: break the needs down into concrete tasks.
• Build: write the code, the tests and the documentation.
• Review: check quality and security in every change.
• Monitor: watch the systems in production and fix the simple things right away.

The people, our agentic engineers, have three:

• Set the direction: understand the business and prioritise what creates the most value.
• Make the decisions: architecture, trade-offs and everything that takes judgement.
• Take responsibility: for quality, security and delivery, also after launch.

In practice, the agents pick up work items from the boards the organisation already uses, such as Azure DevOps or GitHub, implement them and open pull requests. Every change passes automated tests, security scans and AI reviews, with human decision points where they matter. Decisions and context are captured in a knowledge bank about the business, so the agents act on the same facts as the people directing them, and the knowledge stays with the organisation.

Assistant or agent

AI-assisted development, with coding tools in an editor, makes an individual developer faster while the process and the roles stay the same. Agentic development rebuilds the model around the agents. The agents do the implementation, and the people judge solutions against specifications, architecture and test results. The conversation moves from percentages to multiples, because implementation capacity grows with the agents.

What becomes possible

• Faster delivery: the agents do the programming, which makes up most of the work in a typical development project.
• Higher quality: the things that usually get cut when a project is under pressure, such as tests, QA and documentation, now fit.
• More within the same budget: what used to be too expensive to justify becomes possible.

Who takes responsibility

The common failure of AI-generated software is missing accountability. Agentic development done right pairs autonomous implementation with explicit human ownership of architecture, quality and security. The agents work with the least privilege possible, every prompt, tool call and code change is logged, and people approve what goes into production. That traceability is what makes the model work in regulated environments.

Agentic software development in Sweden

Wizardworks is an AI-first consultancy in Helsingborg that delivers this way for customers across Sweden, mainly in the Microsoft, .NET and Azure ecosystem. Examples are the data solutions, integrations and IoT for Gito and the data warehouse and integrations for Sportswik.

If you are comparing agentic AI companies in Sweden, four questions show how the delivery is built:

• Do the agents implement? Ask to see agents picking up work items and opening pull requests.
• Who is accountable? A named person should own architecture, quality and security for every delivery.
• Is the work traceable? Prompts, tool calls and code changes should be logged.
• What are you paying for? With agents doing the implementation, delivery can be sold as results, for example a development team as a subscription at a fixed monthly cost.

Curious what it would look like in your organisation? See how we work with you or read how we work.