How we introduce agentic AI in your development organization

AI-assisted means developers use AI as a helper — typically Copilot in the editor for code suggestions. The process and the roles stay the same. AI-first means AI agents are the primary builders and humans steer direction, architecture, and quality. The entire delivery model is rebuilt. The difference is fundamental, not gradual.

AI-generated code goes through the same or stricter quality gates as human-written code. Three parallel AI reviews on every pull request, automated security scans, test runs, and human review before merge. In practice, quality often improves because AI doesn't skip tests or documentation under deadline pressure.

Our framework Fae is built for regulated environments from the ground up. You retain control over where the AI runs (your Azure tenant or on-premise), what it sees (least-privilege per agent), and what it's allowed to do (configurable autonomy level). Every prompt, tool call, and code change is logged for full traceability. We're already building a bank under the Swedish FSA's supervision this way.

They shift roles from writing code to leading agents and reviewing results. A senior developer becomes an architect who defines what "good" means and ensures the agents follow it. It's a skill shift, not a layoff. Experienced developers become more effective; junior developers need to learn a new discipline: harness engineering.

No. We meet you in your existing workflow — Jira, Azure DevOps, GitHub, GitLab, your CI/CD pipelines. We adapt Fae to integrate with your systems. No rip-and-replace. As your organization matures in AI-first ways of working, you can choose to standardize more or less.

A pilot with a single team can be up and running within 4-6 weeks. A full transformation of a development organization typically takes 6-12 months and happens in phases: pilot, expansion, standardization. The pace depends on your existing maturity, regulatory requirements, and your change capacity.

You own everything. All code belongs to you. All data stays inside your infrastructure. There's no vendor lock-in — Fae uses standard protocols and your code is regular code, not a proprietary format. If you want to continue on your own or with another partner, you can do so without friction.

Copilot and Cursor are tools for individual developers. They make a developer roughly 20-30 percent more productive. We rebuild the entire delivery model with AI agents as the primary builders — that's 5-10x productivity, not 20-30 percent. We often use Copilot or Cursor as components in the solution, but they are not the solution itself.

A team open to trying new ways of working, a bounded pilot where we can demonstrate the effect concretely, and an executive sponsor. We need access to relevant repos and development environments. Everything else we set up together. We often start with a two-week workshop mapping your current state against the AI-first model.

We measure both speed and quality. Speed: time from requirements to production, pull requests per week, lead time for bug fixes. Quality: production defects, test coverage, code review time. And business metrics: delivery against the roadmap, time-to-market for new features. The measurement is set up together with you before the pilot starts so you have a baseline to compare against.