Agent-heavy development needs a smaller blast radius.
Managed Forgejo for teams that want coding agents, CI, and private source code inside a dedicated forge with a written no-AI-training commitment.
Managed Forgejo for AI development
The forge matters more when software writes software.
Coding agents do not just touch prompts. They touch branches, pull requests, CI logs, secrets by proxy, generated artifacts, and the history behind a change. Fjord gives that work a dedicated Forgejo home operated for your team.
What Fjord does not solve
Fjord does not replace your review policy, secret hygiene, branch protections, or agent permission model. It gives those choices a dedicated managed forge to run inside.
What changes when agents join the workflow
Agents widen repository access
A coding agent with broad credentials can see more source history, issues, and branches than a human usually reviews in one sitting.
CI becomes part of the trust boundary
Agent-authored changes still flow through runners, secrets, artifacts, and deployment hooks, so the forge and CI boundary matter together.
Training policy should be explicit
Fjord has a written no-AI-training commitment for repository and CI content on dedicated instances, rather than a vague privacy slogan.
Tenancy is a concrete control
A dedicated Forgejo instance gives the team a clearer boundary for repos, runners, backups, exports, and administrative access.
Review the controls
Read the policy
Start with the no-AI-training page when the concern is how repository and CI content may be used.
Read the commitment ->
Check the architecture
Use the architecture page when the concern is tenancy, runners, backups, regions, and what Fjord does not claim yet.
Review architecture ->
Assess code exposure
Use the sovereignty tool when the concern is vendor concentration, AI policy, export, and operational control.
Run the assessment ->