https://featureloom.com/en/blog/ Articles by the featureloom team on working with AI agents: how to plan that work, write plans the agents will realize, and accept what they deliver. en Sun, 01 Nov 2026 00:00:00 GMT Sun, 01 Nov 2026 00:00:00 GMT https://featureloom.com/en/blog/a-plan-an-agent-can-deliver/ https://featureloom.com/en/blog/a-plan-an-agent-can-deliver/ How do you write a task so an AI agent doesn’t have to guess what you want? Give it a plan with a goal, scope, acceptance criteria and a definition of done. The agent then gets what it can’t learn from the code, and knows how to tell when it has finished. featureloom Sun, 01 Nov 2026 00:00:00 GMT https://featureloom.com/en/blog/claude-code-in-a-team/ https://featureloom.com/en/blog/claude-code-in-a-team/ When several people on a team start working with Claude Code, it is easy to lose track of who is doing what and who decided the work was finished. Agents work well in a team when the work is split into plans in a clear order and a person accepts the result of each plan. featureloom Sun, 01 Nov 2026 00:00:00 GMT https://featureloom.com/en/blog/several-ai-agents-in-one-project/ https://featureloom.com/en/blog/several-ai-agents-in-one-project/ Multiple AI agents in one project get in each other’s way when sessions change the same files, do the same thing, or start a task that waits on another session’s result. Two rules help: each session delivers one plan in its own folder, and dependencies between plans show what can start right away and what has to wait. featureloom Sun, 01 Nov 2026 00:00:00 GMT