Three groups drawn from the same sources. Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. Signals open on All users. Leaders and teams have 15 accounts; GILD prints their sentiment from 20.
Leaders and teams rolling it out
24 sources. These accounts focus on governance, credit costs, and agents that behave differently once published, from teams, admins, and organization-wide rollouts.
Individual users
28 sources. These accounts focus on how hard agents are to build, answer quality, and day-to-day failures, from people building their own agents.
All users
52 sources. This gives the broadest read, but combines one person's agent with organization-wide rollouts, which can reach different conclusions.
52 sources from practitioners, by the context they work in. Filled rows count for this group.
- Individual userOne person using it for their own work28 sources, counted here
Emphasizes Ease of building, answer quality, and bugs in topics, prompts and flows
- Small team2 to 10 people sharing itNo sources from this setting yet
- DepartmentA department, or a named company's team19 sources, counted here
Emphasizes Agents that break after publishing to Teams, credit costs, and security research
- IT & leadershipIT and business leaders deciding the rollout1 sources, counted here
Emphasizes Model choice and connector behavior measured on a real job
- Organization-wideCompany-wide rollout4 sources, counted here
Emphasizes Gated rollouts, admin controls, and credits used outside cost policies
What changes with scale. Individual builders report bugs and how hard agents are to build. Team and admin accounts raise governance and agents that break once published, and organization-wide accounts gate who may build at all and watch where credits go.