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 practitioners. Leaders and teams have 13 accounts; GILD prints their sentiment from 20.
Engineering leaders and teams
20 sources. These accounts focus on data paths, permission defaults, and running OpenCode headless inside a team's own pipeline.
Individual builders
70 sources. These accounts focus on model and plan choice, spend, the terminal experience, and what breaks between releases.
All practitioners
90 sources. This count includes every practitioner: individual builders and the team and leadership accounts together.
90 sources from practitioners, by the context they work in. Filled rows count for this group.
- Individual practitionerSolo developers and independent builders70 sources, counted here
Emphasizes Model and plan choice, spend, and setups that break between releases
- Very small team2 to 10 engineers, or a team of unstated sizeNo sources from this setting yet
- Professional team11 to 50 engineers, or a named company's team9 sources, counted here
Emphasizes Token overhead measured against Claude Code
- Technical leadershipLeaders assessing tools across teams9 sources, counted here
Emphasizes Headless agents on the SDK, project plugins, and prompt caching
- Organization-wideEnterprise or company-wide rollout2 sources, counted here
Emphasizes One login that configures models and permissions for every engineer
What changes with scale. Individual builders pick OpenCode for model choice and cheap open models, and leave it over defaults, data paths, or release churn. Team accounts use it as infrastructure: a headless server their own orchestrator or CI drives, measured for token and cache cost before it is trusted with volume.