How to use the Model option comparison template

Start a board from it
Use this template opens a new Freero board with the Model option comparison template on it (sign up free first). On a board you already have, open Templates in the toolbar and search for “Model option comparison”.
Follow the instruction on the board
“Score every option on the same test set from your real work. Quality on your cases beats any public leaderboard.”
Fill in each part
- Table Columns: Compare on · Large hosted model · Small hosted model · Self-hosted open model
- Decision What we chose and when we’ll recheck.
Bring your team and your agents
Invite people to the board or share a link, and work on it together live. The timer is in the top bar, private mode and voting in the board menu, and Claude or ChatGPT can join through Freero’s MCP server.

Work on it with an AI agent

Connect an assistant once and it works on the board with you, with your permissions: by default it reads and proposes, and people decide.

You ask: “Fill in the Model option comparison board from these notes.”
What happens It reads the board, then proposes sticky notes for it. Nothing changes until someone on the board accepts them.
You ask: “Group what we wrote into themes and list the actions.”
What happens It proposes clusters with a title each and task cards for the actions, labelled with its name and yours.

Agent run review
Step through one run of an AI agent: what it did at each step, whether it was right, and what to change in its instructions or tools.
Eval review board
Go through test cases for an AI feature: the input, what good looks like, what it actually said and the verdict.
AI pilot plan
Run a small, honest pilot of an AI tool: the job it should do, the baseline, a test group, what you measure and the decision at the end.
Agent permissions review
Decide what an AI agent may do on its own, what needs a person’s approval and what it must never do, action by action.
Prompt iteration log
Keep track of how a prompt evolves: each version, what changed, how it did on your test cases and whether to keep it.
Agent incident review
Look into a time an AI agent got something wrong: what happened, why it happened, why checks missed it, and what changes.