How to use the Prompt iteration log template

Start a board from it
Use this template opens a new Freero board with the Prompt iteration log template on it (sign up free first). On a board you already have, open Templates in the toolbar and search for “Prompt iteration log”.
Follow the instruction on the board
“Change one thing per version and run the same test cases every time. Keep losing versions in the log: they stop you trying them again.”
Fill in each part
- Table Columns: Version · What changed · Test cases passed · Notes · Keep?
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 Prompt iteration log 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.

Team prompt library
The prompts your team reuses, with the inputs each one needs, when it works best and who keeps it up to date.
Red team session
Spend an hour trying to make an AI feature misbehave: the attempts, what worked, how bad it was and the fix.
Golden test set
Build the set of test cases an AI feature must pass: realistic inputs, the expected answer, tags and why each case matters.
Eval review board
Go through test cases for an AI feature: the input, what good looks like, what it actually said and the verdict.
Agent workflow design
Design a workflow an AI agent runs: what starts it, what it gathers, what it does, how its work is checked and how it hands back.
AI use case canvas
Think an AI idea through before building it: the problem, the people, the data, what good looks like, risks and who stays in the loop.