Product development on Agiflow
Your coding agent's plan lives only in the chat thread. Close the terminal or switch machines, and there is nothing to pick back up.
The cost
Only the person who ran the last session knows what happened, and there is nothing to check the work against.
The shape
Agiflow holds the tasks, the acceptance criteria, the progress trail, and the review verdict. The agent reads and writes it over MCP.

The rules
Planning to Todo to In Progress to Testing to Review to Done.
Setup
The AgiFlow AI Plugin wires the MCP connection and adds the workflows, and setup is identical after install across Claude Code, Codex, ChatGPT. Here is how you check it worked.
The loop
Five workflows run in order: project-plan, refine-task, backlog-grooming, run-task, review-work. Nothing skips ahead: a task runs only after grooming promotes it, and closes only after review judges it.
Step 1 of 5
project-plan reads the project, checks for overlapping tasks, and asks only the questions it needs. It proposes a task list and waits for your approval before writing anything.
Step 2 of 5
refine-task names the ambiguities in one task and asks about the ones it can't resolve on its own. It rewrites vague criteria into observable behavior, without adding scope.
Step 3 of 5
backlog-grooming classifies every Planning task as ready, needs refinement, blocked, or duplicate. It proposes a priority order and suggested work units before it writes anything.
Step 4 of 5
run-task works the acceptance criteria one at a time, recording which files changed and what the tests returned. It lands in Review with a draft commit message and PR body.
Step 5 of 5
review-work gives every acceptance criterion a pass, fail, or partial verdict with the evidence used, and flags issues by severity. It approves the work or sends it back with specific instructions.

Start here
The full walkthrough, with every prompt and what you should see, is in the tutorial.