Your agent says "Done." nobrainer-tech-flow shows what was delivered, the proof, what was not checked and what is left for you to decide. One open-source workflow for Codex, Claude Code, Cursor and other coding agents, instead of 50+ separate tools. Set up with one message: the agent verifies the release, shows the planned changes with a rollback path, then installs. Free, MIT. Your client's own usage costs still apply.
Hi Product Hunt. I built nobrainer-tech-flow because "Done!" from an AI agent rarely tells you what was actually done.
It is one open-source workflow for the coding agent you already use (Codex, Claude Code, Cursor, GitHub Copilot CLI, OpenCode, Gemini CLI, Kimi Code, Pi), instead of piecing together 50+ separate skills and tools. It asks only what matters, scopes the work, carries it through and checks it. The handoff says what was delivered, the proof, what was not checked and what is left for you to decide.
Setup is one message: copy the prompt from https://nobrainer.tech/flow/ and paste it into your agent. It verifies the release, shows the planned changes with a rollback path, then installs. Free and MIT; your client's own usage costs still apply.
The two short films on the page show the idea in under a minute. One question for you: when an agent says a task is done, what evidence do you want to see before you trust it?
Hi Product Hunt. I built nobrainer-tech-flow because "Done!" from an AI agent rarely tells you what was actually done.
It is one open-source workflow for the coding agent you already use (Codex, Claude Code, Cursor, GitHub Copilot CLI, OpenCode, Gemini CLI, Kimi Code, Pi), instead of piecing together 50+ separate skills and tools. It asks only what matters, scopes the work, carries it through and checks it. The handoff says what was delivered, the proof, what was not checked and what is left for you to decide.
Setup is one message: copy the prompt from https://nobrainer.tech/flow/ and paste it into your agent. It verifies the release, shows the planned changes with a rollback path, then installs. Free and MIT; your client's own usage costs still apply.
The two short films on the page show the idea in under a minute. One question for you: when an agent says a task is done, what evidence do you want to see before you trust it?