The prompt improvement cycle
WorkflowsVai em: Chat
For prompts you will run more than once. Instead of tweaking wording and hoping, this makes the notebook grade its own last answer against the sources, then rewrite the prompt that produced it. Three passes usually gets further than an afternoon of manual fiddling.
Compartilhado por Guillaume Martin (notebooklm-prompts) — o crédito é de quem merece.
Act as a prompt engineer reviewing your own previous answer. Step 1 — Grade it. Mark each claim in your last answer as: supported by the sources, inferred beyond them, or unsupported. Give the counts. Step 2 — Diagnose the prompt, not the answer. Which instruction in my prompt allowed the weak parts through? Be specific about the wording at fault: vagueness, a missing constraint, or an assumption I left implicit. Step 3 — Rewrite my prompt so those failures are impossible rather than discouraged. Keep it as short as the job allows. Step 4 — Name the one thing your rewritten prompt still cannot guarantee, so I know what to check by hand.
Como usar
- 1Abra seu notebook em notebooklm.google.com.
- 2Substitua as partes [entre colchetes] pelas suas informações.
- 3Cole o prompt na caixa de chat e envie.
Colchetes marcam as partes que você substitui pelo seu tema ou pergunta.
Mais prompts de workflows
- Triage your sources before you synthesiseStep one of any multi-source project. Run this before asking for a synthesis and it tells you which sources actually earn their place, which duplicate each other, and where the collection has a hole. Ten good sources beat fifty mediocre ones, and this is how you find out which ten you have.
- Multi-source synthesis into a Video OverviewA three-stage pipeline: synthesise everything in chat, save that answer as a note, then generate the video from the note alone. Generating straight from twenty sources gives you a wandering video; generating from one tight synthesis gives you a focused one, because the model is no longer choosing what matters while it narrates.
- From notebook to a finished deliverableThe last mile: you have read everything and now something has to leave the notebook. This asks for the deliverable and its evidence trail in one pass, so the draft arrives with the citations already attached instead of you rebuilding them afterwards.