[Steve Side Hustler]

I have a lot of quick notes (voice memos, a Notes app, email ideas) and I’d like a simple, non-technical way to turn them into clear tasks in either Todoist or Notion using AI.

Can anyone share practical workflows, tools, or step-by-step examples that work well for beginners? I’m especially interested in:

• Which no-code tools or services to use (for example, simple connectors or automations).
• How to format prompts so AI creates concise tasks with due dates, priorities, or tags.
• Example recipes or short automations for both Todoist and Notion.
• Common pitfalls to watch for and tips to keep things reliable and private.

If you can, please share a short, copy-paste prompt or a very brief step list that someone over 40 with limited tech skills could follow. Thanks — I’d love to try a few simple approaches and hear what worked for you.

[aaron]

Quick hit: Good call focusing on Todoist and Notion — they’re the best targets for turning notes into actionable work.

The problem: Notes sit in inboxes, pocket apps, or Notion and never become tasks. The result: missed deadlines and wasted time.

Why it matters: Every uncaptured action is friction. Converting notes into tasks reliably saves time, prevents things falling through the cracks, and gives you measurable progress.

What I’ve learned: Keep the workflow simple: capture → parse → map → confirm. Use AI to parse natural language into structured task fields, then push to Todoist or Notion via an automation tool (Zapier/Make/Shortcuts) or direct API if you’re comfortable.

1. What you’ll need
   1. Accounts: Todoist and/or Notion.
   2. An automation layer: Zapier, Make (Integromat), or Apple Shortcuts.
   3. An AI agent: ChatGPT, Claude, or any LLM that can parse text.
   4. API tokens for Todoist/Notion if using direct integration.
2. How to implement (step-by-step)
   1. Decide input source: email inbox, a notes folder, or a Notion capture page.
   2. Create an automation trigger: new email / new note / new database entry.
   3. Call the LLM: send the note text and ask it to extract title, due date, priority, project/tag, and a 1-sentence task description.
   4. Map the parsed fields to Todoist or Notion fields and create the task/item via the automation action.
   5. Send a confirmation back (optional) for manual review before creation.

Copy-paste AI prompt (use as-is)

“You are an assistant that converts a free-form note into a task. Given this note, extract and return JSON with fields: title (short), description (one sentence), due_date (YYYY-MM-DD or null), priority (low/medium/high), tags (array), project (string or null). If no value, return null. Note: if due date mentions ‘tomorrow’ resolve relative to today’s date. Note: keep title under 8 words.”

What to expect: Initial setup 1–3 hours. After that, 10–30 tasks automated per day depending on volume. Expect edge-cases: ambiguous dates, complex notes.

Metrics to track

• Tasks created per day (automation vs manual)
• Conversion accuracy (%) — tasks requiring manual edit
• Time saved per week (minutes)
• % tasks with due dates

Common mistakes & fixes

1. Ambiguous dates — enforce a confirmation step or use relative-date parsing.
2. Too many tags — limit to 3 or use a project-first mapping.
3. Overcomplicated parsing — keep JSON schema minimal.

1-week action plan

1. Day 1: Pick input source and automation tool; get API token.
2. Day 2: Build trigger and a simple action that records raw notes to a holding table.
3. Day 3: Integrate LLM call with the prompt above; parse into JSON.
4. Day 4: Map fields to Todoist/Notion and create test items; iterate.
5. Day 5–7: Monitor, measure accuracy, tweak prompt and mappings.

Your move.

Aaron

[Jeff Bullas]

Hook: You can turn messy notes into tidy, actionable tasks in 15–30 minutes using AI and simple automations. Let’s make your notes work for you — not the other way round.

Why this matters: If you capture ideas in notes but never convert them into tasks, they don’t get done. AI can read, extract, prioritize and format tasks for Todoist or Notion, saving time and mental overhead.

What you’ll need

• Accounts: Todoist or Notion (or both)
• An automation tool: Zapier, Make, or a simple script using the Notion/Todoist API
• An AI: ChatGPT or another LLM (via web or API) to parse and structure notes
• Sample notes you want converted

Step-by-step: build a simple workflow

1. Decide the source: pick where your notes live (phone notes app, email, Notion page).
2. Create a trigger in your automation tool: new note or new page created.
3. Send the note text to the AI with a prompt that asks for tasks, priorities, due dates and tags.
4. Parse the AI response into structured fields (task title, description, due date, priority, project/tag).
5. Create the task in Todoist or append a row/page in Notion with those fields.
6. Test with 3–5 real notes, tweak the prompt and mapping until results are reliable.

Copy-paste AI prompt (use as-is)

“You are an expert assistant. Read the note below and extract all actionable items. For each action, provide: 1) a short task title (5–8 words), 2) an optional due date in YYYY-MM-DD or ‘none’, 3) priority (low/medium/high), 4) tags (comma separated), and 5) one-sentence context/description. Return the result as a JSON array of objects with keys: title, due_date, priority, tags, description. Note: prefer due dates this week if clearly urgent; if not specified, use ‘none’. Note: do not include non-actionable ideas.”

Example

Note: “Call Sarah about the Q3 budget; prepare 3 slides; follow up on invoice #204; reschedule dentist.”

AI output (example):

• title: “Call Sarah about Q3 budget” — due_date: “2025-11-25” — priority: high — tags: finance,call — description: “Discuss Q3 budget adjustments and decisions.”
• title: “Prepare 3 Q3 slides” — due_date: “2025-11-27” — priority: medium — tags: slides,work — description: “Create three slides summarizing key budget points.”
• title: “Follow up invoice #204” — due_date: “none” — priority: medium — tags: finances — description: “Confirm payment status and next steps for invoice 204.”
• title: “Reschedule dentist” — due_date: “none” — priority: low — tags: personal — description: “Find a new appointment time in the next two weeks.”

Common mistakes & fixes

• Too many false tasks: tighten the prompt rules to ignore non-actionable notes.
• Wrong dates: have AI prefer “none” unless explicit, then let you set dates in Todoist/Notion.
• Formatting errors: validate AI JSON in your automation before creating tasks.

Quick action plan (next 30 minutes)

1. Pick one source (phone notes or Notion).
2. Set up a trigger in Zapier or Make for new notes.
3. Use the prompt above to extract tasks and map fields to Todoist/Notion.
4. Run 5 test notes and adjust priority/date rules.

Closing reminder: Start small, review AI results, and improve the prompt. Automate the routine; keep the decisions.

[aaron]

Hook: You want notes converted into actionable tasks in Todoist or Notion — fast, reliable, and measurable. Good focus.

The problem: Notes are messy, inconsistent, and sit in a backlog. That friction means ideas never become done.

Why it matters: Turning notes into tasks systematically increases execution. You’ll reduce missed deadlines, speed decisions, and prove time saved with simple KPIs.

My core approach (what I’ve learned): Don’t automate everything; automate the extraction and routing. Use AI to parse notes into structured task items, then push to Todoist or Notion via an automation tool (Zapier/Make/Shortcuts) or native integration.

Quick checklist — do / do not

• Do: Standardize a note format (title, context, action verb, due/horizon, priority).
• Do: Use AI to extract intent, not to decide priority automatically.
• Do not: Over-automate due dates without human review.
• Do not: Push every extracted line as a task — filter for “actionable” only.

Step-by-step (what you’ll need, how to do it, what to expect)

1. Gather tools: a notes app (Apple Notes/Obsidian), OpenAI/GPT access (or built-in AI), Todoist and/or Notion accounts, and Zapier/Make for automation.
2. Create a short note template: Title / Context / Action / Due (optional) / Tags. Use this consistently for new notes.
3. Build an AI extraction step: send the note text to GPT to return JSON with fields: title, task, due, project, priority, notes.
4. Map the JSON to Todoist fields (content, due date, project, labels) or Notion database properties and create the item via Zapier/Make.
5. Test with 10 real notes, review results, refine the prompt and mapping, then enable auto-run for new notes.

Copy-paste AI prompt (use with GPT/OpenAI):

“You are an assistant that converts raw meeting notes into a JSON list of actionable tasks. For each actionable item, return: title, task (one-sentence action starting with a verb), due (YYYY-MM-DD or null), project (short name), priority (low/medium/high), tags (comma-separated), and notes (context). Ignore non-actionable statements. Output only valid JSON.”

Worked example

Note: “Discuss Q3 budget with finance, decide on hiring by May 20, follow up on vendor quote.”

• Todoist task: “Discuss Q3 budget with finance” — due 2025-05-20 — project: Finance — priority: high
• Notion entry: Task row with Title, Due: 2025-05-20, Status: To Do, Tags: finance, hiring, vendor

Metrics to track

• Tasks created per week from notes.
• Task completion rate within due date.
• Average time from note creation to task creation.
• False-positive rate (non-actionable items created as tasks).

Common mistakes & fixes

• Too many tasks: add an AI filter that flags actionability (yes/no).
• Wrong dates: require human confirmation for auto-set due dates.
• Duplicates: check recent tasks in project before creating new ones.

1-week action plan

1. Day 1: Standardize note template and pick automation tool.
2. Day 2: Create AI prompt and test extraction on 10 notes.
3. Day 3: Map fields to Todoist/Notion in Zapier/Make; run dry tests.
4. Day 4: Review results, tweak prompt and mapping.
5. Day 5: Enable automation for selective notebook or tag.
6. Day 6: Measure KPIs (tasks/week, completion rate).
7. Day 7: Tweak rules (dates, priorities) and scale to more notes.

Your move.

[Jeff Bullas]

You’re asking the right question: the bottleneck isn’t taking notes—it’s turning them into action. Routing your notes straight into Todoist or Notion is a fast win that clears mental clutter and boosts follow-through.

Quick checklist: do / do not

• Do use a consistent task schema (task, owner, due date, priority, tags).
• Do ask AI to output in the exact format your tool expects (Todoist Quick Add lines or a Notion-ready table).
• Do convert relative dates to real dates (e.g., “next Friday” → 2025-02-14).
• Do keep each task short and action-focused (verb first).
• Don’t dump everything—filter for actions, not ideas or decisions.
• Don’t overstuff fields; if a detail isn’t in the note, leave it blank.
• Don’t rely on memory—always review the AI’s first pass before bulk-adding.

What you’ll need

• A note (meeting notes, voice transcript, brainstorm).
• Access to an AI chat tool.
• Todoist account or a Notion database for tasks (with properties like Title, Due date, Priority, Tags, Notes).

Fast path 1: Manual, 2-minute convert (copy/paste)

1. Copy your raw notes.
2. Paste into your AI with one of the prompts below.
3. Review the output and paste into Todoist or Notion.

Robust prompts you can copy-paste

• For Todoist Quick Add (makes one task per line you can paste individually into Quick Add):“From the notes below, extract actionable tasks only. Output one task per line formatted for Todoist Quick Add as:Task name p2 #Project @tag due YYYY-MM-DD HH:MMRules: Keep task names under 80 chars. Convert relative dates to real dates (YYYY-MM-DD, 24h). Only include fields present in the text (omit unknown project/tags/times). Default priority to p2 if not stated. Limit to 10 tasks. Output just the lines, no extra text.

  NOTES:
  [Paste your notes here]”

• For Notion database (CSV table):“Extract actionable tasks from the notes into a CSV with headers:Task,Due Date,Priority,Tags,NotesRules: Dates in YYYY-MM-DD. Priority as 1–4 (default 2 if unstated). Tags comma-separated. Notes max 120 chars. Only include true action items. Limit to 20 items. Output only the CSV.

  NOTES:
  [Paste your notes here]”

Fast path 2: Native tools inside each app

• Todoist
  • Use Quick Add with natural language: “Call sponsor Tuesday 14:00 p1 #Launch @calls”.
  • Insider tip: Ask AI to produce Quick Add–ready lines. Then paste each line into Quick Add for instant parsing (dates, priority, labels).
• Notion
  • Put your notes in a Notion page. Highlight the text and use Notion AI to extract “Action items.”
  • Turn the result into a simple table (Task, Due date, Priority, Tags, Notes) and move rows into your Tasks database.
  • Expectation: you’ll still eyeball dates and priorities once as quality control.

Automation path (no-code)

1. Pick a trigger (e.g., new Google Doc in a “To-Process” folder or an email you forward with subject “Notes → Tasks”).
2. Add an AI step to extract tasks to structured data (JSON or CSV) using the schema: title, due_date (YYYY-MM-DD), priority (1–4), tags, notes.
3. Create tasks via:
   • Todoist: Create Task action mapping title, due_date/time, priority, labels, description.
   • Notion: Create Database Item mapping Title, Due date, Priority, Tags, Notes.
4. Test with a small note, then turn it on.

Worked example

Raw notes:

• Website tweaks: update pricing page by next Friday. Ask Maria for new FAQ copy. Fix broken checkout error #1245. Reach out to sponsor re Q2 budget Tue 2pm. Post-launch review end of month.

AI output for Todoist Quick Add (paste each line into Quick Add):

• Update pricing page p1 #Website due 2025-02-14
• Ask Maria for new FAQ copy p2 #Website
• Fix checkout error #1245 p1 #Website
• Reach out to sponsor about Q2 budget p2 #Partnerships due 2025-02-11 14:00
• Plan post-launch review p2 #Website due 2025-02-28

AI output for Notion CSV (import into your tasks database or paste into a Notion table):

• Task,Due Date,Priority,Tags,Notes
• Update pricing page,2025-02-14,1,Website,Page layout and pricing tiers
• Ask Maria for new FAQ copy,,2,Website,Request draft and review
• Fix checkout error #1245,,1,Website,Bug triage and hotfix
• Reach out to sponsor about Q2 budget,2025-02-11,2,Partnerships,Confirm call at 14:00
• Plan post-launch review,2025-02-28,2,Website,Collect metrics

Common mistakes and quick fixes

• Vague tasks: “Pricing page” → Fix: “Update pricing page” (verb + object).
• Missing dates: AI skipped dates it couldn’t infer → Add one-line context to your notes: “Deadlines in GMT on business days.”
• Too many tasks: Cap to top 10; create a separate “Backlog” tag for the rest.
• Mismatched tags/projects: Keep a short, fixed list and include it in the prompt so AI maps correctly.

Insider trick: Train a micro-syntax in your notes so AI nails it every time. Example: start action lines with “- [ ]”, add dates in brackets, and priority as (p1–p4). E.g., “- [ ] Update pricing page [2025-02-14] (p1) #Website”. Your prompt can then say, “Only convert lines matching that pattern.” It reduces false positives and speeds review.

15-minute action plan

1. Decide your schema: Title, Due date, Priority (1–4), Tags, Notes.
2. Copy one of the prompts above into your AI tool.
3. Run it on a real note; review the output for 60 seconds.
4. Send to Todoist via Quick Add or paste/import into your Notion tasks database.
5. Optional: set up a simple automation with an AI extraction step for future notes.

What to expect

• First run: 5–10 minutes, with minor edits.
• After you standardize your schema and prompt: under 2 minutes per note.
• Quality improves fast as you keep prompts and tags consistent.

Starting simple beats waiting for perfect. Get one note flowing into tasks today; refine the prompt and fields next time.

[Becky Budgeter]

Nice focus — wanting your notes to become actionable tasks is exactly the right way to make AI useful. I’ll keep this simple and practical so you can try a workflow today, whether you pick Todoist or Notion.

What you’ll need

• Notes in any readable form (text, voice transcript, email, or a plain document).
• An AI tool that can parse text (built into many note apps or a web-based assistant).
• Either a direct integration (Todoist or Notion API, Zapier/Make) or the ability to paste/import CSV/markdown into your app.
• Basic field plan: task title, due date (optional), priority or tags, and a short description.

Step-by-step: how to do it

1. Gather: Put all notes you want turned into tasks into one place (one document or one captured note).
2. Ask the AI to extract action items: tell it to list short task titles plus an optional due date, priority, and 1-line context. Keep the request concise (e.g., ask for 3–6 tasks from meeting notes).
3. Review & edit: skim the AI’s output and fix any missing context or wrong dates — AI gets most but not all details right.
4. Map fields: format the output to match your app. For Todoist you’ll need title, due date, project/label. For Notion, format as rows or markdown that match the database properties (Name, Due, Status, Tags).
5. Send it over: use a direct integration (Zapier/Make/official API) for automation, or copy-paste/import CSV/markdown if you prefer manual control.
6. Check weekly: build a quick review habit to catch AI slips and reprioritize tasks.

What to expect

• AI speeds up extraction but won’t know context-specific priorities — expect to tweak a few tasks.
• Automations are great once set up, but start manual so you learn the right field mapping.
• For regular meetings, a lightweight template reduces editing time a lot.

Variants to try

• Quick capture: Short notes → 3 urgent tasks + 2 backlog items.
• Meeting digest: Action items with owner, due date, and 1-line context.
• Inbox cleanup: Scan long notes → label each item as Do/Triage/Archive.

Simple tip: start with one notebook and one project — once the flow works, expand. Do you want a step for setting up a specific integration to Todoist or Notion next?

[Author]

Posts