What it does
Monitors emails and call notes for commitments made to clients (“I’ll send that by Friday”, “We can include that”), creates tasks with deadlines, and reminds you before promises are broken.
Why I recommend it
Broken promises destroy trust, but most break not from bad intent but from forgotten commitments scattered across conversations.
Expected benefits
- Stronger client trust from kept promises
- Fewer embarrassing “I forgot” moments
- Better reputation and referrals
- Less stress from tracking mental commitments
How it works
Email or call note captured → AI scans for promise language (“I will”, “We’ll”, “By [date]”) → extracts commitment and due date → creates task → sends reminder before deadline → marks complete when fulfilled.
Quick start
After client calls, manually jot down promises made and create tasks. Once you see the value, add AI extraction from notes and emails.
Level-up version
Track promise kept/broken rate. Alert if approaching capacity. Suggest underpromising when workload is high. Categorise promises by type to identify patterns.
Tools you can use
Email: Gmail, Outlook
AI: ChatGPT, Claude
PM tools: ClickUp, Asana, Todoist
CRM: GoHighLevel, HubSpot
Automation: Zapier, Make, n8n
Technical implementation solution
- No-code: After calls, paste notes into form → AI extracts promises → manually create tasks.
- API-based: Email or call notes webhook → AI API detects commitment language → extract promise and date → PM API creates task with deadline → reminder workflow triggers → track completion.
Where it gets tricky
- Distinguishing firm commitments from casual mentions
- Extracting accurate due dates from vague timeframes
- Handling promises that require delegation
Chapter 6 – Support, Retention, and Growth Systems
