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AI Overview

Thread uses OpenAI’s GPT models to generate personalized content for emails, handoff Q&A, forms, and more. AI drafts save CSMs hours while maintaining quality and personalization. [SCREENSHOT: AI-generated email draft in review interface] Caption: AI generates drafts based on customer context and template guidance

What AI Generates

Action Drafts

Email Content

Subject lines and email bodies with customer-specific details

Form Intro Text

Instructions and context for form collection

Slack Messages

Channel updates and notifications

Handoff Q&A

Answers to handoff questions from CRM data

What AI Doesn’t Generate

Form Fields

Pre-configured in templates by admins

Document Types

Pre-defined in action configuration

Meeting Agendas

Template-based, not AI-generated (yet)

Portal UI

Configured through Thread’s interfaces

How AI Generation Works

The AI Pipeline

1

Trigger Fires

Action trigger evaluates true (milestone starts + delay passes)
2

Context Gathering

Thread collects all relevant context:
  • Account data (company, contacts, ARR, close date)
  • Handoff Q&A
  • Template configuration
  • Previous actions and responses
  • Milestone information
3

Prompt Construction

Thread builds a structured prompt with:
  • System instructions (tone, format, constraints)
  • Customer context
  • Action purpose and template
  • Variable placeholders
  • Output format requirements
4

OpenAI API Call

Thread sends prompt to OpenAI GPT-4
  • Uses structured output mode
  • Enforces JSON schema
  • Includes retry logic for failures
5

Response Processing

Thread processes AI response:
  • Validates format
  • Interpolates variables
  • Applies final formatting
  • Stores as draft
6

Ready for Review

Action moves to “ready” status in CSM Implementation Tab
[SCREENSHOT: AI generation flow diagram] Caption: From trigger to ready draft in seconds

AI Context Sources

Account Data

{
  company_name: "Acme Corporation",
  arr: 50000,
  close_date: "2024-03-15",
  primary_contact_name: "Jane Smith",
  primary_contact_email: "jane@acme.com",
  primary_contact_role: "IT Director",
  industry: "Healthcare",
  company_size: "51-500",
  notes: "Excited about API integrations..."
}
What AI learns:
  • Company name for personalization
  • Industry for relevant examples
  • Contact name and role for appropriate tone
  • ARR for understanding customer tier
  • Notes for specific context

Handoff Intelligence

{
  primary_use_case: "Sales outreach automation",
  top_goals: [
    "Reduce manual email work",
    "Improve response rates",
    "Scale team efficiency"
  ],
  risks: "Tight Q3 deadline, small IT team",
  stakeholders: "Jane (IT Director), Bob (Sales VP)",
  technical_environment: "Salesforce CRM, AWS infrastructure"
}
What AI learns:
  • Why customer bought (use case)
  • What success looks like (goals)
  • Potential challenges (risks)
  • Who’s involved (stakeholders)
  • Technical context (environment)

Template Configuration

{
  action_type: "SEND_EMAIL",
  action_label: "Welcome Email",
  action_description: "Initial welcome and onboarding kickoff",
  milestone_name: "Kickoff",
  milestone_description: "Getting started with implementation",
  content_template: {
    subject: "Welcome to {{company_name}}'s onboarding!",
    body: "...template structure..."
  }
}
What AI learns:
  • Purpose of this action
  • Stage in customer journey
  • Expected tone and format
  • Required elements to include

Previous Actions

{
  previous_emails: [
    {
      subject: "Welcome!",
      sent_at: "2024-03-15",
      customer_responded: true
    }
  ],
  customer_engagement: {
    portal_visits: 3,
    forms_completed: 1,
    documents_uploaded: 0
  }
}
What AI learns:
  • Established relationship context
  • What’s been discussed already
  • Customer engagement level
  • Appropriate follow-up tone

Prompt Engineering

System Prompt

Thread uses a carefully crafted system prompt:
You are a Customer Success Manager writing to a new customer.

TONE:
- Professional yet friendly
- Enthusiastic but not overeager
- Helpful and supportive
- Clear and concise

REQUIREMENTS:
- Use customer's name and company name
- Reference specific details from their use case
- Include clear call-to-action
- Keep under 250 words
- Use bullet points for multiple items
- End with CSM signature

AVOID:
- Generic greetings ("Dear customer")
- Overly formal language
- Sales-y language
- Excessive exclamation marks
- Walls of text

User Prompt (Context)

Then adds customer-specific context:
CUSTOMER: Acme Corporation
CONTACT: Jane Smith, IT Director
ARR: $50,000
INDUSTRY: Healthcare
USE CASE: Sales outreach automation
GOALS: Reduce manual work, improve response rates, scale efficiency
RISKS: Tight Q3 deadline, small IT team (3 people)

ACTION: Welcome Email - Initial kickoff
MILESTONE: Kickoff (Week 1)
PREVIOUS: None (first touchpoint)

Generate a welcome email that:
1. Welcomes Jane to the onboarding journey
2. References their sales automation use case
3. Sets expectations for timeline (mindful of Q3 deadline)
4. Offers support given their small team
5. Includes link to customer portal
6. Provides CSM contact info and calendar link

Output Format

AI responds with structured JSON:
{
  "subject": "Welcome to Acme's Implementation, Jane!",
  "body": "Hi Jane,\n\nI'm excited to partner with Acme Corporation on your sales outreach automation journey!\n\n**What's Next:**\n- Review your portal timeline\n- Complete pre-kickoff questionnaire\n- Schedule our kickoff call\n\nGiven your Q3 deadline, we'll move efficiently while ensuring quality. I know your IT team is small, so I'll provide extra documentation and support.\n\n**Your Portal:** [link]\n**My Calendar:** [link]\n\nQuestions? I'm here to help.\n\nBest,\n{{csm_name}}"
}

Regeneration

When to Regenerate

AI generated something generic or off-topicSolution: Regenerate with specific instructions
Too formal, too casual, or inconsistent with brandSolution: Regenerate with tone guidance
Didn’t mention important contextSolution: Regenerate with “Include [specific detail]”
Doesn’t match desired lengthSolution: Regenerate with length constraint

How to Regenerate

  1. Click “Regenerate” in action review
  2. Add instructions in text field:
    • “Make it more casual”
    • “Add urgency about Q3 deadline”
    • “Focus on technical integration aspects”
    • “Keep under 150 words”
    • “Reference their Salesforce CRM specifically”
  3. Click “Regenerate”
  4. AI generates new draft with your guidance
  5. Review new version
[SCREENSHOT: Regenerate modal with instruction field] Caption: Guide AI to improve drafts with specific instructions
Each regeneration is independent—AI doesn’t remember previous attempts. Be specific about what you want changed!

AI Quality Factors

High-Quality Drafts

When you get great drafts:
  • ✅ Rich customer data in account
  • ✅ Detailed handoff Q&A completed
  • ✅ Clear action purpose in template
  • ✅ Good content template with examples
  • ✅ Relevant previous action context
  • ✅ Specific, not generic account notes
Example high-quality input:
Company: Acme Corp
Contact: Jane Smith, IT Director
Use Case: Automating outbound sales emails for 50-person sales team
Goals: Reduce 10 hours/week of manual work, improve response rates from 15% to 25%
Risks: Tight Q3 deadline (July 1), small IT team may need extra support
Technical: Using Salesforce CRM, need API integration
Previous: Just signed contract, eager to get started
Result: Personalized, relevant, actionable email draft

Lower-Quality Drafts

When drafts are generic:
  • ❌ Minimal account data
  • ❌ Skipped or sparse handoff
  • ❌ Vague action descriptions
  • ❌ Generic content templates
  • ❌ No previous context
  • ❌ Empty account notes
Example low-quality input:
Company: Acme Corp
Contact: Jane Smith
Use Case: [empty]
Goals: [empty]
Risks: [empty]
Technical: [empty]
Previous: [none]
Result: Generic “Dear Customer” email that needs heavy editing
AI quality is directly proportional to input quality. Garbage in, garbage out!

Improving AI Performance

1. Enrich Account Data

Before AI generates drafts:
  • Complete all optional fields
  • Add detailed notes
  • Include CRM data in raw payload
  • Paste relevant conversations

2. Optimize Templates

Action descriptions:
  • ❌ “Send email”
  • ✅ “Welcome email introducing CSM, setting expectations, and providing portal access”
Content templates:
  • ❌ “Email customer about status”
  • ✅ Structured template with sections, examples, and variables
Context hints:
  • Add notes in template: “This email should reference the customer’s use case and address any risks mentioned in handoff”

3. Provide Feedback

Help improve AI over time:
  1. Note patterns in edits (always adding industry examples?)
  2. Track which prompts work well
  3. Share feedback with team
  4. Request template improvements from admins

AI Limitations

What AI Can’t Do

Read Your Mind

AI doesn’t know unstated customer preferences or internal politics

Remember Calls

AI doesn’t have access to verbal conversations unless you document them

Predict Future

AI can’t anticipate customer reactions or upcoming issues

Replace Human Touch

AI drafts need your personalization and relationship context

When to Override AI

Always edit or rewrite when:
  • Customer has unique situation not captured in data
  • Sensitive topic requiring human nuance
  • Relationship dynamic AI doesn’t understand
  • Brand voice needs adjustment
  • Humor or empathy required
  • Complex negotiation or escalation
Think of AI as your first draft writer, not your final copy editor. You’re the expert—AI just saves you time on the initial structure.

Best Practices

Always Review

Never execute AI drafts without reading them

Add Personal Touch

Include customer-specific details only you know

Use Regeneration

Don’t settle for mediocre—guide AI to better output

Enrich Context

Better input data = better AI output

Track Patterns

Note what works and share with team

Provide Feedback

Help improve prompts and templates over time

Next Steps