JTBD Interview Agent

An AI-powered interview agent that conducts Jobs to Be Done (JTBD) interviews following Bob Moesta's methodology. Built with the Claude Agent SDK and React, featuring Skills integration for Bob Moesta's interview techniques.

Features

Bob Moesta Interview Style: Uses the five core techniques (Context, Contrast, Unpacking, Energy, Analogies)
Timeline Building: Automatically tracks the decision journey from first thought to first use
Forces of Progress: Maps push, pull, anxiety, and habit forces that drive decisions
Diet/Lifestyle Inquiry: Captures media consumption, professional networks, and physical touchpoints
Real-time Visualization: See timeline, forces diagram, and insights as they're captured
Model Selection: Choose between Claude Sonnet, Opus, or Haiku for interviews
Admin Panel: View, search, and manage past interviews
Interview Reports: Generate formatted reports with job statements and key insights
Export to JSON/Markdown: Save complete interview data for analysis

Project Structure

jtbd-interview-agent/
├── .claude/
│   └── skills/
│       └── bob-moesta-advisor/   # Bob Moesta JTBD interview skill
│           ├── SKILL.md          # Skill definition and methodology
│           ├── assets/           # Skill assets
│           └── references/       # Framework references
│
├── packages/
│   ├── agent/         # TypeScript agent using Claude Agent SDK
│   │   ├── src/
│   │   │   ├── interviewer.ts    # Main interview agent class
│   │   │   ├── prompts/          # System prompts & interview scripts
│   │   │   ├── tools/            # Custom interview tools
│   │   │   ├── types/            # TypeScript type definitions
│   │   │   ├── server.ts         # HTTP API server
│   │   │   ├── storage.ts        # Interview persistence
│   │   │   └── cli.ts            # Command-line interface
│   │   └── package.json
│   │
│   └── web/           # React frontend
│       ├── src/
│       │   ├── components/       # UI components
│       │   │   └── admin/        # Admin panel components
│       │   ├── pages/            # Page components
│       │   ├── hooks/            # React hooks
│       │   └── types/            # Frontend types
│       └── package.json
│
├── data/              # Interview storage
│   └── interviews/    # Saved interview JSON files
│
├── package.json       # Monorepo root
└── README.md

Skills Integration

This project uses the Claude Agent SDK (@anthropic-ai/claude-agent-sdk) with Skills support for Bob Moesta's JTBD interview methodology.

How It Works

The agent uses the SDK's query() function with Skills configuration:

import { query } from '@anthropic-ai/claude-agent-sdk';

for await (const message of query({
  prompt,
  options: {
    model: 'claude-sonnet-4-20250514',
    cwd: PROJECT_ROOT,
    settingSources: ['user', 'project'],  // Load Skills
    allowedTools: ['Skill', 'Read'],
    permissionMode: 'bypassPermissions'
  }
}))

Configuration Options

| Option | Description | |--------|-------------| | settingSources | Where to load Skills from: user (~/.claude/skills/), project (.claude/skills/) | | allowedTools | Tools the agent can use. Include Skill to enable Skills | | permissionMode | Set to bypassPermissions for server/non-interactive use | | cwd | Working directory for project Skills discovery |

The bob-moesta-advisor Skill

Located in .claude/skills/bob-moesta-advisor/, this skill provides:

SKILL.md - Core skill definition with Bob Moesta's methodology
references/frameworks.md - JTBD theory, Forces of Progress, Five Skills of Innovators
references/interview-method.md - Interview techniques and timeline building
references/mattress-interview.md - Example interview transcript

The skill teaches the agent to:

Use the "empty vessel" interview approach
Apply the five techniques: Context, Contrast, Unpacking, Energy, Analogies
Build decision timelines backward from purchase
Map Forces of Progress (push, pull, anxiety, habit)
Capture the Information Diet for customer discovery

Getting Started

Prerequisites

Node.js v18+ (Download)
npm (included with Node.js)
Anthropic API key (Get one here)

Installation

Clone the repository

git clone <repo-url>
cd jtbd-interview-agent

Install dependencies
```
npm install
```
Set up environment

Create a .env file in the project root:
```
echo "ANTHROPIC_API_KEY=your-api-key-here" > .env
```
Or export directly (for current session only):
```
export ANTHROPIC_API_KEY=your-api-key-here
```
Build the packages
```
npm run build
```

Verify installation

# Check the build succeeded
ls packages/agent/dist/
# Should see: cli.js, server.js, interviewer.js, etc.

Running the CLI

# Build the agent (if not already built)
npm run build:agent

# Run CLI interview
node packages/agent/dist/cli.js

Running the Web Interface

Terminal 1: Start the API server

cd packages/agent
npm run start
# Server runs at http://localhost:3001

Terminal 2: Start the web frontend

cd packages/web
npm run dev
# Frontend runs at http://localhost:3000

Open http://localhost:3000 in your browser.

Troubleshooting

| Issue | Solution | |-------|----------| | ANTHROPIC_API_KEY not found | Ensure the API key is exported or in .env file | | Skills not loading | Verify .claude/skills/ directory exists in project root | | Port 3001 in use | Change port: PORT=3002 npm run start | | TypeScript errors | Run npm run typecheck to see detailed errors | | Module not found | Run npm install then npm run build |

Model Selection

Choose the Claude model that best fits your needs:

| Model | Model ID | Best For | |-------|----------|----------| | Claude Sonnet 4 | claude-sonnet-4-20250514 | Most interviews (Recommended) | | Claude Opus 4 | claude-opus-4-20250514 | Complex or sensitive interviews | | Claude Haiku 3.5 | claude-3-5-haiku-20241022 | Quick interviews, testing |

Interview Flow

Phase 1: Warm-up

Build rapport and explain the interview purpose.

Phase 2: Decision Deep-Dive

Explore a recent purchase/decision with timeline questions:

When did you first think about this?
What triggered your search?
How did you research options?
What made you decide?

Phase 3: Forces Mapping

Identify the four forces of progress:

Push: What wasn't working?
Pull: What attracted you?
Anxiety: What almost stopped you?
Habit: What kept you comfortable?

Phase 4: Diet Inquiry

Capture information about how to reach similar customers:

Media consumption (podcasts, newsletters, social)
Professional networks (Slack, conferences, associations)
Physical touchpoints (coffee shops, gyms, commute)
Trusted sources and discovery channels

Phase 5: Synthesis

Generate job statement and validate understanding.

API Endpoints

Interview Endpoints

| Endpoint | Method | Description | |----------|--------|-------------| | /api/interview/start | POST | Start a new interview | | /api/interview/message | POST | Send a message in an interview | | /api/interview/end | POST | End and save interview | | /api/interview/data/:sessionId | GET | Get interview data | | /api/interview/export/:sessionId | GET | Export as JSON | | /api/models | GET | Get available Claude models | | /api/health | GET | Health check |

Admin Endpoints

| Endpoint | Method | Description | |----------|--------|-------------| | /api/admin/interviews | GET | List all saved interviews | | /api/admin/interviews/:id | GET | Get interview details | | /api/admin/interviews/:id | DELETE | Delete an interview | | /api/admin/interviews/:id/report | GET | Generate interview report |

Output Format

The interview generates structured data:

{
  "interviewee": { "name": "", "context": "" },
  "timeline": [
    { "phase": "first_thought", "date": "", "details": "" },
    { "phase": "trigger", "trigger": "", "details": "" }
  ],
  "forces": {
    "push": [{ "description": "", "intensity": 8 }],
    "pull": [{ "description": "", "intensity": 7 }],
    "anxiety": [{ "description": "", "intensity": 5 }],
    "habit": [{ "description": "", "intensity": 4 }]
  },
  "dietProfile": {
    "mediaConsumption": { "podcasts": [], "newsletters": [] },
    "professionalNetworks": [],
    "physicalTouchpoints": [],
    "trustedSources": []
  },
  "jobStatement": "When I [situation], I want [motivation], so I can [outcome]",
  "insights": [],
  "verbatimQuotes": []
}

Report Format

Generated reports include:

Interview metadata (date, interviewee, model used)
Job statement
Struggling moment
Decision timeline with context
Forces of progress analysis
Information diet summary
Key quotes and insights
Conversation summary

Key Interview Questions

Struggling Moment

"What wasn't working?"
"What were you putting up with?"
"What finally pushed you over the edge?"

jtbd-interview-agent

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