No product manager writing PRD, no frontend/backend division—the true story of how the Qoder team "hacked" a product with AI.
Introduction: No product manager writing PRD, no frontend/backend division—5 people completed in 7 days what traditionally takes 15-20 people several weeks. This isn't science fiction; this is the true experience of the Qoder team developing QoderWork with Quest.
The Qoder team is a pioneer in the AI programming tools space, with multi-platform products including Qoder IDE, Qoder for VS Code, and Qoder CLI. In early 2026, the team decided to develop a desktop AI assistant for all users—QoderWork—to democratize Coding Agent capabilities for everyone.
Challenges:
The team gathered everyone in the project room and used whiteboard co-creation to determine:
The team adopted Qoder Quest's Spec-driven development model:
Human-AI Co-created Specs:
Early Phase (Shared Code): One person per Quest, rapid iteration, frequent commits to resolve conflicts
Late Phase (Vertical Modules): One person with multiple Quests in parallel, isolating tasks through Git Worktree to significantly boost individual output
Launch Results:
Key Transformations:
QoderWork is a desktop AI assistant launched by the Qoder team, based on Qoder CLI's Coding Agent capabilities, enabling non-programmer users to enjoy the convenience brought by AI.
Core Capabilities:
Customer Background
The Qoder team is a pioneer in the AI programming tools space, with multi-platform products including Qoder IDE, Qoder for VS Code, and Qoder CLI. In early 2026, the team decided to develop a desktop AI assistant for all users—QoderWork—to democratize Coding Agent capabilities for everyone.
The Impossible Mission
Challenges:
- Traditional software development cycles are long, typically taking months from requirements to launch
- Complex role divisions (product manager, frontend, backend, testing, UED) result in high communication costs
- Need to rapidly validate a new software R&D paradigm for the AI era
- 5-person team to complete QoderWork development and launch from 0 to 1 in 7 days
- Explore a "role-less division" collaboration model
- Validate the new paradigm of "Spec-driven development"
Solution: Not Writing a Single Line of Code, "Hacking" the Entire Product
Day 1: Co-creation Defining Boundaries, Not a Single Line of Code Written
- MVP product boundaries: what to include and what not to include in the first version
- Module breakdown: functional descriptions, technical conventions, interface definitions, acceptance criteria
- Establishing technical architecture based on existing code assets
From Day 2: Entering "Hack Code" Mode
The team adopted Qoder Quest's Spec-driven development model:
Human-AI Co-created Specs:
- Technical personnel describe requirements and intent
- Quest AI understands and asks clarifying questions (e.g., "Local or cloud database?" "Expected TPS?")
- After several rounds of interaction, human and AI jointly produce detailed Spec documents
- Hand Specs to Quest; AI generates functional modules end-to-end
- Frontend architects build the skeleton; all engineers vertically own modules end-to-end
- UED directly produces frontend component code that meets engineering standards
Parallel Development: One Person Directing Multiple AI Colleagues
Early Phase (Shared Code): One person per Quest, rapid iteration, frequent commits to resolve conflicts
Late Phase (Vertical Modules): One person with multiple Quests in parallel, isolating tasks through Git Worktree to significantly boost individual output
AI Code Review: 7×24 Quality Gatekeeper
- All PRs automatically trigger Qoder CLI's AI Code Review
- AI understands existing codebase logic and proposes rigorous review comments
- Unresolved Review issues block code merge
Results: We Did It
| Metric | Traditional Model | Qoder Quest Model |
|---|---|---|
| Team Size | 15-20 people | 5 people |
| Development Cycle | 4-8 weeks | 7 days |
| Role Division | Clear frontend/backend/testing/UED | No role division; all Spec engineers |
| Communication Cost | Multiple rounds of document review | Sit together, align once |
| Efficiency Gain | Baseline | 60-70% end-to-end efficiency improvement |
- January 30, 2026: QoderWork officially launched
- Supports both macOS and Windows platforms
- Core capabilities: autonomous task planning, local file operations, Skill system, privacy and security
Core Discovery: Spec Is Your Productivity
"In the future, writing code will increasingly be done by AI; humans clarify requirements and intent with AI through Specs."
Not just AI-assisted coding, but AI driving the complete R&D process
— QoderWork Project LeadTraditional R&D Process vs Spec-Driven Development:
- From "Software Engineering" to "Software Intentioning" (intent engineering)
- Human role upgrades from "writing code" to "system architecture design + requirements definition + quality review"
- AI becomes a tireless 7×24 "invisible team member"
Customer Testimonials
Project Lead Evaluation
"We completed with 5 people in 7 days what traditionally takes 15-20 people several weeks. This is not just an efficiency improvement, but a revolution in the software R&D paradigm. Quest is not a simple code generation tool, but an AI colleague that can understand intent, ask clarifying questions, and deliver end-to-end."
Team Practice Insights
- Spec is the lifeline of quality — Carefully reviewing Specs early to ensure AI understands correctly costs much less than rework later
- Task granularity — One Quest corresponds to one testable functional unit for easy acceptance
- Don't skimp on Review — Humans focus on architecture and logic; AI focuses on details
- Think AI first — When encountering any problem, first consider if AI can solve it; cultivate an AI-first mindset
About QoderWork
QoderWork is a desktop AI assistant launched by the Qoder team, based on Qoder CLI's Coding Agent capabilities, enabling non-programmer users to enjoy the convenience brought by AI.
Core Capabilities:
- 🎯 Autonomous Task Planning: Understand intent, break down steps, execute automatically
- 📁 Local File Operations: Process office documents like PDF, PPT, Word, Excel
- 🧩 Skill System: Extend professional domain capabilities (e.g., PPT generation, Deep Research)
- 🔒 Privacy & Security: Local execution, VM isolation, high-risk command interception