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Customer Success Story

From 80% AI Code Rejection to Prompt-First Development​

How a growing tech company transformed their AI development workflow

The Challenge​

A fast-growing technology company had established a solid product development process with Confluence for PRDs, senior engineers creating technical designs, and Jira for project management. However, when they adopted AI tools (Microsoft Copilot, GitHub Copilot, Claude Code), they hit a major roadblock: 80% of AI-generated code required significant rework.

The Core Problem​

Despite having good planning processes and powerful AI tools, there was no way to connect them. AI tools lacked understanding of:

  • Company-specific workflows and patterns
  • Existing architecture and technical decisions
  • Business requirements and context
  • Code conventions and standards

Failed Attempts​

The team tried manual solutions:

  • Using ChatGPT to synthesize requirements and tickets
  • Manually creating AI prompts for development work
  • Attempting to bridge planning and implementation gaps

Result: These approaches were extremely tedious and time-intensive. Nobody wanted to use them due to the overhead involved, and developers were essentially starting from scratch every time they used AI assistance.

The Solution: Devplan Implementation​

The company discovered Devplan and immediately recognized its potential to bridge the gap between their planning processes and AI development tools.

Key Benefits Identified​

  • Context Preservation: Maintain project context from planning through implementation
  • Intelligent Prompt Generation: Automatic creation of rich, context-aware prompts for AI tools
  • Workflow Integration: Seamless connection between existing Confluence/Jira workflow and AI development

Implementation Approach​

Rather than replacing their existing tools, Devplan enhanced their current workflow:

  • Phase 1: Connected GitHub repositories for codebase analysis and integrated with Jira
  • Phase 2: Introduced "prompt-first thinking" and trained teams on context-driven development

The Transformation​

After implementing Devplan, the company shifted to prompt-first development with dramatic improvements:

Before vs. After Comparison​

StepOld WayNew Way (Devplan)Impact
PRD WritingManual creation in Confluence, multiple PM-engineering iterations to clarify requirementsAI-assisted discovery sessions in Devplan capture requirements upfront with context from existing codebase60% reduction in planning cycle time
Tech DesignSenior engineers brainstorm separately, designs disconnected from requirementsTechnical designs created within Devplan, automatically connected to business requirements and preserved for implementationSeamless integration between product and technical decisions
User Stories & TicketsManual breakdown of PRDs into Jira tickets, often missing context and implementation detailsAutomated breakdown into context-rich user stories with technical guidance and agentic scoresComplete context preservation, implementation-ready tickets
Prompt Generation30-45 minutes per feature to manually create useful AI prompts, often generic and missing project context<2 minutes automated generation with full codebase context, patterns, and architectural decisions90%+ reduction in prompt preparation time
Self DocumentationNo systematic way to preserve context, decisions lost between planning and implementationStored prompts preserve intent behind each change, creating institutional knowledgeComplete traceability from idea to implementation
AI CodingGeneric AI suggestions requiring 80% rework, developers working without project contextContext-rich prompts enable autonomous AI coding that follows project patterns and conventions25% improvement in AI code quality and acceptance rate

Results​

The Main Win: Dramatically Faster Idea-to-Prompt Pipeline​

Before Devplan:

  • 2-3 days from idea to having usable development prompts
  • Manual PRD creation, separate tech design, manual ticket breakdown, and 30-45 minutes per prompt

After Devplan:

  • 2-3 hours from idea to context-rich prompts ready for AI coding
  • AI-assisted discovery, automated breakdown, and <2 minutes per prompt generation

Impact: This 10x acceleration in the idea-to-prompt pipeline dramatically increased project throughput, allowing the team to tackle significantly more features and respond faster to market needs.

Additional Benefits​

  • Universal adoption of prompt-first thinking across the organization
  • Developers now actively seek out Devplan-generated prompts instead of avoiding AI tools
  • AI-generated code follows company patterns and integrates seamlessly with existing architecture

Key Success Factors​

1. Prompt-First Mindset: Successfully shifted from "AI as an afterthought" to "AI-native development thinking"

2. Workflow Integration: Enhanced existing Confluence/Jira workflow rather than replacing it

3. Gradual Adoption: Started with pilot projects and expanded as benefits became clear

Ready to transform your AI development workflow? Get started with Devplan to see how context-driven development can improve your team's productivity and code quality.