Retrieval-augmented Q&A
Indexed more than 200 platform documents and used intent parsing, entity extraction, and targeted retrieval to produce grounded answers across multi-turn conversations.
AI & Developer Experience / 2025 — Present
AI Agent for a Dynamic UI Platform.
A retrieval-augmented agent that answers platform questions, turns design structures into reusable DSL, and packages expert workflows as discoverable skills.
KNOWLEDGE → INTELLIGENCE → CREATION80%fewer support requests
200+technical documents indexed
Hours → Minutescomponent integration time
01 / THE CHALLENGE
Platform knowledge was powerful, but difficult to access.
The dynamic UI platform served more than 100 business teams. Its capabilities were distributed across component APIs, bridge specifications, framework documentation, and team knowledge. Developers needed expert support to find the right APIs and write valid DSL, creating repeated support work and slow integration cycles.
02 / THE SYSTEM
One agent, two specialized workflows.
Design-to-DSL generation
Converted parsed design structures into platform component trees, mapped them to DSL conventions, and added syntax checks for events, parameters, and tag closure.
Reusable agent skills
Packaged platform onboarding, component guidance, troubleshooting, and unit conversion as standard skills available through the company AI assistant.
Shared core, distinct outputs
Reused intent and knowledge retrieval infrastructure while keeping natural language support and structured code generation as separate, optimized paths.
03 / System map
- InputsQuestions · Designs · Context
- Shared intelligenceIntent · Retrieval · Knowledge
- Specialized outputsAnswers · DSL · Skills
04 / THE OUTCOME
Expert knowledge became a scalable product capability.
The agent reduced support volume by 80% and shortened component integration from hours to minutes. It transformed platform expertise from a person-dependent service into a reusable capability that teams could access directly in their normal workflow.