From spec to production: a three-week drug discovery agent using Kiro

This article demonstrates how AWS built a production-ready drug discovery target identification agent in three weeks using spec-driven development with Kiro and AWS services.

• Spec-driven development separates planning from execution with requirements.md, design.md, and tasks.md documents
• Three solution architects built a unified agent integrating 30+ APIs including PubMed, UniProt, and ClinicalTrials.gov
• Kiro generated 95% of business logic code, saving over 80 hours of development time
• Agent synthesizes fragmented biomedical data to identify therapeutic targets with cited evidence
• Architecture uses Amazon Bedrock AgentCore, Lambda, S3, and CloudWatch for serverless scalability
• Steering documents maintained consistent coding standards and patterns across the team automatically
• Agent Hooks automated documentation updates whenever code changed
• Production security implemented with Cognito, IAM roles, and OAuth 2.0 JWT tokens
• Key success factors: upfront specifications, comprehensive steering docs, MCP knowledge sources, real data only, observability from day one

This case study shows rapid agentic AI development is practical for complex domains when combining spec-driven methodology, AI-assisted coding, and AWS services.