The challenge
Most teams bolt AI tools onto legacy processes and see little. The goal was to redesign the software development lifecycle around AI agents themselves — with quality, cost and evaluation under control.
The approach
- Standardised multi-model, multi-vendor agentic coding (Claude / Claude Code, Cursor, Windsurf, Copilot, GPT / Gemini / open models)
- Built RAG and agent-memory systems to ground agents in client context
- Stood up evaluation frameworks, cost controls and MCP-based tooling
The outcome
- Made AI-native, agentic delivery the exclusive model across the firm
- Kept quality and margins healthy while moving faster
- Built first-hand, hands-on mastery of how AI-built software really behaves