Agent architecture
Designing agentic systems that hold up outside a demo: tool boundaries, context strategy, failure modes, and the evaluation loop that tells you when a change made things worse.
- Agentic AI
- MCP
- Evaluation
AI Architecture & Workflow
KB Development designs AI-native systems and the developer workflows that build them — from the agent architecture down to the tooling a team uses every day.
Designing agentic systems that hold up outside a demo: tool boundaries, context strategy, failure modes, and the evaluation loop that tells you when a change made things worse.
The workflow is the product's second architecture. Spec-driven development, skills and plugins, and the repo conventions that let a team move quickly without relitigating the same decisions.
Token systems with the accessibility maths done and written down, so contrast and colour roles survive contact with a real product rather than living in a slide.
Production React and TypeScript — the layer where architecture either becomes something people can use, or doesn't.
Spec-driven development tooling: turn an intent into a reviewable specification before any code is written.
Skills, plugins, and MCP servers that make agent workflows repeatable — packaged so a team gets the same behaviour every time.
Describe the problem you're working on. Replies come from a person, not a form.