AI-Native Team Workspace (Meta-Repo Architecture)
Gives AI coding agents the whole multi-repository system in one tree without a monorepo migration, and layers on top of it what an agent needs to work there — curated retrieval over the team's documentation, rules and skills written once and generated per agent, tools over MCP, and hooks that block what is expensive to undo.
Appropriate Caching in a Multi-Service Estate (Balancing Efficiency and Simplicity Across a Shared Store)
Eliminates cross-service HTTP hops by letting consumers read owner-managed keys directly from a single shared cache, using server-enforced ACLs, operation-specific failure policies, and a disciplined caching ladder that selects the simplest honest invalidation strategy for each access pattern.
Lightweight Spec-Driven Development (Core Principles Shaped to an AI-Native Meta-Repo)
Keeps the ideas spec-driven development rests on — intent agreed before code, requirements, design and tasks as separate artefacts, small traceable tasks, specs versioned beside the code — without adopting an SDD framework, and derives the rest of the process from the team's own constraints.
Log-Based Distributed Tracing (Trace-Id Propagation Through Shared Libraries)
Correlates a request across every microservice it touches with one HTTP header, one field in the structured log line, and the log pipeline the platform already runs — no tracing backend, no sampling, no process besides the application.
Logical Database-per-Service (Shared Cluster)
A pragmatic implementation of the "Database per Service" microservices pattern.