Barron & Folly
AI execution engine replacing fragmented vendor stacks with autonomous agent workflows.
// The System
Client requests enter through a unified console, are decomposed into discrete tasks by the planning layer, routed through an orchestration queue to specialized agent groups, and deployed through a gated pipeline. Every stage is observable, auditable, and reversible.
// Agent Architecture
Each agent group operates within a sandboxed execution context with enforced rate limits and policy boundaries. Agents carry org-specific memory and tool configurations.
↳ Lower-risk operations auto-execute. Higher-risk changes require client approval before promotion.
// What It Does
- ▶Autonomous task decomposition from natural language briefs
- ▶Parallel agent execution across frontend, content, data, and infra domains
- ▶Real-time progress streaming with human-in-the-loop checkpoints
- ▶Persistent per-organization memory for progressive system improvement
- ▶Gated deployment pipeline with automated rollback on failure
// Key Decisions
Multi-Agent Routing
Tasks are decomposed and routed to specialized agent groups rather than handled by a single general-purpose agent. Each group carries domain-specific context, tooling, and validation rules.
↳ Tradeoff: Orchestration complexity for domain-specific quality.
Tiered Autonomy
Risk-based execution model. Lower-risk operations (formatting, linting, asset optimization) auto-execute. Higher-risk changes (schema migrations, API modifications, deployment) require explicit client approval.
↳ Tradeoff: Slower high-risk operations, significantly safer output.
Per-Org Memory
Each organization accumulates a persistent context store. The system learns brand voice, technical preferences, infrastructure patterns, and approval tendencies over time.
↳ Tradeoff: Storage and retrieval cost vs. progressive improvement.
Preview → Staging → Production
Three-stage deploy gates with automated checks at each boundary. Every change is verified in preview, validated in staging, and promoted to production with full rollback capability.
↳ Tradeoff: Slower delivery cadence, far fewer production incidents.