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OLabs Team

How We Deliver Software Faster With an Agent Team

A technical operational manual for the 70/30 AI/human software engineering model. Details the 14-agent organizational hierarchy, Ralph Loop orchestration daemon, the Nuxt 4 + Hono + Drizzle stack, and verified Sprint 0 failure mode mitigations.

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Executive Summary

OLabs delivers production software systems using an engineered multi-agent swarm structured around conventional Scrum disciplines. The operational workload allocation is strictly divided: 70% automated execution by artificial intelligence agents, and 30% verification and governance by human senior engineers.

This operational model accelerates feature delivery while preserving regulatory compliance, auditability, and software architecture integrity.

This document details the complete operational manual: the agent roster hierarchy, the Ralph Loop orchestration daemon, the technology stack, documented Sprint 0 operational failure modes, and standard operating directives.

System Architecture: The Multi-Agent Organization

Monolithic single-agent systems degrade as context windows fill. An individual agent assigned an entire repository backlog rapidly suffers from attention loss, memory contamination, and divergent decision-making.

OLabs solves this by decomposing software engineering into fourteen specialized agents, each constrained by a bounded operational mandate:

MULTI-AGENT SCATTER-GATHER ORG CHART:

                           ┌───────────────────────────┐
                           │   PRODUCT OWNER AGENT     │
                           └─────────────┬─────────────┘
                                         │
                           ┌─────────────▼─────────────┐
                           │    SCRUM MASTER AGENT     │
                           └─────────────┬─────────────┘
                                         │
                           ┌─────────────▼─────────────┐
                           │   CHIEF ARCHITECT AGENT   │
                           └─────────────┬─────────────┘
                                         │
        ┌───────────────────┬────────────┴───────┬───────────────────┐
        │                   │                    │                   │
┌───────▼───────┐   ┌───────▼───────┐    ┌───────▼───────┐   ┌───────▼───────┐
│ BACKEND POD   │   │ FRONTEND POD  │    │ DEVOPS POD    │   │ QA POD        │
│ Lead + Devs   │   │ Lead + Devs   │    │ CI/CD + Infra │   │ Lead + Auto   │
└───────────────┘   └───────────────┘    └───────────────┘   └───────────────┘

The 14-Agent Operational Roster:

Agent Identifier Assigned Role Bounded Mandate Permitted Tooling Restricted Boundaries
PO-Agent Product Owner Backlog definition, acceptance criteria File read, Docs Code generation strictly prohibited
SM-Agent Scrum Master Cadence tracking, dependency resolution File read, Status Direct code edits prohibited
Arch-Agent Technical Architect System design, interface contracts, PR gating File read, AST check Feature implementation prohibited
BE-Lead Backend Lead API envelope design, database schemas Terminal, Files UI components prohibited
BE-Dev (×2) Backend Engineers Database queries, service handlers Terminal, Files Schema alterations prohibited
FE-Lead Frontend Lead Design system integration, layout state Terminal, Files Server API routes prohibited
FE-Dev (×2) Frontend Engineers UI views, component composition Terminal, Files State schema modifications prohibited
DevOps-Agent Infrastructure Engineer Docker Compose, CI/CD workflows Terminal, Docker Application business logic prohibited
QA-Lead QA Architect Test plan creation, test data generation File read, Test run Production code edits prohibited
QA-Auto QA Automation Integration tests, E2E regression suites Playwright, Bun test Modifying test assertions prohibited
BA-Agent Business Analyst Workflow mapping, compliance docs Markdown writer Code generation prohibited

Every agent possesses an immutable system prompt file committed to git in /agents/. Each prompt strictly declares authorized directories, prohibited actions, and explicit escalation paths.

Orchestration Layer: The Ralph Loop Daemon

Autonomous agent coordination executes through Ralph Loop, a continuous background daemon that polls a file-based task exchange directory:

RALPH LOOP ORCHESTRATION PIPELINE:

1. TASK INGESTION:
   Operator deposits JSON task file into /tasks/ready/

2. CONCURRENCY DISPATCH:
   Ralph Loop locks file, moves to /tasks/processing/, and spawns sub-agent process.

3. EXECUTION MONITORING:
   Process runs with a hard timeout of 15 minutes.
   Heartbeat emits progress status to central log every 60 seconds.

4. CONTRACT VERIFICATION:
   On process exit, CI hooks execute syntax, linter, and unit test checks.

5. SETTLEMENT:
   Success: Task file moves to /tasks/completed/; PR opened against sprint branch.
   Failure: Task file moves to /tasks/failed/ with error trace; alerts human lead.

Task Activation Payload Schema:

{
  "taskToken": "TASK-2026-0422-01",
  "assignedAgent": "be-dev1",
  "objective": "Implement patient registration endpoint with Zod schema validation",
  "dependencies": ["TASK-2026-0422-00"],
  "contextFiles": [
    "agents/be-dev1.md",
    "apps/api/src/schemas/patient.ts"
  ],
  "verificationCommand": "bun test apps/api/src/routes/patient.test.ts",
  "timeoutSeconds": 900
}

Production Stack Specification

The technology stack is deliberately conservative to maximize machine-verifiability and minimize runtime ambiguity:

  • Frontend: Nuxt 4 + TypeScript (Strict Mode).
  • Backend: Hono + TypeScript (Standard Request/Response fetch API compliance).
  • ORM & Database: Drizzle ORM + PostgreSQL (Full type-safety from schema to query).
  • Authorization: JWT authentication + Database-evaluated Role-Based Access Control (RBAC).
  • Containerization: Docker Compose for local reproducibility; GitHub Actions for continuous delivery.
  • Code Quality Linters: Biome (formatting and import sorting) + TypeScript Strict.

Documented Sprint 0 Operational Failure Modes

During initial execution on a complex multi-tenant clinical application, four critical failure modes emerged. The following table documents the empirical failures, root cause analyses, and implemented operational fixes:

Failure Mode Empirical Impact Root Cause Analysis Corrective Mitigation
1. Agent Execution Timeouts Frontend Lead and DevOps agents halted mid-task, leaving uncommitted state. Monolithic tool calls executing project initialization and package downloads exceeded the 15-minute process timeout budget. Subdivided task definitions. Infrastructure initialization is now partitioned into discrete, sub-5-minute atomic stages.
2. Pipeline Stalling on Empty Task Queue All agents remained in IDLE state for 65 minutes following sprint kickoff. Operators initiated the Ralph Loop daemon prior to populating the /tasks/ready/ directory. Automated kickoff script now seeds the initial task batch atomically prior to daemon launch.
3. Downstream Git Rejections 4 sub-agents aborted because git branches lacked initial baseline commits. Sprint feature branch created without a commit head; downstream agents could not compute branch ancestry. Pre-sprint checklist enforces an initial baseline commit containing shared type definitions before agents are initialized.
4. Package Security Scanner Rejection Security scanner blocked legitimate npx nuxt prepare command during CI. Automated scanner flagged nuxt as a prospective typosquat of next (Levenshtein distance = 1). Added explicit domain and package allowlist to repository security policies.

Senior Human Engineering Allocation (The 30%)

The 30% human effort allocation is executed exclusively by senior staff engineers, technical architects, and domain leads. The human workload encompasses:

  1. Architectural Invariant Auditing: Reviewing database schema alterations, session lifecycles, and cryptographic implementations.
  2. Regulatory & Statutory Compliance: Verifying data retention and access control compliance against statutory frameworks (e.g., India DPDPA 2023, HIPAA).
  3. Escalation Intervention: Resolving architectural deadlocks when automated conflict detection halts cross-agent branches.
  4. Orchestration Tuning: Modifying task specifications and linter rules when repetitive agent failure patterns emerge.

Standard Operating Directives

  1. Never Deploy Unbounded Agents: Every agent must operate within a constrained file directory with explicit tool authorization.
  2. Enforce File-Based Audit Trails: All agent prompts, task payloads, and execution logs must be committed to git alongside application source code.
  3. Retain Human Authority on Critical Paths: No code modifying authentication, cryptographic keys, payment processing, or database migration tables may merge without explicit human sign-off.

OLabs engineers software systems using verified human-agent workflows. Contact our engineering team to evaluate your product architecture.

Written by a human, with assistance from AI.