I build enterprise AI platforms, multi-agent engineering systems, and governed autonomous software delivery factories.

I'm an engineering leader with 18+ years of experience building enterprise platforms and leading high-performing engineering teams. My recent work focuses on production agentic AI, model-independent infrastructure, agent orchestration, enterprise knowledge systems, evaluations, and developer productivity.

I'm focused on moving AI engineering beyond individual copilots and coding agents toward reliable systems where humans, agents, and deterministic software work together.

• Humans define intent, constraints, risk, and consequential decisions.
• Agents plan, use tools, modify software, and execute bounded work.
• Deterministic systems enforce policy, verification, evidence, and recovery.

The goal isn't simply to generate code faster. It's to deliver verified outcomes consistently.

The engineering discipline for designing, governing, operating, evaluating, and continuously improving AI software factories.

FDLC.ai is the public home of the Factory Development Lifecycle, an engineering framework for building reliable, governed autonomous software delivery systems.

FDLC defines how an AI software factory should operate. Mission Control implements those principles in a working software delivery system.

Define → Plan → Configure → Execute → Verify → Deliver → Observe → Improve

FDLC brings together:

• Agent orchestration: Agents, execution harnesses, tools, and workflows.
• Context engineering: RAG, memory, retrieval, and knowledge systems.
• Durable execution: Long-running workflows, state, retries, and recovery.
• Evaluation & verification: Quality gates, regression detection, and independent validation.
• Governance & observability: Permissions, budgets, evidence, tracing, and operational controls.
• Continuous improvement: Learning from verified outcomes and production evidence.

Verified delivery, not merely generated code.

🔗 Explore: FDLC.ai

A governed control plane for human-directed, agent-executed software delivery.

Mission Control coordinates autonomous coding agents, execution infrastructure, independent verification, and human approval to produce evidence-backed, review-ready pull requests.

Mission → Plan → WorkOrder → Execution → Verification → Pull Request → Human Acceptance → Learning

• Agent Orchestration & Durable Execution: Provider-independent harnesses, persistent workers, lease-based execution, isolated Git worktrees, scoped tools, and bounded recovery.
• AI Evaluation & Independent Verification: Rubric-based evaluations, baseline comparisons, deterministic quality gates, and independently verified outcomes.
• Platform Governance: Versioned Factory configurations, policy enforcement, execution budgets, audit trails, and human approval boundaries.
• Observability & Learning: Execution tracing, evaluation datasets, Factory Memory, failure analysis, and evidence-driven improvement proposals.

TypeScript · React · Convex · Hono · GitHub Apps · GitHub Actions · Playwright

Built with 16 packages, 190+ test suites, automated CI/CD, and independent verification.

Demonstrated: End-to-end governed delivery from approved engineering intent through agent execution, independent verification, real GitHub pull requests, and human acceptance.

Status: Active development with qualified production-pilot capabilities.

🔗 Explore: Mission Control on GitHub

An AI-native developer platform connecting engineering intent, intelligent agents, tools, and independently verified software delivery.

MyEve is my multi-agent AI software engineering platform. Sofie is its primary AI engineering assistant and developer interface, helping engineers define requirements, coordinate agents, manage engineering context, and review results.

Intent → Plan → Code → Test → Verify → Deploy → Operate → Improve

• Multi-Agent Orchestration: Specialized agents, persistent context, delegated work, and tool coordination.
• Developer Experience: Conversational engineering workflows, structured work tracking, and reviewable results.
• AI Platform Infrastructure: Agent execution contracts, secure integrations, capability controls, and durable state.
• Autonomous Software Delivery: Integration architecture connecting Deep Agent, MyFactory, Mission Control, and MyApps.
• Evaluation & Verification: Independent validation, automated quality gates, execution evidence, and controlled release workflows.

Architecture: Sofie · Relay · Deep Agent · MyFactory · Mission Control · MyApps

Status: Limited beta with two external installations supporting bounded Sofie chat. Autonomous developer execution and full software delivery remain under qualification.

🔗 Explore: MyEve on GitHub

A technical guide to designing and operating governed AI software factories, covering agent architecture, orchestration, context engineering, durable execution, evaluations, verification, observability, and continuous improvement.

🔗 Explore: AI Software Factory Mastery Guide

• AI-FDE | AI Factory Deployed Engineer: An evidence-driven workspace supporting human Factory Deployed Engineers in discovering workflow friction, defining factory requirements, and guiding adoption.
• Agentic Pi Harness: Agent harness architecture, model and tool execution, and reusable orchestration infrastructure.
• Multi-Agent Observability: Execution tracing, evaluation, runtime visibility, and operational controls for multi-agent systems.
• Agentic-KB: Enterprise knowledge search and retrieval, persistent memory, provenance, and RAG infrastructure.

AI & Agent Platforms: OpenAI · Claude · Codex · Agent SDKs · LangGraph · MCP · RAG · Agent Orchestration · Context Engineering · Model Routing

Agent Infrastructure: Agent Harnesses · Durable Job Execution · Worker Runtimes · Sandboxed Execution · Git Worktrees · Checkpointing · Recovery

AI Evaluation & Operations: LLM Evals · LangSmith · OpenTelemetry · Independent Verification · Quality Gates · Observability

Backend & Platforms: Python · TypeScript · JavaScript · C# · Node.js · FastAPI · Convex · REST APIs · PostgreSQL · Docker · GitHub Apps · CI/CD

Engineering Leadership: Engineering Strategy · Team Development · Technical Roadmaps · Architecture Reviews · Developer Platforms · Production Reliability

The next breakthrough in autonomous software engineering isn't generating more code. It's proving that the code works.

AI agents can write software faster than ever. The bottleneck is shifting from implementation to verification. Knowing what was built, whether it meets the requirements, and whether it's safe to ship.

That's why I'm building systems around agents that make execution bounded, verification independent, and every outcome backed by evidence.

Agents build. Systems verify. Humans decide.

Trust the system, not the model.

I'm interested in collaborating with engineers and teams building AI platforms, agent infrastructure, developer tools, and autonomous software delivery systems.

• LinkedIn: Jarrett West
• GitHub: jaydubya818
• FDLC.ai: fdlc.ai