Multi-Agent Orchestration Patterns: A Field Guide
A field guide to six multi-agent orchestration patterns and when each one wins: pipeline, fan-out, orchestrator-worker, supervisor, blackboard, and swarm.
17 min read
Mikul Gohil — AI Engineer 👋 👋
LLM-Powered Systems · Agentic Workflows · Enterprise Web Architecture
I'm an AI Engineer with 18+ years of experience shipping production-grade software, based in Dubai, UAE. I design and build LLM-powered systems, agentic workflows, and AI-augmented engineering pipelines — turning fragile prototypes into reliable, measurable infrastructure that works at enterprise scale.
My foundation in React.js, Next.js, TypeScript, and enterprise web architecture gives me the production context most AI experiments lack. I've worked across financial services and global agencies, which means I understand what compliance-constrained, high-traffic AI deployment actually looks like.
Certifications
Next.js Foundations Certification
Vercel
Certified expertise in building production-ready applications with Next.js
AI-Augmented Engineering, Directed
I direct specialized AI agents to deliver your complete product vision.
Director
WORKFLOW
Analyze Data
Code Prototype
Rapid Iteration
Launch Product
Specialized AI Agents Working Together Directed By A Human
Code Agent
Engineers full-stack solutions with clean architecture and modern frameworks
Research Agent
Discovers market opportunities and analyzes competitive landscapes
Content Agent
Crafts compelling narratives and designs information architecture
Chat Agent
Creates conversational experiences with natural language understanding
Core Competencies & Technical Skills
My focus is building production-grade AI systems — LLM integration, agentic workflows, and AI-augmented engineering pipelines. That work sits on top of 18+ years of enterprise software delivery, which is what separates reliable AI infrastructure from well-packaged demos.
AI & LLM Engineering
- LLM Integration (OpenAI, Anthropic)
- Agentic Workflow Design
- Multi-agent Orchestration
- Tool Calling & Function Calling
- Structured Output Validation
- Prompt Engineering
- Agent Memory Systems
- RAG (Retrieval-Augmented Generation)
- Vector Databases
- LangGraph
- LangFuse Observability
- AI-Augmented Dev Pipelines
- Python (applied)
Frontend Technologies
- React.js
- Next.js
- TypeScript
- JavaScript ES6+
- HTML5
- CSS3
- Tailwind CSS
- Redux Toolkit
- Zustand
- React Query
- SWR
- React Hook Form
Backend & Cloud
- Node.js
- Express.js
- REST APIs
- GraphQL
- MongoDB
- PostgreSQL
- AWS
- Vercel
- Netlify
Tools & DevOps
- Git
- GitHub Actions
- Webpack
- Vite
- Jest
- ESLint
- Prettier
- Docker
CMS & Platforms
- Sitecore XM Cloud
- Contentful
- Strapi
- WordPress Headless
- Sanity
- contentstack
UI/UX & Design
- Figma
- Responsive Design
- Web Accessibility (WCAG)
- Material-UI
- Shadcn/ui
- Ant Design
- Chakra UI
Recent Posts
View all →Claude Code Mastery: The Config That Compounds
How I configure Claude Code as a programmable agent: the .claude directory, CLAUDE.md, rules, skills, subagents, plugins, and MCPs that compound over time.
26 min readThe Real Problem with AI in Companies Is Not Tools
Enterprises keep losing money on AI not because of bad models or bad vendors but because of how they think about the work. The mindset gap, with data.
11 min readWhy AI-Built Applications Keep Shipping Broken
AI writes code. Shipping software is a systems problem. The 11 reasons AI-built apps keep breaking in production, with data and real incidents.
12 min readAI Kit: The Open-Source CLI That Makes AI Coding Assistants Actually Useful
I built AI Kit because every AI coding tool starts dumb. One command auto-detects your stack and generates tailored rules, 48 skills, 16 agents, and quality hooks for Claude Code, Cursor, and more.
18 min read