name: "Bruce Deb"
handle: "deb888"
role: "AI Developer · Fullstack Architect · AI DevOps Engineer"
mission: "Building AI-powered applications end-to-end — from React Native to LangChain agents deployed on Kubernetes"
philosophy: "Fullstack is the foundation. LangChain is the brain. Kubernetes is the body. OpenClaw is the heartbeat."
domains:
mobile: "React Native · Expo · Ionic/Capacitor — cross-platform native apps"
ai_agents: "LangChain · LangGraph · Deep Agents · Multi-Agent Systems · RAG · Tool-Use · Memory"
agent_proto: "MCP (Model Context Protocol) · A2A (Agent-to-Agent) · ACP (Agent Client Protocol)"
frameworks: "LangChain · CrewAI · Google ADK · Microsoft Agent Framework · Mastra · OpenAI Agents SDK"
backend: "NestJS · Fastify · Python · PostgreSQL · Redis · Kafka"
frontend: "Angular 18+ (Signals, Standalone) · React · Tailwind"
aws: "Bedrock · Lambda · API Gateway · DynamoDB · SQS · S3 — serverless AI on AWS"
infra: "Kubernetes · Terraform · ArgoCD · Istio · Crossplane"
tools_i_love:
- "LangChain — The standard for LLM application development"
- "LangGraph — Agent orchestration with cycles, state, and persistence"
- "MCP — Model Context Protocol, the universal tool connector for AI"
- "A2A — Google-led Agent-to-Agent protocol for multi-agent interoperability"
- "Google ADK — Opinionated, batteries-included agent runtime for GCP"
- "Microsoft Agent Framework — Unified AutoGen + Semantic Kernel at GA"
- "Mastra — TypeScript-native agent framework with workflows + memory"
- "Deep Agents — LangChain's long-running, persistent agent workflows"
- "OpenAI Agents SDK — Clean multi-agent delegation with minimal abstraction"
- "Claude Agent SDK — Anthropic's agent framework for tool-use and reasoning"
- "OpenCode — AI coding agent I'm using right now to build this profile"
- "OpenClaw — Personal AI assistant ecosystem (core contributor)"
- "Gemini 2.5 / Claude 4 — The frontier models driving agent reasoning"
- "React Native — One codebase, every platform"
- "AWS Bedrock — Foundation models + agents as a managed service"
- "AWS Serverless — Lambda, API Gateway, DynamoDB — pay-per-use AI backends"
ai_devops:
ml_pipelines: "Kubeflow · MLflow · DVC · Weights & Biases"
serving: "AWS Bedrock · vLLM · TGI · Ollama · Triton Inference Server · TensorRT-LLM"
monitoring: "LangSmith · Prometheus · Grafana · Phoenix · Datadog"
governance: "Agent lifecycle management · Guardrails · Audit trails · Cost tracking"
automation: "OpenClaw Workflows · Cron · Heartbeat · Task Flow · Hooks"graph TB
subgraph "MOBILE FIRST"
A["React Native / Expo"] --> B["iOS & Android"]
A --> C["Hybrid (Ionic)"]
end
subgraph "AGENT PROTOCOLS"
P1["🔌 MCP (Tool Access)"] --- P2["🤝 A2A (Agent-to-Agent)"]
P2 --- P3["🔄 ACP (Agent Client)"]
end
subgraph "AI FRAMEWORKS 2026"
D["LangChain"] --> E["LangGraph / Deep Agents"]
F["Google ADK"] --> P2
G["MS Agent Framework"] --> P1
H["Mastra (TypeScript)"]
I["OpenAI Agents SDK"]
J["Claude Agent SDK"]
K["CrewAI"]
Z["☁️ AWS Bedrock"]
end
subgraph "MULTI-AGENT SYSTEMS"
L["Supervisor / Worker"] --> M["Swarm / Pipeline"]
M --> N["Reflection / ReAct"]
N --> O["RAG · Tool-Use · Memory · Planning"]
end
subgraph "BACKEND & OPS"
Q["NestJS / FastAPI"] --> R["PostgreSQL · Redis · Kafka"]
Q --> S["REST · GraphQL · gRPC"]
W["☁️ AWS Serverless"] --> Q
end
subgraph "AI DEVOPS & SERVING"
T["Terraform"] --> U["Kubernetes"]
U --> V["vLLM · Ollama · TGI · TensorRT-LLM"]
V --> W["MLflow · Prometheus · LangSmith · Datadog"]
W --> X["OpenClaw Workflow Engine"]
end
C --> Q
O --> A & C & Q
X --> U & L
P1 --> D & K
P3 --> X
style A fill:#61DAFB,color:#000
style D fill:#FFBE0B,color:#000
style F fill:#4285F4,color:#fff
style G fill:#00A4EF,color:#fff
style H fill:#8B5CF6,color:#fff
style O fill:#00FFE7,color:#000
style P1 fill:#00C853,color:#fff
style P2 fill:#FF6F00,color:#fff
style T fill:#7B42BC,color:#fff
style U fill:#326CE5,color:#fff
style X fill:#FF006E,color:#fff
style Z fill:#FF9900,color:#fff
style W fill:#FF9900,color:#fff
382k+ ⭐ GitHubSelf-hosted AI gateway connecting Telegram, WhatsApp, Discord, iMessage → AI agents
Stack: TypeScript · Node.js · Plugin Architecture · MCP/ACP
My part: Skills engine, automation layer, plugin SDK, multi-agent routing
Workflows: Cron jobs · Heartbeat monitoring · Task Flow orchestration · Hooks · Standing Orders
Multi-agent system with planning, tool-use, persistent memory, and human-in-the-loop
Stack: LangChain · LangGraph · LangSmith · Qdrant · PostgreSQL
Patterns: Supervisor/worker · Swarm · Pipeline · Reflection · ReAct
Using OpenCode (AI coding agent) paired with OpenClaw for autonomous development pipelines
Setup: OpenCode writes code → OpenClaw deploys it → Cron monitors it → Heartbeat reports back
Flow: "write a Slack bot" → OpenCode codes it → OpenClaw deploys to K8s → Cron keeps it alive
Cross-platform native apps — one TypeScript codebase, iOS + Android
Stack: React Native · Expo · TypeScript · Socket.io
Projects: Real-time chat · GPS tracking · Image upload · REST APIs
ML infrastructure: model serving, monitoring, auto-scaling, and cost optimization
Stack: Kubernetes · Terraform · vLLM · MLflow · Prometheus · Grafana
Scale: 50+ clusters · 500+ services · 99.99% uptime
%%{init: {"theme": "base", "themeVariables": { "background": "#0D1117", "primaryColor": "#00FFE7", "primaryTextColor": "#fff", "primaryBorderColor": "#333", "lineColor": "#00FFE7", "secondaryColor": "#0a0a1a", "tertiaryColor": "#1a1a2e"}}}%%
graph LR
subgraph "PROTOCOLS"
A["🔌 MCP"] --> B["Tool Access"]
C["🤝 A2A"] --> D["Agent Interop"]
E["🔄 ACP"] --> F["Client Protocol"]
end
subgraph "FRAMEWORKS"
G["LangGraph / Deep Agents"]
H["Google ADK"]
I["MS Agent Framework"]
J["Mastra"]
K["OpenAI Agents SDK"]
L["Claude Agent SDK"]
U["☁️ AWS Bedrock"]
end
subgraph "FRONTIER MODELS"
M["⚡ Gemini 2.5 Pro"]
N["🔥 Claude 4 Sonnet/Opus"]
O["🧠 GPT-5"]
P["🦙 Llama 4"]
end
subgraph "PRODUCTION"
Q["vLLM · Ollama · TGI"]
R["LangSmith · Datadog · Phoenix"]
S["Kubernetes · Terraform · ArgoCD"]
T["OpenClaw · Cron · Heartbeat"]
end
A & C & E --> G & H & I & J & K & L & U
G & H & I & J & K & L & U --> M & N & O & P
M & N & O & P --> Q
Q --> R
R --> S
S --> T
style A fill:#00C853,color:#fff
style C fill:#FF6F00,color:#fff
style E fill:#8B5CF6,color:#fff
style G fill:#FFBE0B,color:#000
style H fill:#4285F4,color:#fff
style I fill:#00A4EF,color:#fff
style M fill:#4285F4,color:#fff
style N fill:#D97706,color:#fff
style T fill:#FF006E,color:#fff
style U fill:#FF9900,color:#fff
2026 Key Trends:
- 🔌 MCP — Universal standard for AI-to-tool connectivity (Anthropic-led)
- 🤝 A2A — Google-led Agent-to-Agent protocol for cross-framework interop
- 🪟 Microsoft Agent Framework — AutoGen + Semantic Kernel unified at GA
- 🎯 Google ADK — Batteries-included agent runtime for GCP-native stacks
- 📦 Mastra — TypeScript-native agent framework (workflows, memory, Studio)
- 🌀 Deep Agents — LangChain's long-running persistent agent workflows
- 🔥 Claude 4 / Gemini 2.5 / GPT-5 — Frontier models driving agent reasoning
- 🛡️ Agent Governance — Lifecycle management, guardrails, cost tracking
🦜️ LangChain & AI Agents (click to expand)
| Tech | What I Build With It |
|---|---|
| LangChain | LLM app framework — chains, agents, RAG, tool-use, memory |
| LangGraph | Stateful agent orchestration — cycles, branching, persistence |
| Deep Agents | Long-running persistent agent workflows with LangChain |
| LangSmith | LLM observability — traces, evaluations, prompt management |
| Google ADK | Batteries-included agent runtime for GCP with A2A interop |
| MS Agent Framework | Unified AutoGen + Semantic Kernel (GA) for .NET/enterprise |
| Mastra | TypeScript-native agents with workflows, memory, and Studio |
| OpenAI Agents SDK | Clean multi-agent delegation with minimal abstraction |
| Claude Agent SDK | Anthropic's agent SDK — tool-use, reasoning, handoffs |
| CrewAI | Role-based multi-agent teams — rapid prototyping |
| MCP Servers | Model Context Protocol — universal tool connectivity |
| A2A Protocol | Agent-to-Agent interoperability across frameworks |
| OpenClaw | Personal AI assistants — skills engine, automation, plugin SDK |
| Qdrant / pgvector | Vector stores for RAG — hybrid search, filtering, re-ranking |
| vLLM / Ollama / TGI | Self-hosted model serving — privacy-first, local inference |
| AWS Bedrock | Managed FM access — Claude, Llama, Mistral + agents via AWS |
⚛️ React Native & Mobile (click to expand)
| Layer | Stack |
|---|---|
| Framework | React Native, Expo, Ionic/Capacitor |
| Navigation | React Navigation, Expo Router |
| State | React Query, Zustand, Redux Toolkit |
| UI | NativeBase, Tamagui, Tailwind Native |
| Native APIs | Camera, Geolocation, Bluetooth, Push Notifications |
| Build | EAS Build, Xcode, Android Studio, Fastlane |
| Store | App Store Connect, Google Play Console |
🔧 OpenCode & AI Development (click to expand)
| Tech | What I Do With It |
|---|---|
| OpenCode | AI coding agent — building this profile and more |
| Claude Code / Codex | Terminal-based AI coding assistants |
| OpenClaw + OpenCode | Autonomous dev loop — OpenCode writes, OpenClaw deploys |
| MCP Servers | Model Context Protocol — connecting AI to tools and data |
| A2A Protocol | Agent-to-Agent — multi-framework agent coordination |
| ACP Agents | Agent Client Protocol — multi-agent coordination |
| Genkit | Google's open-source AI framework for TypeScript/Node.js |
☸️ AI DevOps & MLOps (click to expand)
| Tech | What I Do With It |
|---|---|
| Kubernetes | Model serving infrastructure — EKS/GKE/AKS |
| AWS Serverless | Lambda · API Gateway · DynamoDB · SQS · S3 — serverless AI backends |
| vLLM / TGI / TensorRT-LLM | LLM inference serving with continuous batching |
| Terraform / Pulumi / Crossplane | Infrastructure as Code for ML platforms |
| MLflow / W&B | Experiment tracking, model registry, artifact storage |
| Prometheus / Grafana / Datadog | Model monitoring — latency, throughput, token usage |
| LangSmith / Phoenix | LLM observability — traces, evals, prompt management |
| ArgoCD / Flux | GitOps for model deployments |
| Kubeflow / Flyte | ML pipelines on Kubernetes |
| Agent Governance | Lifecycle mgmt, guardrails, audit trails, cost tracking |
🦞 OpenClaw Workflow Engine (click to expand)
| Feature | What It Does |
|---|---|
| Cron Jobs | Scheduled tasks — daily reports, reminders, batch jobs |
| Heartbeat | Periodic agent turns every ~30 min — inbox check, calendar scan |
| Task Flow | Durable multi-step orchestration with revision tracking |
| Hooks | Event-driven scripts — session lifecycle, message flow |
| Standing Orders | Persistent agent instructions (AGENTS.md) |
| Inferred Commitments | Memory-like follow-ups from natural conversation |
| Skills | SKILL.md instruction packs — teach agents new abilities |
| Plugins | Channel, tool, and provider extensions from ClawHub |
⚛️ Full Stack (click to expand)
| Layer | Stack |
|---|---|
| Frontend | Angular 18+ (Signals, Standalone), React, Tailwind |
| Backend | NestJS, Fastify, Express, Python (FastAPI), Go |
| Database | PostgreSQL, MongoDB, Redis, TimescaleDB, ClickHouse |
| API | REST, GraphQL Federation, gRPC, tRPC, WebSocket |
| Mobile | React Native, Expo, Ionic/Capacitor |
| Testing | Vitest, Playwright, Cypress, Testing Library |
mindmap
root((🧠 Current Focus))
Agent Protocols
MCP
A2A
ACP
AI Frameworks 2026
LangGraph
Deep Agents
Google ADK
MS Agent Framework
Mastra
AWS Bedrock
OpenAI Agents SDK
Claude Agent SDK
Frontier Models
Gemini 2.5 Pro
Claude 4 Sonnet
GPT-5
Llama 4
React Native
Cross-platform apps
Expo
Native modules
OpenClaw
Skills
Workflows
Plugin SDK
OpenCode
AI coding
Agent protocols
MCP
AI DevOps
K8s model serving
AWS Serverless
ML monitoring
Agent governance
AI Developer · Fullstack · AI DevOps · OpenCode · OpenClaw
"React Native → LangChain → Kubernetes → OpenClaw workflow — I build the whole pipeline."

