Production AI workflows are deterministic, stateful orchestration patterns where autonomous agents perceive context, execute verified tools, manage DAG graphs, and automatically recover from API failures.
Explore runnable, multi-file code architectures for LangGraph, CrewAI, Temporal, and vector stores—benchmarked for token economy, sub-100ms state recovery, and zero token waste.
Implement a stateful LangGraph pipeline for high-stakes financial auditing, featuring built-in human-in-the-loop approval gates and strict token budgeting controls.
Deepak Bagada
Design self-healing Kubernetes infrastructure by deploying AutoGen 0.4 distributed multi-agent workflows for autonomous incident triage and remediation.
Deepak Bagada
Architect a production-ready multi-agent RAG pipeline leveraging LlamaIndex and Qdrant for sophisticated hybrid vector-keyword search orchestration.
Deepak Bagada
Architect a resilient, multi-agent LLM pipeline using LangGraph and Qdrant. Explore the Planner-Worker-Reviewer pattern for production-grade, stateful AI workflows with complex reasoning and long-term memory.
Deepak Bagada
Create a cutting-edge self-healing infrastructure using AutoGen agents that continuously analyze Prometheus metrics to detect, diagnose, and remediate Kubernetes cluster anomalies in real time.
Deepak Bagada
Design a highly scalable, event-driven financial audit system utilizing LangGraph for complex compliance workflows and Qdrant for semantic hybrid search over unstructured financial records.
Deepak Bagada
A comprehensive blueprint for implementing Multi-Modal Vision RAG architectures, leveraging Gemini 2.5 Pro for visual reasoning and Qdrant for high-dimensional vector search to unlock insights from PDFs, diagrams, and video frames.
Deepak Bagada
Learn to build a self-healing CI/CD pipeline using Claude 3.7 Sonnet and FastMCP, enabling your codebase to automatically detect, analyze, and patch regressions during runtime.
Deepak Bagada
Discover how to orchestrate advanced reasoning pipelines using DeepSeek-R2 and LangGraph to build multi-agent systems that verify, iterate, and solve complex problems autonomously.
Deepak Bagada
Deploy a production-ready role-based multi-agent support team using CrewAI v1.16 hooks, WaitTool, and SLA tracking.
Deepak Bagada
Implement a high-performance corporate RAG pipeline combining n8n event triggers with Qdrant hybrid vector-keyword retrieval.
Deepak Bagada
Learn how to build self-healing enterprise agentic pipelines combining LangGraph state machine routing with AutoGen multi-agent debate.
Deepak Bagada
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