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Hey β€” It's Sandip Das πŸ‘‹

Here’s a quick recap of what we shared on LearnXopsβ€”check out anything you missed πŸ‘‡

The β€œAI for Cloud & DevOps Engineers” series is finally finished , covering from AI fundamentals and LLMs to RAG, AI agents, AI-native DevOps, Kubernetes, observability, governance, and production AI systems.

πŸ‘¨πŸ»β€πŸ’» AI Projects & Exclusive Content for XOps Pro Engineers! πŸš€

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Project:AI-Powered Kubernetes Troubleshooting Assistant

Agentic AI for Autonomous Kubernetes Debugging & Self-Healing Infrastructure (Day 30)

πŸ—“ Date: May 13, 2026

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Building Your AI Roadmap as a DevOps Team

Prioritization framework, quick wins vs long-term bets, and how to get leadership buy-in (Day 29)

πŸ—“ Date: May 11, 2026

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The Future of Platform Engineering with AI

AI-native IDPs, self-healing infrastructure, and what the "AI-augmented SRE" looks like in 2026 (Day 28)

πŸ—“ Date: May 10, 2026

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Multi-Agent AI Systems & Orchestration Patterns

Data residency, model access controls, audit logging, and responsible AI frameworks for teams (Day 27)

πŸ—“ Date: May 9, 2026

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Multi-Agent AI Systems & Orchestration Patterns

Supervisor patterns, parallel execution, agent-to-agent communication β€” and when NOT to use them (Day 26)

πŸ—“ Date: May 8, 2026

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Monitoring AI in Production: Drift, Quality & Evals

LLM evaluation frameworks, output monitoring with Langfuse/Helicone, drift detection(Day 25)

πŸ—“ Date: May 7, 2026

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AI Cost Optimization: Caching, Batching & Right-sizing

Semantic caching, request batching, model cascading β€” techniques to slash AI infra bills (Day 24)

πŸ—“ Date: May 6, 2026

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Managed AI Services β€” SageMaker, Vertex AI & Azure ML

When to use managed vs self-hosted, a cloud-by-cloud breakdown for MLOps teams (Day 23)

πŸ—“ Date: May 5, 2026

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Deploying AI Models on Kubernetes

A practical field guide to GPU node pools, model serving with vLLM and Triton, and the dark art of autoscaling inference workloads on GKE and EKS β€” without setting your cloud bill on fire. (Day 22)

πŸ—“ Date: May 4, 2026

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MLOps vs LLMOps: What's Different in 2026

Model versioning, prompt versioning, evaluation pipelines β€” the new ops discipline for AI (Day 21)

πŸ—“ Date: May 3, 2026

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AI in CI/CD Pipelines: Smarter Automation

Auto-generating changelogs, test suggestions, deployment summaries, and anomaly detection (Day 20)

πŸ—“ Date: May 2, 2026

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AI Security: Prompt Injection, Data Leakage & Supply Chain

New attack surfaces introduced by AI β€” and how to defend them at the infrastructure level (Day 19)

πŸ—“ Date: April 30, 2026

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Project:AI-Powered Incident Response Agent

Let's Build a Autonomous SRE AI agent (Day 18)

πŸ—“ Date: April 29, 2026

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Project: AI-Powered AWS Idle Resource Finder

Build a useful AWS Cost Analyzer which identify underutilized or idle resources across all regions and use AI (Local LLM / Amazon Bedrock) to filter the TOP resources for removal (Day 17)

πŸ—“ Date: April 28, 2026

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Project: AI-Powered Runbook Assistant

Build a production-ready RAG (Retrieval-Augmented Generation) app (Day 16)

πŸ—“ Date: April 27, 2026

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Open-Source Models: Llama, Mistral & Running Locally and on the Cloud

9Self-hosting LLMs Local Machines and on EC2/GKE with Ollama β€” when open-source beats API services (Day 15)

πŸ—“ Date: April 26, 2026

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LangChain & LlamaIndex: When to Use What ?

The two dominant orchestration frameworks compared β€” architecture choices for DevOps use cases (Day 14)

πŸ—“ Date: April 25, 2026

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Building AI Agents: What They Are & How They Work

Tools, function calling, ReAct loops β€” agents as autonomous automation workers (Day 13)

πŸ—“ Date: April 24, 2026

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AI-Driven Observability & Log Analysis

Using LLMs to parse logs, correlate alerts, and draft incident summaries automatically (Day 12)

πŸ—“ Date: April 23, 2026

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AI for Infrastructure as Code: Terraform & Pulumi

Generating, reviewing, and auditing IaC with AI β€” practical prompts and pitfalls (Day 11)

πŸ—“ Date: April 18, 2026

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AI-Assisted Code Review & Static Analysis

GitHub Copilot, CodeRabbit, and custom review bots β€” how AI fits into your PR workflow (Day 10)

πŸ—“ Date: April 16, 2026

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RAG: Retrieval-Augmented Generation Explained

The architecture pattern that gives AI real knowledge β€” and why every cloud team needs it (Day 9)

πŸ—“ Date: May 2, 2026

Free Forever curated for everyone in the tech community. ❀️

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Embeddings & Vector Databases Demystified

What vectors are, why semantic search matters, and how Pinecone/Weaviate/pgvector fit in (Day 8)

πŸ—“ Date:March 23, 2026

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AI Safety, Hallucinations & Trust in Production

Why AI lies confidently and how to build guardrails as an infrastructure problem (Day 7)

πŸ—“ Date: March 18, 2026

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Tokens, Context Windows & Why They Matter for Cost

How to think about context limits, pricing models, and request optimization (Day 6)

πŸ—“ Date: March 17, 2026

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AI APIs: OpenAI, Anthropic, Google & AWS Bedrock

Comparing model APIs like you compare managed services (Day 5)

πŸ—“ Date: March 8, 2026

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Prompt Engineering 101

System prompts, few-shot examples, chain-of-thought β€” the new "config files" of AI (Day 4)

πŸ—“ Date:March 7, 2026

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The AI Stack: From GPU Clusters to API Calls

Infrastructure layers behind modern AI β€” how training and inference pipelines differ (Day 3)

πŸ—“ Date: March 5, 2026

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How Large Language Models Actually Work

Tokens, embeddings, transformers (Day 2)

πŸ—“ Date: March 3, 2026

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What Is AI? A DevOps Engineer's Mental Model

ML vs AI vs DL vs GenAI β€” cutting through buzzwords with infrastructure metaphors (Day 1)

πŸ—“ Date: March 2, 2026

Want Pro plan for Lifetime at 50% off ? You are in luck , 1 slot still available for 50% membership, use the code below:
(Apply discount code: SpecialMember50POff ):
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πŸ’‘
Other Completed Series for Cloud & DevOps Engineers (FREE):
1) 60 Days of DevOps
2) 30 Days of MLOps
3) 30 Days of AWS (out of 90 Days of Cloud)

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