Tag: #ai-platform
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 51 posts
Vibe Coding and the 2026 AI Development Tool Ecosystem: Lights and Shadows of the Productivity Revolution
Analyzes the reality of the Vibe Coding concept proposed by Andrej Karpathy one year later. Covers the 2026 AI coding tool ecosystem, productivity data, limitations, and strategies engineers should prepare.
2026-03-14 · 28 min read #vibe-coding#ai-tools#developer-productivity#ai-platform#trend-analysisAI Agent Multi-Agent Orchestration Patterns: A Practical Guide to Hierarchical, Pipeline, and Swarm Architectures
From single agents to multi-agent collaboration — design principles for hierarchical, pipeline, and swarm patterns with hands-on implementations using LangGraph, CrewAI, and AutoGen.
2026-03-14 · 25 min read #ai-platform#ai-agent#multi-agent#orchestration#workflowStaff Engineer Technical Leadership and Influence Expansion Strategy
A comprehensive guide covering Staff/Principal Engineer role definitions, technical decision-making (RFC/ADR), influence expansion, mentoring, tech debt management, and engineering culture building for senior+ engineer c
2026-03-14 · 12 min read #ai-platform#staff-engineer#technical-leadership#career-growth#engineering-cultureLLMOps Platform Architecture Guide: Model Deployment, Monitoring, and A/B Testing
A comprehensive guide to designing and implementing an LLMOps platform. Covers vLLM/TGI-based model serving, token usage/latency/quality monitoring, prompt version management, A/B testing framework, guardrail integration
2026-03-13 · 14 min read #ai-platform#llmops#model-serving#monitoring#ab-testingKServe Model Serving Complete Guide: InferenceService, Canary Deployment, Transformer, and InferenceGraph Production Operations
Covers Kubernetes-based model serving with KServe. Model deployment with InferenceService CRD, safe rollouts with Canary strategy, pre/post-processing pipelines with Transformer, and DAG-based composite inference with In
2026-03-12 · 17 min read #ai-platform#kserve#model-serving#kubernetes#inference-graphFeature Store Design and Operations Guide: Building Online/Offline Stores with Feast and ML Feature Pipeline Automation
A comprehensive guide covering Feature Store core concepts (Online/Offline Serving, Feature Freshness, Point-in-Time Correctness), Feast architecture, feature definitions and entity design, materialization pipelines, Onl
2026-03-12 · 13 min read #ai-platform#feature-store#feast#mlops#online-storeKubeflow Pipelines ML Workflow Orchestration Practical Guide: From KFP v2 SDK to Production Deployment
A practice-focused guide to ML workflow orchestration with Kubeflow Pipelines. Covers KFP v2 SDK architecture, pipeline component writing, caching strategies, Argo Workflows/Airflow comparison, and failure response for p
2026-03-11 · 13 min read #ai-platform#kubeflow#mlops#pipeline-orchestration#kubernetesComplete Guide to MLflow Experiment Management: Experiment Tracking, Model Registry, and Deployment Pipeline
A production-focused guide to MLflow covering experiment tracking, model registry, and deployment pipelines. From Tracking Server architecture to auto-logging, model versioning, and Kubernetes/Docker deployment strategie
2026-03-11 · 13 min read #ai-platform#mlflow#experiment-tracking#model-registry#mlopsComplete Guide to Building a Feature Store: Feast Architecture, Online/Offline Serving, and ML Pipeline Integration
A deep dive into the Feature Store, a core ML infrastructure component. Covers Feast framework architecture and implementation, online/offline feature serving, feature engineering pipeline integration, comparative analys
2026-03-10 · 12 min read #ai-platform#feature-store#feast#mlops#ml-pipelineRay Serve Model Serving Platform Building Guide — Autoscaling, Multi-Model, and Production Deployment
A comprehensive overview of Ray Serve architecture, LLM model serving deployment, autoscaling, multi-model patterns, and KubeRay operations with practical code examples.
2026-03-09 · 26 min read #ai-platform#ray-serve#model-serving#kuberay#mlopsComparing LLM Production Monitoring Platforms: A Practical Operations Guide for LangSmith, LangFuse, and Arize Phoenix
A comprehensive comparison guide of three LLM production monitoring platforms (LangSmith, LangFuse, Arize Phoenix). Covers trace collection, prompt version management, evaluation pipelines, cost monitoring, quality dashb
2026-03-09 · 23 min read #ai-platform#llm-monitoring#langsmith#langfuse#arizeWeights & Biases (W&B) Experiment Management Practical Guide: From Experiment Tracking to Model Registry and Production Monitoring
A practical guide to ML experiment management with Weights & Biases (W&B). Covers experiment tracking, Sweeps hyperparameter tuning, Artifacts version management, Model Registry, and team collaboration with code examples
2026-03-08 · 31 min read #ai-platform#wandb#experiment-tracking#model-registry#mlopsOpen-Source Real-Time Conversational Voice Chatbot Building Guide: Barge-In Architecture and Implementation
A comprehensive guide to building real-time voice chatbots using only open-source tools. Covers barge-in implementation with Silero VAD, faster-whisper, Ollama, and Piper TTS pipeline, state machine design, Python exampl
2026-03-08 · 26 min read #ai-platform#voice-chatbot#barge-in#realtime-audio#sttNVIDIA Triton Inference Server Production Guide: GPU Model Serving Optimization Strategies
A guide to GPU model serving optimization with NVIDIA Triton Inference Server. Covers Dynamic Batching, Model Ensemble, TensorRT integration, multi-model serving, Kubernetes deployment, performance profiling, and product
2026-03-08 · 29 min read #ai-platform#triton#inference-server#gpu#model-servingMLflow Production Guide: Experiment Tracking, Model Registry, and Scalable MLOps Workflow
A comprehensive guide to MLflow covering experiment tracking at scale, model registry lifecycle management, CI/CD integration, PostgreSQL and S3 backend configuration, multi-team collaboration, and production deployment
2026-03-07 · 15 min read #ai-platform#mlflow#experiment-tracking#model-registry#mlopsForward Deployed Engineer Career Guide: The fastest growing problem-solving engineer job in the AI era
The actual role of a Forward Deployed Engineer (FDE), differences from general software engineers/solution architects, required competencies, career growth path, and 90-day preparation roadmap are summarized based on the
2026-03-07 · 7 min read #ai-platform#forward-deployed-engineer#career#llm#enterprise-aiFeast Feature Store Practical Operation Guide: From feature engineering to real-time serving and learning-serving skew prevention
A comprehensive guide that covers Feast Feature Store architecture, offline/online store design, feature definition and entity management, real-time serving pipeline construction, training-serving skew prevention strateg
2026-03-07 · 28 min read #ai-platform#feast#feature-store#feature-engineering#mlopsKubeflow Pipelines v2 ML Workflow Automation and Operations Guide
From KFP v2 architecture to building ML pipelines with the KFP SDK, caching, artifact management, CI/CD integration, and production troubleshooting.
2026-03-06 · 13 min read #ai-platform#kubeflow#ml-pipeline#mlops#2026-03ML Model Monitoring and Drift Detection: Evidently AI + MLflow Production Operations Guide
A comprehensive guide covering production monitoring pipeline construction with Evidently AI and MLflow, data/concept drift detection, automatic retraining triggers, and operational troubleshooting.
2026-03-06 · 22 min read #ai-platform#model-monitoring#drift-detection#evidently-ai#mlflowMLflow 2.x Experiment Tracking and Model Registry Operations Guide
A practical guide from MLflow 2.x experiment tracking design to model registry operations, artifact management, CI/CD integration, multi-tenancy, and production deployment.
2026-03-05 · 15 min read #ai-platform#mlflow#model-registry#2026-03