Useful AWS Architectures Production-ready reference architectures for common AWS ML & data workflows
 
https://knowledge.businesscompassllc.com/useful-aws-architectures-production-ready-reference-architectures-for-common-aws-ml-data-workflows/
 
AWS ML architectures can make or break your machine learning projects in production. This podcast covers battle-tested AWS data pipeline designs and machine learning deployment patterns that data engineers, ML engineers, and cloud architects use to build scalable, reliable systems.

SageMaker Lineage & Bedrock Model Evaluation ML provenance tracking & model quality assessment across the lifecycle
 
https://knowledge.businesscompassllc.com/sagemaker-lineage-bedrock-model-evaluation-ml-provenance-tracking-model-quality-assessment-across-the-lifecycle/
 
Tracking machine learning models from training to production gets messy fast, especially when you’re working with foundation models and complex ML pipelines. SageMaker Lineage and Bedrock Model Evaluation solve this chaos by giving you complete ML provenance tracking and model quality assessment throughout your entire development process.

LLM Training & Fine-Tuning LoRA, Adapters, RLHF, and AWS Bedrock/SageMaker strategies
 
https://knowledge.businesscompassllc.com/llm-training-fine-tuning-lora-adapters-rlhf-and-aws-bedrock-sagemaker-strategies/
 
Large language model optimization has become essential for building AI applications that actually work for your business. This podcast is designed for ML engineers, data scientists, and AI developers who want to master LLM training techniques without breaking their compute budget or timeline.

Prompting Strategies Guide Interactive comparison of LLM prompting techniques
 
https://knowledge.businesscompassllc.com/prompting-strategies-guide-interactive-comparison-of-llm-prompting-techniques/
 
Getting the most out of large language models comes down to one thing: how you ask. This podcast breaks down the essential prompt engineering best practices that separate amateur users from power users who consistently get exceptional results.

Bedrock Guardrail Concepts Capabilities, custom filtering, and full observability
 
https://knowledge.businesscompassllc.com/bedrock-guardrail-concepts-capabilities-custom-filtering-and-full-observability/
 
Amazon Web Services Bedrock Guardrails give developers and AI teams the tools they need to build safer, more reliable AI applications. If you’re working with large language models or building AI-powered products, you need robust AI content filtering and monitoring systems that protect your users and your business from potential risks.

MCP Server Architecture Model Context Protocol — How AI apps connect to the world
 
https://knowledge.businesscompassllc.com/mcp-server-architecture-model-context-protocol-how-ai-apps-connect-to-the-world/
 
AI applications need a bridge to connect with real-world data and services, and that’s exactly what MCP Server Architecture delivers through the Model Context Protocol. This podcast is designed for AI developers, software engineers, and technical architects who want to understand how modern AI apps integrate with external systems and data sources.

AWS Agent Stack Strands · Agent Core · Agent Squad
 
https://knowledge.businesscompassllc.com/aws-agent-stack-strands-%c2%b7-agent-core-%c2%b7-agent-squad/
 
AWS Agent Stack Strands, Agent Core, and Agent Squad represent Amazon’s powerful framework for building collaborative AI agents that work together seamlessly. This podcast is designed for cloud developers, AI engineers, and DevOps teams who want to create scalable agent infrastructure and deploy distributed agent systems effectively.

Bedrock RAG: Reranker & Hybrid Search
 
https://knowledge.businesscompassllc.com/bedrock-rag-reranker-hybrid-search/
 
Amazon Bedrock RAG combines powerful reranker technology with hybrid search implementation to transform how AI applications retrieve and rank information. This podcast targets developers, ML engineers, and technical teams building retrieval augmented generation systems who want to optimize their AI search performance beyond basic vector database retrieval.

AWS Bedrock Inference Concepts
 
https://knowledge.businesscompassllc.com/aws-bedrock-inference-concepts/
 
AWS Bedrock makes running AI inference simple by giving you access to powerful foundation models through a single API. This podcast is for developers, ML engineers, and cloud architects who want to understand how AWS Bedrock inference works and start building AI applications without managing infrastructure.

SageMaker Inference Options
 
https://knowledge.businesscompassllc.com/sagemaker-inference-options/
 
Amazon SageMaker offers multiple ways to deploy your machine learning models, each designed for specific use cases and performance needs. This podcast is for data scientists, ML engineers, and developers who want to understand which SageMaker deployment options work best for their projects.