Tags→#ai
Defending your codebase from AI slop: guardrails that keep you in control
Turn coding standards into CI checks with dependency-cruiser, Semgrep, Trivy, crap4ts, and CodeRabbit so AI-written code can't erode your codebase.
The layers of an AI agent product
Model SDK, agent framework, harness, execution runtime, and product: what each layer of an AI agent product does, with real examples of what's under the hood.
I am an AI Engineer
AI Engineer: Hands-on builder turning AI models into production apps. 5 real projects, solid code, no PhD needed.
Understanding the Agentic Commerce Protocol: your guide to selling on ChatGPT
Learn how to integrate your e-commerce store with ChatGPT's Instant Checkout using the Agentic Commerce Protocol. TL;DR guide for developers.
Six pillars of well-architected framework and resilient multi-agent systems
How AWS's Well-Architected Framework applies to AI agent systems. Four proven pillars plus sustainability for building resilient multi-agent swarms.
From 60 to 25 Hours: Practical Tips for Effective AI-Assisted Development
Slash dev time by 60% without sacrificing control. Real strategies to make AI tools work for you, not against you. Stop fighting LLMs and start shipping faster.
Go with SSE for your AI chat app
Comparing SSE and WebSockets for AI chat applications, and why SSE is the better choice for most use cases.
Creating a simple RAG in python with AzureOpenAI and LlamaIndex
Embedding and vectorizing data from PDF documents into Azure Cosmos MongoDB using LlamaIndex. Refactoring tips and querying techniques.
Capture the value of AI without drawing attention to its presence
Leveraging AI for business value: Caterpillar's smart approach to solving real problems without hyping AI, improving service and efficiency.
Creating a Simple RAG in Python with AzureOpenAI and LlamaIndex
Building a Retrieval-Augmented Generation (RAG) system using Python, AzureOpenAI, and LlamaIndex to query PDF documents and get AI-powered responses. Part 1.