A team shipped a vibe-coded Lambda function last month. Claude generated it, the tests passed, and it went to production. Two days later, the function
A team I worked with ran their entire product on Claude 3.5 Sonnet. Every request – from simple classification to complex document analysis – hit
Anthropic ran a public red teaming exercise against their Constitutional Classifiers system via HackerOne, offering up to $15,000 to anyone who could find a universal
Six months ago, picking an agent framework felt like choosing a JavaScript framework in 2016 – new options every week, each claiming to be the
A team I advise spent three months migrating their Java microservices to Graviton3. They finished in November 2025. Two weeks later, AWS announced Graviton4 with
If you want to build a production-grade voice agent, there are some things you will need: A way to connect phone networks. Speech-to-text processing. Understanding
Your healthcare AI chatbot passed security review. It has Amazon Bedrock guardrails configured to block PII and sensitive medical topics. The web client connects directly
AWS just released a new certification: Certified Generative AI Developer – Professional. If you work with GenAI on AWS or plan to, this exam outline
Werner Vogels stepped on stage for what he announced would be his final re:Invent keynote after roughly 14 years. After more than a decade of
Two quotes land on your desk for the same feature set. Both list similar features and both mention AI in their process. One includes architecture
OpenAI just launched ChatGPT Atlas on October 21, 2025, a browser that brings AI-powered assistance directly into your web experience. There’s one catch: it’s macOS-only
You’re working through a CodeCrafters challenge, making real progress, and suddenly realize something frustrating: all your work lives in a private remote repository that CodeCrafters
Your stakeholder asked a reasonable question: “Will the AI system learn from our users and improve over time?” You said yes, because that sounds right.
Consider a typical scenario: A compliance team processes 10,000 transactions in a month. They flag 847 for manual review. Analysts spend three weeks investigating. They
Your AI model needs to run closer to users. Latency from round-tripping to us-east-1 kills the user experience. You investigate AWS edge options and find
Your AI model runs great on a GPU instance in development. You deploy to production. Then finance asks why you’re spending $15,000/month on compute when
Your AI model works perfectly in development. You deploy it to production. Three weeks later, your AWS bill arrives and SageMaker costs are 4x what
You have a model. You need to deploy it on AWS. You ask which service to use and get three answers: SageMaker, Bedrock, or Lambda.
