Tag: faang

Hiring at scale in industries such as retail, logistics, hospitality, and others has its fair share of challenges. Recruiting teams are expected to fill hundreds of roles within tight timelines, often with limited capacity and with tools that weren’t designed to seamlessly work together. As a result of this, applications pile up, phone screens get …

Read more “Reduce time-to-hire for quality candidates with AI-powered Amazon Connect Talent”

At Orange, the leading France-based multinational telecom provider, there are days when engineering teams set aside their delivery backlogs and spend the day cleaning up cloud spend together. There’s a leaderboard. There are goodies on the line. Experienced practitioners guide the newcomers, so people learn the work while doing it. By the end of the …

Read more “How Orange built FinOps accountability, and why agents are next”

AI agents built on foundation models (FMs) often misapply healthcare and life sciences (HCLS) decision frameworks, even when they’ve seen the guidelines in training and in the system prompt. Ask an agent to classify a TP53 missense variant using ACMG/AMP criteria. It will cite the correct framework but misapply evidence categories, skip population frequency thresholds, …

Read more “Improving HCLS AI reasoning with open-source agent skills”

Welcome to the first Cloud CISO Perspectives for September 2026. Today, Sandra Joyce shares the latest details on Google’s visibility into how attackers are using AI, and how we’re using AI to stop them. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog. If you’re reading …

Read more “Cloud CISO Perspectives: How Google monitors AI threats and advances AI defenses”

Prompt caching in Amazon Bedrock can reduce your input token costs by up to 90 percent when you repeatedly send the same context to foundation models, based on Amazon Bedrock prompt caching pricing. Without caching, a 10,000-token contract sent alongside 50 user questions means 500,000 input tokens billed at full price for content the model …

Read more “Optimizing cost and latency with Amazon Bedrock prompt caching”

AI agents now run in production at a scale of billions of operations a day, and a recurring architectural pattern has surfaced: agents need a compute scratch pad. Not only for coding tasks, but for data aggregation, analysis, verification, and any workflow where semantic reasoning alone isn’t enough. Abnormal AI, a behavioral security service that …

Read more “Abnormal AI: Amazon Bedrock AgentCore for agentic email security at scale”

Multi-agent systems in production experience issues in ways that traditional monitoring misses. For example, the agent can’t invoke its foundation model (FM) and returns an empty response. This could be because of a missing AWS Identity and Access Management (IAM) permission on an agent’s execution role that doesn’t throw a 500 error. A supervisor agent …

Read more “Monitoring production agent lifecycle with AWS DevOps Agent and AgentCore Evaluations”