Featured
Meet Sed: Sedai's New AI Assistant Brings Conversation (and Action) to Cloud Optimization
Introducing Sed and Sedai's MCP integration: ask questions, take action, and extend it into your own agents.
Read more
All Posts
AllAIAWSAzureCloud StrategyCompany NewsEngineering IdeasFinopsGPUGoogle CloudKubernetesTechnical Guides
Introducing the IaC Mapping Agent
Sedai has always been able to find the right optimization. Now it can eliminate IaC drift at the same time.
What is AI Agent Optimization?
Learn about AI agent optimization, how it works, and which teams own it in production. The complete breakdown for platform and FinOps teams.
How Much Isolation Do AI Agents Actually Need?
AWS, Microsoft, Google, and Anthropic all isolate AI agent sessions differently. Sedai's engineering leaders weigh in on how much isolation agents really need.
What Is AI Tokenomics?
AI tokenomics is the governance of how token consumption connects to cost and business outcomes. Three layers, six operational controls, and why most governance stops at the wrong one.
Sedai Extends Autopilot for VM and Amazon RDS Optimization
Sedai Autopilot now covers VMs and RDS — autonomous, incremental rightsizing with maintenance window controls and RL-based safety guardrails.
Tokenmaxxing Is Ending. The Era of AI Tokenomics Has Begun
Token consumption was never the right metric. Here's why enterprise AI budgets are exploding and what to measure instead.
AI Failed the Human Test. Should We Be Surprised?
Engineering leaders on why AI agents scored 0% on the ALE benchmark's hardest tier — and what that means for deploying agents today.
Automated vs. Autonomous Cloud Operations
Automated systems execute pre-defined rules. Autonomous systems adapt when conditions change. Here's what that means for cloud operations teams.
Top Strategies for Google Dataflow Cost Optimization in 2026
Google Dataflow is a powerful tool for processing large-scale data, but its costs can quickly add up without proper management. Optimizing Google Dataflow costs is crucial for organizations looking to maximize the value of their data processing pipelines while minimizing expenses.Cost optimization involves a combination of strategies, techniques, and best practices that help users effectively manage and reduce the costs associated with running Dataflow jobs. By understanding the factors that influence Dataflow pricing and implementing targeted optimizations, organizations can significantly improve their cost efficiency and overall return on investment.