mission-test

Amazon Quick Suite might surprise you in 2026 | Mission

Admin — Wed, 17 Dec 2025 05:00:00 GMT

Dr. Ryan Ries here. I can’t believe I’m writing the last Mission Matrix of 2025. Thank you for tuning in this year. It seriously means a lot to me when I’m at events or when you all reply back to my newsletter with your thoughts on Matrix. Building this newsletter has helped me build new relationships and connect with you all, and I’m very thankful for that.

Now, enough of my sappiness. I want to discuss something that I believe can transform how teams operate next year. A lot of people are still sleeping on it.

How to Get Ahead of AI’s Coming Power Crunch | Mission

Admin — Wed, 10 Dec 2025 05:00:00 GMT

Dr. Ryan Ries here. Lately, I’ve been thinking a lot about the power problem in the AI industry, and I don’t see enough people talking about it.

While this may feel a bit doom and gloom at first, I promise there are solutions your business can (and should) be thinking about today as you’re planning your AI projects. Just keep reading!

Quick sidebar. I am co-hosting a re:Invent recap this Thursday. Register here if you’re interested in hearing about which re:Invent announcements are most important for your business!

Mission & CDW Announce Multi-Product Solutions in AWS Marketplace as Launch Partners | Mission

Admin — Wed, 03 Dec 2025 05:00:00 GMT

VERNON HILLS, IL – DECEMBER 3, 2025 – Mission, a CDW company and U.S.-based AWS Premier Tier Services and ISV Accelerate Partner, and CDW, a leading multi-brand provider of information technology solutions, announced today the availability of 6 integrated multi-product solutions in AWS Marketplace.

Mission and CDW Named 2025 Global AWS Partner Award Finalists | Mission

Admin — Tue, 02 Dec 2025 05:00:00 GMT

Mission recognized as GenAI Global Consulting Partner of the Year finalist; CDW recognized as Marketplace Partner of the Year finalist and Nonprofit Consulting Partner of the Year finalist.

Mission, a CDW Company, Achieves AWS Agentic AI Specialization, Expanding Enterprise AI Capabilities | Mission

Admin — Mon, 01 Dec 2025 05:00:00 GMT

Recognition distinguishes Mission for delivering production-ready autonomous AI systems across enterprise sectors

Building Enterprise AI Agents with Amazon Bedrock AgentCore: Lessons from a Data Migration Chatbot | Mission

Admin — Mon, 24 Nov 2025 05:00:00 GMT

Agentic AI is changing what's possible with generative systems. Early AI workloads centered on content tasks like retrieving information from knowledge bases, summarizing documents, and pattern-based composition. Useful, but limited. Agentic systems reason through complex problems, orchestrate multi-step workflows, and take direct action on backend infrastructure.

Mission recently put this into practice for a global data migration platform provider facing a scaling challenge. Their move from enterprise to mid-market customers required a self-service model that could guide users through intricate migration processes. The support team couldn't keep pace with demand, and scaling by hiring wasn't viable. Domain expertise in complex data migrations takes months to develop, making it impossible to train new support staff fast enough to match customer growth. The process is well documented but couldn't bridge the gap. Users needed an intelligent system that could not only answer questions but validate data, query databases, monitor jobs, and execute workflows.

The answer was an agentic chatbot built on Amazon Bedrock AgentCore, a managed runtime for AI agents. AgentCore took care of infrastructure concerns (security, session management, observability, memory) while our team concentrated on orchestration and agent design. The chatbot queries databases, validates migration data, monitors job status, and executes multi-step workflows.

This blog article walks through the architecture, technical decisions, and patterns that shaped the solution.

What is Amazon Bedrock AgentCore? AI Agent Platform for Enterprise Deployment

Admin — Fri, 21 Nov 2025 05:00:00 GMT

Most AI agents never make it to production. The problem usually isn't the agent—it's the infrastructure.

Frameworks make it straightforward to create agents that reason, use tools, and automate workflows. But getting those agents into production reveals a hard truth: agents need infrastructure that traditional applications don't.

Session isolation to prevent data leakage. Persistent memory across conversations. Identity management for third-party services. Tool connectivity at scale. Observability into autonomous decisions. Building this infrastructure from scratch means months of engineering work replicating what cloud providers already perfected.

Amazon Bedrock AgentCore provides that infrastructure. Released to general availability in October 2025, it delivers seven fully-managed services purpose-built for production agents: runtime, memory, identity, gateway, code interpreter, browser tool, and observability. With over one million SDK downloads, AgentCore has become the platform that moves agents from prototype to production.

AI Coding Tools vs. Reality | Mission

Admin — Fri, 14 Nov 2025 05:00:00 GMT

Dr. Ryan Ries here. I just spent weeks testing every AI coding platform I could get my hands on.

I’m not surprised to say that I’m a bit disappointed. Let's just say the marketing promises and the actual reality exist in completely different universes.

Amazon Bedrock AgentCore GA: Building Production-Ready AI Agents at Enterprise Scale | Mission

Admin — Thu, 06 Nov 2025 05:00:00 GMT

Back in July, AWS announced Amazon Bedrock AgentCore, a collection of integrated services designed for developing, deploying, and operating AI agents securely at scale. The launch in July was a preview, tailored to customers and partners developing at the leading edge. To Amazon's credit, their customer and partner obsession is incredibly influential as they launch and iterate on services.

How Does AI Evaluate NFL Trade Decisions? | Mission

Admin — Wed, 05 Nov 2025 05:00:00 GMT

Dr. Ryan Ries here in your inbox for this week’s Matrix. In honor of yesterday being the 2025 NFL trade deadline, I thought we’d try something different.

I took 3 of the 8 trades that happened yesterday and asked ChatGPT, Gemini, and Claude to analyze them. Same questions, same order, no context sharing.

I was curious how these different AI systems reason through ambiguous, subjective problems where there’s no single “right” answer. And sports trades are perfect for this!