Mission Cloud

Your agents probably don't need as much GPU as you think 🤔

Most teams building agents on AWS default to GPU. On October 15, Dr. Ryan Ries and Marty Neuhard trace a real agentic AI request from start to finish to show where the compute actually lands.

The answer changes how you architect, size, and budget for agents.

Save your seat 👉 https://hubs.ly/Q04ywDMG0

Your AI idea is either a green light or a waste of six months. Tomorrow you find out which. 🎯

If you've got an AI idea you're not sure is worth building, this is your shot to find out for real. Dr. Ryan Ries is running a live, interactive session on how to find, score, and prioritize your best AI opportunities, and he's evaluating submitted ideas live, on the spot.

Still have time to submit yours when you register, or drop it in the chat tomorrow during the session.

Register here: https://hubs.ly/Q04xfYVH0

Here's what makes this session different: nobody's using a hypothetical example.

Attendees submit their own AI ideas ahead of time, or drop them in the chat during the session. Dr. Ryan Ries picks one and scores it live, on the spot, walking through his exact reasoning in real time.

You'll see the framework applied to a real idea, then leave ready to run it on every idea on your list.

One week out. Grab your spot.

Register here: https://hubs.ly/Q04xfVHf0

When your AI agent remembers something, who is it remembering it for?

That's not a small detail once multiple agents, users, or projects start sharing the same memory store — and getting it wrong means one instructor's house style, one client's data, or one session's context bleeding into somewhere it shouldn't.

Mission Cloud's latest post breaks down four lessons learned building production AgentCore systems, including how namespace-based memory scoping keeps context properly walled off by actor, project, or compliance tier, no custom access-control layer required.

This is the kind of lesson you only learn after building past the demo stage

Read it here 👉 https://hubs.ly/Q04x5K3-0

The math behind Amazon Bedrock simply speaks for itself, according to our own Dr. Ryan Ries.

If your organization has committed AWS spend through a Private Pricing Agreement, migrating to Bedrock is a no-brainer.

Learn more ➡️ https://www.crn.com/news/ai/2026/amazon-bedrock-economics-and-aws-cost-savings-fueling-ai-workloads-mission-cloud-s-ai-leader

Not all AI ideas deserve your time. Here's how to tell which ones do.

Every team has a running list of AI ideas. Most never get built, not because they're bad, but because nobody has a clear way to weigh them against each other.

Dr. Ryan Ries breaks it down to two questions: how much impact would this actually have, and how hard would it be to build. That's it. That's the whole test for separating a quick win from a resource sink.

He'll walk through the full method live, then apply it to real ideas from the audience in real time.

Register here: https://hubs.ly/Q04w6LkF0

Every AI vendor you add outside your AWS environment becomes a new relationship to contract, audit, and re-approve every year.

Bedrock solves this by staying inside AWS's already authorized environment. FedRAMP, BAA, SOC2... Years of audit work already done!

Check out the full story on CRN ➡️ https://www.crn.com/news/ai/2026/amazon-bedrock-economics-and-aws-cost-savings-fueling-ai-workloads-mission-cloud-s-ai-leader

Got an AI idea sitting in a doc somewhere?

Most teams have more AI ideas than they know what to do with, and no clear way to tell which ones are worth building versus which ones stall out as another pilot that goes nowhere.

Join Dr. Ryan Ries for a live, interactive session on how to find, score, and prioritize your best AI opportunities. Submit your idea when you register (or drop it in the chat) and Ryan will evaluate it live, on the spot, using the same framework he's about to teach you. Walk away with a framework you can reuse on every AI idea you have, not just the one that gets the spotlight.

Register here: https://hubs.ly/Q04tD7hZ0

There's a compute decision most teams aren't even putting on the table.

We're a few days out from Agentic AI on CPU: Efficient, Scalable, Accessible in Seattle, and seats are going fast. Mission Cloud, AWS, and AMD are bringing the full stack view: 5th Gen AMD EPYC "Turin" processors, the AWS Nitro System, model selection, and how Cloudamize is building agentic workflows into a live platform today.

This is a working session, not a keynote. Come with real workload questions.

If you're planning to join us Thursday, now's the time to lock in your spot.

👉 https://hubs.ly/Q04tFWP00

Everyone assumes GPUs are non-negotiable for agentic AI. AMD and AWS are proving otherwise.

Join AWS, AMD, and Mission Cloud in Seattle for Agentic AI on CPU: Efficient, Scalable, Accessible. We're bringing together the people building this shift from the chip up: 5th Gen AMD EPYC "Turin" processors, the AWS Nitro System, and the model and orchestration decisions that make CPU-based agent pipelines actually production-ready.

You'll hear directly from AMD and AWS on the hardware, plus a look at how Cloudamize is embedding agentic workflows into a live analytics platform.

📅 August 27th, 8:30 AM - 12:30 PM PDT
📍 Seattle, WA
Reserve your seat: https://hubs.ly/Q04tfQym0