Key Takeaways from AWS Community Day Baltic 2025: Attendee Insights
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Attending AWS Community Day Baltic 2025 on September 10th was a delightful experience. This community‑driven, full‑day event featured practical sessions, real‑world use cases, and numerous hallway conversations, allowing builders from across the region to share their experiences. As a community conference, AWS Community Day exists to amplify practitioner knowledge, foster peer learning, and turn ideas into production‑grade decisions - prioritizing substance over show.
The first session I attended was “Model Context Protocol (MCP): From Zero to Hero,” which covered the essentials of building and running agents with MCP. MCP is an open standard that defines how AI systems connect to tools, data, and environments, simplifying integration and reducing glue code. The speaker, Viktor Vedmich, Senior Developer Advocate at AWS, delivered real‑life examples and quick demos that fit naturally into daily workflows. A memorable framing was: MCP is to LLM what REST is to the Web. The session also highlighted AWS’s role in MCP tool chaining, emphasizing Strands Agents and Bedrock AgentCore as emerging building blocks for agentic systems at scale. For deeper dives, see the links in the original draft.
Key takeaways
MCP standardizes tool access for agents, enabling safer, composable integrations.
Strands Agents and Bedrock AgentCore accelerate agent orchestration in AWS environments.
https://aws.amazon.com/bedrock/agentcore/
https://strandsagents.com/latest/
To pivot from AI orchestration to data fundamentals, I next attended “DynamoDB Demystified – Core Features & the Single‑Table Design,” led by Asia Chojnacka, Senior Software Engineer & Cloud Community Leader at Capgemini (AWS Community Builder), and Szymon Sołtys, Senior DevOps Engineer at Transition Technologies (AWS Community Builder). Although they noted it was their first AWS event talk, the delivery was confident and well‑structured. The session was split into DynamoDB essentials and an approachable walkthrough of Single‑Table Design (a modeling strategy that consolidates multiple entities into one table using partition/sort keys and access patterns). With prior DynamoDB experience, the second part was especially valuable: practical partition/sort key strategies, a disciplined query‑over‑scan mindset, and techniques for managing schema evolution without sacrificing read efficiency. The most important takeaway: if Single‑Table Design is not well understood, resist adopting it prematurely despite its potential benefits.
Key takeaways
Model around access patterns first; design keys to answer the most frequent queries.
Single‑Table Design pays off only when the team is proficient with its trade‑offs.
Building on the agentic foundation from the morning, I attended “Build → Ship → Scale,” presented by Viktor Vedmich, a Senior Developer Advocate. The session focused on moving from a first working agent to orchestrated multi-agent systems with guardrails and observability on AWS. It naturally continued themes from the MCP session, showing how Strands Agents and Bedrock AgentCore support real production workflows. Multi‑agent infrastructure is rapidly becoming a standard approach for enterprise LLM usage.
After a lunch break, I attended “Self‑Healing Data Platforms – 3A’s: Automation, AI, and Alignment,” presented by Przemysław Mikulski, the Co-Founder and Cloud & Data Architect at Kodlot ApS. The session emphasized using automation to reduce MTTR, AI-assisted anomaly detection, and cross-team alignment. Real-life examples showing a significant reduction in incident volume provided impressive evidence of AI's importance in Data Platform monitoring. The session was highly expert-level, so domain experts could truly benefit from the insights shared.
Continuing into operations, I attended “There Are No Magic Tricks in Cloud Cost Optimization,” led by Martin Hauskrecht, Head of Engineering at Labyrinth Labs. The session emphasized building lasting FinOps habits rather than relying on quick fixes. It highlighted design-for-cost, unit economics, strict tagging, and continuous measurement as the foundation for sustainable savings. Unfortunately, the session was quite short and focused only on Kubernetes and database cost optimization. I was hoping for more insights into serverless. The key lesson learned: To reduce costs, you first need accurate information obtained through observability.
To translate concepts into practice, I participated in the workshop “Agentic AI with MCP and Strands SDK,” led by Szymon Kochański, a Senior Solutions Architect at AWS. The session covered everything from MCP basics to building Strands-based agents using tools, memory, and simple orchestration patterns. The hands-on format and step-by-step labs made it easy to continue the work after the event. It was my favorite session at the conference. I was impressed by how easy it was to use Strand Agents and their powerful usage patterns. The most impressive example? A multi-agent app with multiple tools that makes HTTP requests, saves data to OpenSearch, commits changes in the source code, and even creates new tools from just a user prompt! Want to try it? Here’s the link:
https://catalog.workshops.aws/strands/en-US
The last session I attended was “The Engineering Mindset in the Age of AI: Beyond Vibe Coding.” This talk contrasted prompt-first “vibe coding” with an engineering mindset focused on invariants, guarantees, and clear system design around probabilistic components. The session advocated for clear interfaces, considering failure modes, and measurable outcomes—treating AI assistance as a component to be constrained and evaluated, not a replacement for engineering rigor. It also outlined practical principles for senior developers to balance speed with safety, moving from exploratory generation to intentionally designed, testable systems. I was personally amazed by the talk. Gunnar Grosch—Principal Developer Advocate at AWS—perfectly explained all the benefits and challenges of current AI-powered development work. I now believe that AI is like the steam engine in the late 19th century. It won't reduce developers' work; it will help us in our daily tasks with a brand-new toolset. Have you heard of Jevons Paradox?
https://simple.wikipedia.org/wiki/Jevons_paradox
AWS Community Day Baltic 2025 delivered a balanced mix of foundational concepts and advanced practices across agentic AI, data platforms, and cloud operations. The through‑line across sessions was disciplined engineering: adopt open standards for agents, model data around access patterns, automate detection and recovery, and embed cost visibility from day one. The community format—talks, workshops, and hallway exchanges—made the insights immediately actionable and reinforced that continuous learning is essential in today’s rapidly evolving landscape. Most of all, the event demonstrated that combining principled engineering with modern AI tools yields systems that are not only more capable but also more reliable and economically sound.
MCP: an open protocol that standardizes how AI agents access tools, data, and environments.
Single‑Table Design: modeling multiple entities in one DynamoDB table using partition/sort keys and access‑pattern‑driven schema.
FinOps: a cross‑functional practice aligning engineering and finance to measure, manage, and optimize cloud spend.
