Slides and material

AWS Community Day Romania

The Romanian community day in Timișoara.

aws-community.ro

On the programme

From MacBook to Bedrock: Lessons from Building an AI Assistant

2025 · Timișoara

With Philipp Bergsmann. Prototyping a GenAI assistant on a laptop and scaling it to a production workflow on Amazon Bedrock.

Under the session

The services doing the work

Read off the slides, not guessed. Each card says what that service did in this build, and links to the page explaining the capability and how to run it somewhere else.

InstructLab

InstructLab

The open-source pipeline behind the fine-tune: documents become Q&A pairs in YAML, synthetic data is generated from them, then the adapter is trained with LoRA. Model-agnostic, and it ran on a laptop.

Your own model
Amazon Bedrock

Amazon Bedrock

The workstation. Claude Sonnet 3.7, Amazon Nova Pro and the custom model are all served from one place.

Foundation models
Amazon Bedrock Custom Model Import

Amazon Bedrock Custom Model Import

Serves the fine-tuned Llama 3.1 3B as the UG Specialist, so the trained model needs no cluster of its own.

Your own model
CrewAI

CrewAI

Runs the crew: Q&A agent, agenda producer, header generator, speaker finder, GitHub planner and the UG Specialist.

AI agents
AWS App Runner

AWS App Runner

Runs the agent container. The whole system came to about 30 euros a month.

Serverless compute
Amazon ECR

Amazon ECR

Holds the container image App Runner pulls.

Object storage
Amazon S3

Amazon S3

Stores the trained model before Bedrock imports it.

Object storage
Llama 3.1 3B

Llama 3.1 3B

The open-weights base model that became the UG Specialist, adapted with LoRA rather than retrained.

Your own model
Amazon Nova Pro

Amazon Nova Pro

The agent model, and the teacher that generated the synthetic training data.

Foundation models
Claude Sonnet 3.7

Claude Sonnet 3.7

Answers the open questions in the Q&A agent.

Foundation models
Red Hat OpenShift AI

Red Hat OpenShift AI

The alternative to training on a Mac: the same run as a Jupyter environment or an OpenShift pipeline.

Your own model

Go deeper

The longer write-ups

Where the builds behind these sessions are explained properly.

From AI Demo to Enterprise Solutions

The longer write-up: the build, the services and what it costs to run.

Enterprise AI Consultant vs. AI Consultant

The longer write-up: the build, the services and what it costs to run.

What is an AWS Community Day?

The longer write-up: the build, the services and what it costs to run.

10 Years of AWS User Group Vienna

The longer write-up: the build, the services and what it costs to run.

Work with me

Bring one of these into your own room

Every session here can be given as a conference talk, a company workshop or an internal briefing. Most started as a real project rather than as a slide deck.

Talks and moderationWorkshopsBook 30 minutes

Sources

Where all of this comes from

Every claim on this page traces back to the deck, the recap or the event's own site.

  1. aws-community.ro, the event's own site
  2. Slides: From MacBook to Bedrock: Lessons from Building an AI Assistant, 2025
  3. Recap: From MacBook to Bedrock: Lessons from Building an AI Assistant, 2025
  4. From AI Demo to Enterprise Solutions
  5. Enterprise AI Consultant vs. AI Consultant
  6. What is an AWS Community Day?
  7. 10 Years of AWS User Group Vienna

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