Workshops

What a student is expected to learn:

Deploy First Mentality:

We begin to focus on service design with a focus on the ability to maintain, manage, and debug the service in Kubernetes.

• Design Philosophy, Guidelines, What to Expect
• Project Layers, Policies, and Guidelines
• Prepare Project

Domain-Driven, Data-Oriented Architecture:

We talk about the data-driven, data-oriented architecture. We discuss the design philosophy, guidelines, and semantics of how the three layers of App, Business, and Storage work together.

• Architecture Review
• Applying and Implementing Firewalls
• Data Flow Trust vs Non-Trust
• Data Shaping and Data Validation
• Developer Isolation with Domains
• Extending Functionality through Composition

What a Student Is Expected to Learn

By the end of this workshop, you'll leave with working code, a production-ready mindset for AI-powered Go applications, and hands-on experience across the full stack: retrieval, action, performance, and security. 🚀

Part 1: Ground It — Retrieval-Augmented Generation (RAG) in Go

• Understanding RAG Concepts – Improve responses by dynamically retrieving relevant context rather than relying solely on static training data.
• Ingesting and Processing Documents – Build pipelines to index and retrieve documents from client systems.
• Interacting with AI-Compatible APIs – Learn how Go applications can connect to local inference engines, OpenAI-compatible servers, or cloud AI services.
• Optimizing Performance & Latency – Implement caching, batching, and parallel processing to enhance efficiency.
• Using Vector Databases – Store and search embeddings with tools such as Chroma, Pinecone, Weaviate, Milvus or pgvector in PostgreSQL.

Part 2: Make It Act — Tool Calling, Function Execution & MCP in Go

• How AI Uses Tool Calling – Enable external system control by allowing AI to invoke predefined functions in Go.
• Building Function Calls with OpenAI-Compatible Systems – Define structured function inputs and outputs for AI-driven interactions.
• Connecting to External APIs & Databases – Trigger real-world actions, query databases, and automate workflows.
• Handling Responses & Errors – Ensure safe and reliable execution of AI-invoked functions.
• Introduction to the Model Context Protocol (MCP) – Understand how MCP standardizes the way models discover and invoke tools. Build a simple MCP server in Go that exposes tools to any MCP-compatible client, showing how it compares to direct function calling.

Part 3: Make It Fast — Advanced Optimizations

• Speculative Decoding – Use a smaller draft model alongside a larger verification model to get near-large-model quality at small-model speeds. Applicable to both local inference libraries and serving engines that support it natively.
• Automatic Prefix Caching & KV Cache Reuse – Structure multi-turn conversations so shared prefixes (system prompts, conversation history) are cached and reused across requests, avoiding redundant computation. Manage message arrays carefully to keep prefixes stable across turns.
• Semantic Caching – Embed user queries and check vector similarity against cached query-response pairs, returning cached answers for semantically equivalent questions without running inference — implementable in Go with any embedding model or API.
• Adaptive Retrieval – Use a lightweight classifier or a small local model to decide whether RAG context is needed at all, avoiding irrelevant context injection that can degrade response quality.
• Cascading Model Routing – Route queries to different models based on complexity: a fast small model for simple questions, escalating to a larger model only when confidence is low, implemented as Go middleware.

Part 4: Lock It Down — Securing LLM-Powered Go Applications

• Prompt Injection Defenses – Understand direct and indirect prompt injection attacks, and implement role separation, input sanitization, and detection strategies. Demonstrate how injected instructions in user input or retrieved documents can hijack model behavior.
• Securing Tool Calls – Apply least-privilege principles to exposed functions, prevent command injection from model output, and enforce authorization checks before execution.
• RAG Pipeline Security – Guard against data poisoning and indirect injection via ingested documents. Show how a malicious document in the vector DB can manipulate retrieval results and model responses, and defend with access controls, relevance thresholds, and content isolation.
• Output Sanitization & Exfiltration Prevention – Sanitize model-generated content before rendering in web UIs to prevent XSS. Defend against data exfiltration where the model encodes sensitive retrieved data into tool call arguments targeting attacker-controlled endpoints, using domain allowlists and egress filtering.
• Chain-of-Call Escalation – Show how a model can chain multiple tool calls in a single turn to escalate privileges. Implement call budgets, supervision layers, and human-in-the-loop checkpoints in Go.

Meet the zero-kb02

The zero-kb02 isn't just a simple keypad — it's a powerful, programmable controller designed for versatility. You'll be building and coding with:

• Brain: Powered by the RP2040 microcontroller
• Controls: 12 keys for your favorite shortcuts
• Interaction: A Joystick and a Rotary Encoder for intuitive navigation
• Visuals: An OLED Display and RGB LEDs to show status and add flair

Endless Possibilities with TinyGo

Beyond a simple keypad, the zero-kb02 is a gateway to embedded development. With the extensive documentation and the power of TinyGo, you can transform it into:

• Musical Instruments: Create a buzzer-based synth or a MIDI controller
• Gadgets: Build a weather station using I2C sensors and the OLED display
• Gaming: Run 2D games using koebiten (a TinyGo-friendly subset of Ebitengine)
• Fully Customizable Keyboard: It's Vial-compatible, allowing you to remap keys and change settings directly from your web browser

Morning: Soldering Workshop

You'll assemble your own zero-kb02 from scratch — soldering the RP2040 microcontroller, keys, joystick, rotary encoder, OLED display, and RGB LEDs. Expert staff will guide you through every step.

Afternoon: Programming with TinyGo

With your macropad assembled, you'll bring it to life with TinyGo firmware. Learn how to program key mappings, control the OLED display, drive RGB LEDs, and read the joystick and rotary encoder — all in Go. By the end of the day, you'll leave with a custom keyboard that you built and programmed yourself.