Skip to main content
Adam Strojek

Adam Strojek

Tech/People Leader at Semantive

I am a passionate Rust enthusiast with a keen interest in WebAssembly and Generative AI. I hold the AI_Devs3 certification, demonstrating my proficiency in developing AI Agents and LLM-based software. Professionally, I serve as a Python Tech Leader, specializing in creating microservices solutions using asynchronous Python. My expertise spans various frameworks, including Django, FastAPI, Flask, Sanic, and more. I work natively on AWS Cloud and have experience with Docker and Kubernetes.

Recent

MCP is Not Enough: Addressing Security Flaws with a WebAssembly-Based Standard

·11 mins

The rapid proliferation of applications built around Large Language Models (LLMs) has brought a common challenge to the forefront: how do we effectively provide these models with the necessary external context? It’s well understood that LLMs, much like humans, can “hallucinate” or produce incorrect information when operating without sufficient context. We cannot always rely solely on the knowledge embedded within a model, this knowledge may be outdated (due to knowledge cutoffs), limited to publicly available information, and unable to access private or real-time data. These limitations restrict the utility of LLMs. Consequently, all LLM providers offer methods to supplement this, such as Retrieval Augmented Generation (RAG) or tool calling, each with provider-specific implementations.

Crate Kickstart: Essential Tips for Bootstrapping a Rust Project With Modern Tooling

·7 mins

Recently, I was working on the AI_Devs course, which aims to teach how AI agents work and how to create them. I completed all the exercises using the Rust programming language, and during that time, I started developing a common library to group code that could be shared across different subprojects for the course. After finishing the entire course, one file — agent.rs — stood out to me as particularly useful in most of the exercises. This was the initial implementation of my library, AgentAI.