AI Regulation
Regulation is important to ensure the safe development of AI and attempt to spread the wealth more evenly whilst limiting the negative impacts as much as possible
Skills are tools
Their real value lies in when and how you use them
Tools and skills are essential, but their value lies in how they are applied. Experience builds judgement about when to use a particular approach, when to simplify, and when a tool will add more complexity than benefit. This helps ensure skills are applied to the problem, not for their own sake
API
RESTful web services and APIs for data exchange and integration between applications.
AWS
Amazon Web Services cloud platform for scalable, reliable, and cost-effective web application hosting and services.
Agentic AI
Agentic AI systems combine reasoning, context, and controlled access to tools and data
Azure
Cloud computing platform for hosting, scaling, and managing web applications and services.
C Sharp
Powerful object-oriented programming with C# and the .NET ecosystem for building robust web applications and services.
Database
Databases are the backbone of most applications
HTML
The foundational markup language for creating structured, semantic web content.
JavaScript
Dynamic and interactive web development with JavaScript
LLM
Large language models are AI systems that understand and generate human language, enabling software to reason, automate tasks, and interact with users in natural, flexible ways.
LangGraph
Build stateful, production-ready AI workflows using a graph-based approach.
MCP
MCP is a standard way for AI systems to connect to tools, data, and services in a consistent and predictable manner
Machine Learning
A field of artificial intelligence focused on building systems that learn from data to make predictions
Python
Python is one of the go-to languages for writing AI application and APIs
SQL
Structured Query Language for managing and manipulating relational databases and data operations.