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18/09/2026

RAG helps AI find right information before answering.

This episode breaks down chunking, embeddings, vector databases and retrieval and how they help AI agents search, filter and use information to complete a task

17/09/2026

Tesla and Waymo are betting on two very different ways to build self-driving AI.

Tesla bets on cameras, AI and data. Waymo combines cameras, LiDAR and radar. Both are already working in the real world at different stages.

16/09/2026

The AI job skill companies are hiring for : AI orchestration.

As AI moves from chatbots to agents, the value is in assigning agents jobs, tools & workflows—and coordinating them to get work done. It’s a shift from using AI to building AI systems.

11/09/2026

AI is now moving from the lab into the operating theatre.

In the UK, surgeons used an AI system during brain surgery to identify critical structures in real time while removing an 11mm tumour pressing against the nerves controlling a patient’s vision.

This is a powerful glimpse of what AI in healthcare could do. Not by replacing expertise, but giving experts better eyes, better information, and more confidence when it matters most.

09/09/2026

What happens after you submit a prompt to an AI image generator?

In Day 10 of Decoding Agentic AI, we follow one image-generation request to explain four important concepts in modern AI deployment

04/09/2026

Why the Same AI Prompt Can Give Different Results

AI doesn't always behave like predictable software.
In Day 9 of Decoding Agentic AI, we explore why AI can produce different outputs, confidently generate incorrect information, and respond differently depending on how a task is presented.
A practical introduction to AI behaviour and control for anyone working with LLMs, generative AI or Agentic AI.

02/09/2026

Day 8 of Decoding Agentic AI explains the role of context windows, context engineering, context rot and statelessness using one simple image-generation example.
Understand why more context isn't always better and why selecting the right context matters.

01/09/2026

What actually happens between an AI model learning language and becoming capable of following instructions and solving problems?
In Day 7 of Decoding Agentic AI, we explain the core stages of AI training through a familiar image-generation example.
From pre-training and fine-tuning to alignment and reasoning training, understand what each stage teaches the model and why it matters to the way today's AI systems behave.

31/08/2026

In Day 6 of Decoding Agentic AI, we use a real-world example to explain the key components behind modern AI systems:
Tokens → Embeddings → Attention → Transformer Blocks → Weights
You'll understand how an AI model processes your instruction, connects different concepts and uses patterns learned during training to generate an image.
A simple breakdown of the technology behind the AI image generation tools we're all starting to use.

28/08/2026

The fundamental difference between a conventional AI interaction and an agentic workflow is you provide the goal.
The agent determines and executes the path.
Follow for Agentic AI, explained from scratch.

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