forge - added tutorial images

autogpts/forge/tutorials/001_getting_started.md

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 ## [AutoGPT Forge: A Comprehensive Guide to Your First Steps](https://aiedge.medium.com/autogpt-forge-a-comprehensive-guide-to-your-first-steps-a1dfdf46e3b4)
 
+![Header](../../../docs/content/imgs/quickstart/000_header_img.png)
+
+
 Welcome to the getting started Tutorial! This tutorial is designed to walk you through the process of setting up and running your own AutoGPT agent in the Forge environment. Whether you are a seasoned AI developer or just starting out, this guide will equip you with the necessary steps to jumpstart your journey in the world of AI development with AutoGPT.
 
 ## Section 1: Understanding the Forge

autogpts/forge/tutorials/002_blueprint_of_an_agent.md

@@ -8,7 +8,7 @@ Craig Swift
 
 ---
 
-![The Github repository](../../../docs/content/imgs/quickstart/001_repo.png)
+![Header](../../../docs/content/imgs/quickstart/t2_01.png)
 
 
 Hello there, fellow pioneers of the AI frontier!  
@@ -27,7 +27,7 @@ Large Language Models (LLMs) are state-of-the-art machine learning models that h
 
 Traditional autonomous agents operated with limited knowledge, often confined to specific tasks or environments. They were like calculators — efficient but limited to predefined functions. LLM-based agents, on the other hand, are akin to having an encyclopedia combined with a calculator. They don’t just compute; they understand, reason, and then act, drawing from a vast reservoir of information.  
 
-![AI visualising AI researchers hard at work](../../../docs/content/imgs/quickstart/001_repo.png)
+![AI visualising AI researchers hard at work](../../../docs/content/imgs/quickstart/t2_02.png)
 
 
 The Agent Landscape Survey underscores this evolution, detailing the remarkable potential LLMs have shown in achieving human-like intelligence. They’re not just about more data; they represent a more holistic approach to AI, bridging gaps between isolated task knowledge and expansive web information.  
@@ -38,7 +38,7 @@ Further expanding on this, *The Rise and Potential of Large Language Model Based
 
 Diving deep into the core of an LLM-based AI agent, we find it’s structured much like a human, with distinct components akin to personality, memory, thought process, and abilities. Let’s break these down:  
 
-![The Github repository](../../../docs/content/imgs/quickstart/001_repo.png)
+![The Github repository](../../../docs/content/imgs/quickstart/t2_03.png)
 Anatomy of an Agent from the Agent Landscape Survey  
 
 1. **Profile**  
@@ -71,7 +71,7 @@ In an ecosystem where every developer might have their unique approach to crafti
 
 Now we understand the architecture of an agent lets look inside the Forge. It’s a well-organized template, meticulously architected to cater to the needs of agent developers. Let
 
-![The Github repository](../../../docs/content/imgs/quickstart/001_repo.png)
+![The Github repository](../../../docs/content/imgs/quickstart/t2_04.png)
 
 #### Forge’s Project Structure: A Bird’s-Eye View