Intro to Using GScript for Red Teams
By Action Dan
Archived: 2026-04-05 20:34:49 UTC
"Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life" by Pascal Bornet.
This book was written at the very beginning of the agentic AI wave, looking at early adopters of using LLMs in
agents to have generic language models drive computer tools. It has some great lessons learned on implementing
agentic systems, but it’s largely non-technical, likely because it was written before these systems became
standardized.. I listened to this on Audible at about ~$15 for roughly 10 hours (on 1.5x speed).  At nearly 500
pages it's a pretty heavy read, although I personally found the first two parts the most impactful in terms of AI
theory and implementation insights. The final three parts shift toward business building, enterprise adoption, and
long-term societal impact. While the end of the book seemed to depart from reality a bit (talking about Universal
Basic Income once agents take over the majority of jobs), I thought the beginning was fascinating and eye opening
in terms of planning and reasoning with agents. Overall I'm going to give this 5 out of 10 stars. I recommend this
to people wanting to get more theory and guidance when building out agentic systems, although I'm not sure I
would recommend this if you were looking for a technical book. The book has no real mention of actual
technology needed to implement these ideas. There is almost no mention of specific models, structures, or even
the types of agents that could be run to automate these goals. In that sense the book left a lot to be desired, it was
almost purely theory.  That said, I did enjoy the first two parts of the book. The following are the chapters of the
book so you can get a better idea of it's contents before picking it up:
http://lockboxx.blogspot.com/2018/02/intro-to-using-gscript-for-red-teams.html
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Introduction
Part 1: The Rise of AI Agents
Chapter 1: Beyond ChatGPT: The Next Evolution of AI
Chapter 2: The Five Levels of AI Agents: From Automation to Autonomy
Chapter 3: Inside the Mind of an AI Agent
Chapter 4: Putting AI Agents to the Test
Part 2: The Three Keystones of Agentic AI
Chapter 5: Action: Teaching AI to Do, Not Just Think
Chapter 6: Reasoning: From Fast to Wise
Chapter 7: Memory: Building AI That Learns
Part 3: Entrepreneurship and Professional Growth with AI Agents
Chapter 8: A Practical Guide For Building Successful AI Agents
Chapter 9: From Ideas to Income: Business Models for the Agent Economy
Part 4: Enterprise Transformation Through Agentic AI
Chapter 10: Human-Agent Collaboration: Leadership, Trust, and Change
Chapter 11: Scaling AI Agents From Vision to Reality
Chapter 12: Case Study and Use Cases of Agents Across Industries
Part 5: Future Horizons For Work and Society
Chapter 13: The New World of Work
Chapter 14: Society in the Age of Agents
Conclusion
I struggled with parts of the book, because it repeatedly argues that agents should take action, but rarely explains
how that action is implemented.. Should agents be calling APIs in a microservice architecture, or should we be
giving agents full control of systems with local tools like ClawdBot? Is it better to give agents skills on how to use
specific tools, or should we continue using MCP servers for up-to-date information on the tools? There is a ton of
implementation details the book conveniently glosses over. The book also glosses over memory in a similar way,
which in my experience if done wrong can make an agentic system much worse. Memory has lots of core
questions, like storage location and structure, as well as retrieval quality and embedding limitations. It's a pretty
hard thing to get right, so I'm surprised it didn't dive into any of the technical edge cases there. One technique the
book does mention in depth is using an extensive RAG library or even a wiki or onboarding documents to support
the agentic system if it needs to lookup context or understanding around a process. The book is also very
idealistic. From it's estimations on agentic reasoning capabilities (nearly a year after it was written and these
models still make regular mistakes) to it's predictions around Universal Basic Income when many common jobs
are automated, it honestly makes me a little worried what a more grounded future might look like when I see these
as proposed solutions. 
http://lockboxx.blogspot.com/2018/02/intro-to-using-gscript-for-red-teams.html
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Ett fel inträffade.
Det går inte att köra JavaScript.
Source: http://lockboxx.blogspot.com/2018/02/intro-to-using-gscript-for-red-teams.html
http://lockboxx.blogspot.com/2018/02/intro-to-using-gscript-for-red-teams.html
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