While AI agents are touted as the future, practical experience reveals critical challenges in reliability, cost, and tool engineering that must be addressed for successful real-world deployment.

Sharing AI-generated content without explicit consent or personal adoption can be seen as a form of information pollution, akin to the alien ‘scramblers’ in Peter Watts’ ‘Blindsight’ who wage war by overwhelming others with meaningless data.

The rapid evolution of AI is reshaping software development, moving from structured coding to a more improvisational approach where developers guide AI assistants, raising questions about traditional expertise and the very definition of programming.

Current limitations in AI’s ability to learn continuously like humans hinder its transformative potential in economic applications.

Exploring the evolution of software and the emergence of Large Language Models (LLMs) as a new programmable paradigm.

Generative AI’s rapid development raises questions about its financial viability, environmental impact, and societal consequences, prompting a critical examination of its potential benefits and drawbacks.

Exploring the multifaceted concept of intelligence, both natural and artificial, and its role in addressing complex global challenges.

Exploring the potential of AI systems that can rewrite their own code to achieve continuous self-improvement and adapt to new challenges.

An analysis of the realism of AI predictions, exploring the potential economic and societal impacts.

Is the AI copilot truly an innovative tool, or does it represent a descent into mediocrity by encouraging laziness and a detachment from the underlying machine?