A developer reflects on the dual nature of AI's power, expressing excitement for its capabilities and dread over its potential to cause widespread job loss and economic disruption.
A curated list of key LLM research papers from the first half of 2025, organized by topic such as reasoning models and reinforcement learning.
Argues that clear thinking and purpose, not prompt or context engineering, are the key skills for effective AI interaction, writing, and coding.
An AI assistant analyzes a developer's chaotic, high-speed workflow using multiple AI agents as 'slot machines' to build apps faster.
Explores how advanced AIs use 'chains of thought' reasoning to break complex problems into simpler steps, improving accuracy and performance.
An Apple fan reflects on Google I/O 2025, expressing fear for Apple's future as Google pivots to an AI-first vision with Gemini.
Argues that the 'LLMs only predict tokens' critique fails, as human brains are similarly opaque systems that process input to produce output without conscious understanding.
A cybersecurity expert contrasts two groups of colleagues: AI skeptics who see it as overhyped and harmful, and those who recognize its transformative potential.
An analysis of key AI trends in 2025, focusing on industry leaders, AGI debates, and AI's impact on software development and science.
Explains the differences between Machine Learning and Generative AI, with examples and industry applications.
A blog post summarizing key concepts from an AI Evals course, focusing on mental models like the 'Three Gulfs' for improving LLM applications.
Critiques the limited scope of current customer support automation and argues for more ambitious AI solutions across industries.
A developer argues that AI coding agents are not like junior developers but rather 'amnesiac spies' with vast knowledge but no memory or growth.
Explains key AI terminology like AI, ML, deep learning, and LLMs to help engineers use the correct terms.
Explores how AI could transform large tech companies into vast networks of micro-startups, shifting the role of developers to broader builders.
Compares Model Context Protocol (MCP) and Agent2Agent (A2A), two AI communication frameworks for multi-model collaboration and agent interaction.
A software engineer explains how they use AI tools to boost productivity and argues why AI won't replace software engineering jobs.
Explores the evolution of AI from symbolic systems to modern Large Language Models (LLMs), detailing their capabilities and limitations.
Announcing EpicAI.pro, a new learning platform focused on building applications for the AI era, teaching foundational principles for AI-agent interaction.
Explores a human-centric definition of ASI and proposes a scalable, iterative methodology for achieving both AGI and ASI.
