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- Indexed issues, last 90 days
- 6
- Latest publication
- Sep 23, 2026
- Audience
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- Earliest in this view
- Jul 21, 2026
Latest issues
Agent Memory Types: Cognitive Architectures for Language Agents (CoALA) framework (opens the original)
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LLM applications are moving from simple text generation to autonomous AI agents that can reason, plan, use tools, interact with their environment, and complete multi-step tasks. A key framework for building these agents is Cognitive Architectures for Language Agents (CoALA), developed by researchers at Princeton University. It connects modern LLM agents with ideas from cognitive science and older AI systems such as SOAR and ACT-R.A basic LLM is stateless: it generates responses based only on the
7 Best Practices for Building AI Agent Skills (opens the original)
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AI agents can now use “skills.” A skill is just a file that tells the agent how to do one job, like filling out a form or reviewing code. It sounds simple, but there’s a right way and a wrong way to build these files.Every new subscriber gets 🔥How to use Agentic AI, Use Cases & Strategy + 100 Free Smart AI Prompts to Grow Your Substack Subscribers, Increase Productivity, M
How Smart Organizations Will Use AI (opens the original)
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Every few months, someone predicts that AI is about to wipe out an entire profession. Radiologists, accountants, lawyers, developers, pick a job, and there’s a headline claiming it’s finished.But history keeps telling a different story. When technology makes a task cheaper and faster, something counterintuitive tends to happen: instead of shrinking the field, it grows. Understanding why this happens, and what it means for how organizations should actually use AI, is one of the most useful things
♾️ The Challenges of Agentic AI: Infinite Loops, Planning Failures, and Beyond (opens the original)
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When an AI agent goes wrong, it’s easy to blame the model. Maybe it “hallucinated.” Maybe the prompt was bad. But in most real cases, the real problem isn’t the AI’s intelligence, it’s how the system around it was built.Agentic AI doesn’t just answer a question and stop. It runs in a loop: it plans a step, takes an action, checks what happened, and adjusts. That loop is powerful, but it’s also where things break. A simple chatbot can’t get stuck repeating itself forever or accidentally delete th
📜 AI Agent Skills Explained: The Missing Procedural Memory Layer (SKILL.md, Scripts, References) (opens the original)
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LLMs possess vast semantic knowledge, general factual understanding, and sophisticated reasoning capabilities. However, when deployed within complex enterprise environments, language models encounter a structural operational boundary known as the procedural knowledge gap. While an LLM can articulate general legal, financial, or engineering principles, it lacks intrinsic awareness of specific organizational workflows, proprietary compliance standards, and step-by-step operational procedures.Histo
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