The Machine Does Not Need a Hat
Context engineering is prompt engineering grown up: less magic wording, more tools, tests, observability, judgment, and feedback loops.
Agents & Automation
18posts
The AI Store Is Funny Until You Notice the Org Chart
An AI-run store sounds like a joke until it starts hiring people, forgetting them, and behaving like middle management with APIs.
The Agents Have Arrived. Now What?
AI agents are everywhere now, local and cloud-based. The real question is no longer what they can do, but what we should let them do.
Nobody With Claws
NVIDIA's NemoClaw is read as more than a framework: a sign that open AI agents are becoming infrastructure with teeth.
Imposta, but Make It Full-Duplex: PersonaPlex and the Next Wave of Voice Agents
NVIDIA's PersonaPlex points toward voice agents that interrupt, overlap, and converse more naturally, with all the design risks that implies.
Stay in Your Lane, Agent
Constantly switching coding agents can feel like progress while destroying continuity; the post argues for discipline over tool churn.
When an AI Can Act but Cannot Judge
LLMs may act impressively while still failing to know when they are capable, making self-assessment a core safety problem.
MCP meets no‑code: KNIME vs Make vs n8n vs Zapier
MCP could turn no-code platforms into callable tool providers for agents, changing the role of KNIME, Make, n8n, and Zapier.
Acontext: The Memory Implant Your AI Agents Have Been Dreaming About (While Forgetting Everything Else)
Acontext tackles the amnesia problem in AI agents by making reusable memory feel less like a feature and more like infrastructure.
The Paper That Made Me Close My Laptop and Pace Around the Room
Agent0 points toward self-evolving agents that learn through tools and reasoning traces without the usual diet of curated training data.
Amazon's Clash with ChatGPT: A Tug-of-War Over Shopping Data
Amazon's block on ChatGPT Shopping exposes the coming fight over product data, agent-mediated commerce, and who owns the customer path.
Two Protocols, Two Futures: OpenAI’s ACP vs. Anthropic’s MCP
OpenAI's ACP and Anthropic's MCP represent different futures for agents: commerce execution versus general tool access.
Agentic Commerce, Explained: What OpenAI’s Agentic Commerce Protocol Means for Retail and SaaS
Agentic Commerce Protocol shows how AI assistants may become buyers, forcing retailers and SaaS platforms to rethink checkout itself.
When AI Becomes Your Shopkeeper: The Curious Case of Claudius
Anthropic's AI shopkeeper experiment shows both the charm and absurdity of letting an autonomous model run a small business.
Human-in-the-Loop: The Art of Teaching Machines to Ask for Help
Human-in-the-loop design is presented as the practical art of knowing when machines should stop and ask for help.
OpenAI's Operator: When AI Gets Its Own Browser (And Why That's Both Cool and Scary)
OpenAI's Operator gives AI a browser, making web automation feel both immediately useful and structurally unsettling.
No Boss, All Brains: The New Paradigm of Decentralized AI Agents
Decentralized multi-agent systems promise problem-solving without a central boss, but coordination becomes the real challenge.
Multi-Agent LLMs: Exploring the Future of AI Collaboration
Multi-agent LLM systems are explored as a path toward distributed reasoning, specialization, and collaborative AI workflows.