Quick Answer Prompt chaining is a technique where you break a complex AI task into a series of smaller prompts, and the output of each prompt becomes the input for the next one. Instead of asking an AI model to research, analyze, write, and edit a 2,000-word report in one shot, you split that into…

Quick Answer AI agents fail in production more often because of weak surrounding systems than weak prompts, which is why loop engineering, not better prompting, is the real fix. A single perfect prompt only governs one exchange. An agent needs to act, check its own work, decide what to do next, and keep going for…

Quick Answer Loop engineering is the practice of designing the automated system that prompts an AI agent on your behalf, instead of you typing each instruction by hand. It became a defining idea in AI circles in June 2026, when developer Peter Steinberger posted that people should stop prompting coding agents and start “designing loops…

Quick Answer Prompt engineering is the practice of crafting the instruction you send to an AI model, the words, structure, and examples within a single message. Context engineering is the broader discipline of deciding what information the model sees before it even starts answering, including retrieved documents, conversation history, tool definitions, and memory. AI researcher…