Applying prompts to GenAI/LLMs

Prompt engineering, context engineering and agentic AI are often used interchangeably, but the literature treats them as distinct. Prompt engineering concerns crafting effective single instructions to a model (Glean, 2026). Context engineering is the broader discipline of designing and managing the entire informational environment around a model—memory, retrieval, tool outputs and conversation state—rather than a one-off instruction (Abstracta, 2026); prompt engineering operates within the context window, while context engineering determines what fills it (arXiv:2606.12422, 2026). Agentic AI describes systems that plan and execute multi-step tasks with delegated autonomy, raising organisational questions of accountability rather than purely technical ones (MIT Sloan, 2026; Palo Alto Networks, 2026). There is genuine debate about prompt engineering's durability. IEEE Spectrum (2025) reported research suggesting prompting is increasingly performed by models themselves, and standa...

New article crafted between myself and Claude.AI both been critical but constructive about each 'others' contribution, and refinement of the replies and editing after. The starting prompt is shown after the references Context Engineering Isn't the New Software Engineering — But Ignoring It Is Still a Mistake What context engineering actually is Why "the new software engineering" overstates it The more defensible version of the argument Where the evidence runs thin — and where curriculum reform gets hard Conclusions Context engineering is a real, evidenced, currently valuable skill — not hype invented from nothing. It sits downstream of genuine engineering problems (retrieval, state management, information curation) that graduates will encounter in real jobs. It is not a replacement for software engineering fundamentals, and framing it that way overstates the case and risks looking like marketing rather than analysis. The stronger, teachable claim is that context e...