Moving From Prompt Engineers to Agent Auditors

Hello,

This is Simon with the latest edition of The Weekly. In these updates, I share key AI related stories from this week's news, list upcoming events, and share any longer form articles posted on the website.

When generative AI first burst onto the scene, we all started by asking basic questions in chatbots like ChatGPT. It didn’t take long for people to realise that structuring prompts in specific ways yielded better answers. This observation launched a behaviour known as "Prompt Engineering"; in fact, many believed this was destined to become an entirely new job role.

Prompt frameworks emerged, such as RICCE (Role, Instructions, Context, Constraints, Examples) and COSTAR (Context, Objective, Style, Tone, Audience, Response). It was widely thought that one had to use approaches like these to extract the most reliable and valuable answers. However, the latest models now possess such extensive built-in context that writing in your natural voice often yields results just as good.

Prompting has effectively become a commodity. Most individuals are now comfortable using their own prompts to aid their day-to-day work. The prevailing belief was that competence in prompting would future-proof your career, marking you as "AI literate". However, the goalposts are already moving.

As we begin 2026, the savviest employees have already realised that working with AI is now about connecting different systems—or, in other words, working with agents.

In a recent edition, I discussed how the Model Context Protocol (MCP) allows systems to interact with one another. AI use has moved beyond simply asking a chat system to summarise your inbox or draft a response. Using tools like Microsoft Agent 365, or Vellum AI, an individual can now submit a high-level intent, such as: "Launch a Q3 engagement campaign targeting our 'at-risk' customers with a budget of $50k."

From this point, a series of actions kick off:

Crucially, you still play a significant role. You must use your knowledge and experience to review the campaign built for you, providing final approval before the campaign is executed.

This signals the future shift in many professional roles: moving from a "doer" to an "auditor". Agents can still "hallucinate" or make errors, so your value lies in your ability to spot a mistake in the agent's output before it goes live. You will spend less time creating items, and more time verifying them.

Whether this shift will be more enjoyable and satisfying remains to be seen.

AI has changed how consumers shop by speeding up research. But one thing hasn’t changed: shoppers still trust people more than AI.

Levanta’s new Affiliate 3.0 Consumer Report reveals a major shift in how shoppers blend AI tools with human influence. Consumers use AI to explore options, but when it comes time to buy, they still turn to creators, communities, and real experiences to validate their decisions.

The data shows:

The most effective brands are combining AI discovery with authentic human influence to drive measurable conversions.

Affiliate marketing isn’t being replaced by AI, it’s being amplified by it.

Download the full report to see what this means for your brand.

Exclusive for subscribers.

In this section, I’m going to bring to you a real world example of AI use. This week, we look at how AI is being used in recruitment.

At CES 2026, Nvidia announced a big push into “physical AI” – AI models designed to control robots in the real world. They released a suite of open models (Cosmos and GR00T), tools for simulating robots, and highlighted partners building humanoid, industrial and even surgical robots on Nvidia hardware.

Why it matters: This represents a shift from AI living on screens to AI in factories, warehouses, hospitals and, maybe one day, homes.

IBM and the US National Retail Federation published a global study showing that while 72% of consumers still shop in physical stores, 45% already use AI somewhere in their buying journey. They lean on AI to research products (41%), interpret reviews (33%) and hunt for deals (31%), often before they ever visit a store or retailer app. The study argues that “agentic commerce” – AI assistants acting as personal shoppers – is reshaping how brands compete.

Why it matters: AI is quietly becoming the new “front door” to the customer, sitting between buyer and brand.

Lenovo unveiled Qira, a system-level AI assistant that runs across Lenovo laptops and Motorola phones. Rather than being “just a chatbot,” it’s pitched as a proactive, cross-device assistant that keeps context throughout your day and can take actions on your devices. It uses a mix of on-device and cloud models (with infrastructure from Microsoft Azure, OpenAI, Stability and others) and leans hard into optional data collection and visible recording to avoid “creepy” behaviour like Microsoft’s controversial Recall feature.

Why it matters: This is another sign that every major hardware vendor is racing to build its own AI layer, not just ship Windows + ChatGPT.

Thanks for reading, and see you next Friday.

Simon,

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