{"id":1005516,"date":"2026-04-20T13:07:55","date_gmt":"2026-04-20T11:07:55","guid":{"rendered":"https:\/\/www.iterates.be\/?p=1005516"},"modified":"2026-04-08T13:33:37","modified_gmt":"2026-04-08T11:33:37","slug":"prompt-engineering-future-profession-or-ephemeral-skill","status":"publish","type":"post","link":"https:\/\/www.iterates.be\/en\/prompt-engineering-future-profession-or-ephemeral-skill\/","title":{"rendered":"Prompt engineering: the job of the future or a fleeting skill?"},"content":{"rendered":"
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Two years ago, the prompt engineer<\/strong> was presented as the most promising job of the decade. There were job offers for 300,000 $s a year in the United States. Today, some claim that major language models<\/strong> have become intelligent enough to do without precise instructions.<\/p>\n\n\n\n

So the prompt engineering<\/strong> is it a strategic investment or a fad that's running out of steam?<\/p>\n\n\n\n

What exactly is prompt engineering?<\/h2>\n\n\n\n

Le prompt engineering<\/strong> refers to the art of formulating precise instructions for an LLM<\/strong> to obtain reliable, relevant and usable results. It is the interface layer between human intention and machine capability.<\/p>\n\n\n\n

User, system and structured prompts: three very different realities<\/h3>\n\n\n\n

In practical terms, the\u2019prompt engineering<\/strong> covers several realities depending on the context. The user prompting<\/strong> is about writing better day-to-day instructions to get the most out of tools like ChatGPT in the workplace<\/a>. Le system prompt application IA<\/strong> designates the configuration of the behaviour of an agent or an upstream application. The structured prompting<\/strong>, Finally, it involves designing instruction chains for automated workflows AI<\/strong> complex. These three levels do not have the same future, and this is precisely where the debate becomes interesting.<\/p>\n\n\n\n

Why the quality of instructions makes all the difference<\/h3>\n\n\n\n

It's true that a more intelligent model understands vague requests better. But it always executes clear, well-structured instructions better. The quality of prompts and instructions IA<\/strong> remains the main lever of interaction: your request directly determines the relevance of the response, whatever the model used<\/p>\n\n\n\n

What will effectively disappear<\/h2>\n\n\n\n

Let's be frank: part of the prompt engineering<\/strong> as practised in 2023 is becoming obsolete, and that's good news.<\/p>\n\n\n\n

Tips for getting around the first LLMs<\/h3>\n\n\n\n

The first generations of major language models<\/strong> required very specific formulations to work properly: \u201cAct like an expert in...\u201d, \u201cOnly reply in JSON...\u201d, \u201cDon't mention that you're an AI...\u201d. These bypass techniques disappear as models become more robust and better educated by default.<\/p>\n\n\n\n

Prompting as a substitute for software engineering<\/h3>\n\n\n\n

Some companies thought that they could replace a real work of\u2019software architecture<\/strong> by sophisticated prompts. This approach quickly shows its limitations: a prompt, no matter how well designed, is no substitute for solid integration, error management or well thought-out business logic. This is particularly obvious when developing a customised business application<\/a> designed to be integrated into an existing digital ecosystem.<\/p>\n\n\n\n

The \u201cblack magic\u201d of obscure techniques<\/h3>\n\n\n\n

The catalogues of esoteric techniques - chain-of-thought prompting, tree-of-thought, least-to-most prompting - are still relevant for academic research, but their practical value for a practical application is limited. Belgian SME<\/strong> is often overestimated. It's not the sophistication of the technique that determines the quality of a prompt, it's the clarity of the intention behind it.<\/p>\n\n\n\n

On the contrary, it is becoming more strategic<\/h2>\n\n\n\n

While some practices are disappearing, others are becoming increasingly important in 2026. And they won't be disappearing any time soon.<\/p>\n\n\n\n

The design of instruction systems for AI agents<\/h3>\n\n\n\n

As companies deploy AI agents<\/strong> in production, the quality of the system prompt<\/strong> the one that defines the agent's behaviour becomes absolutely critical. A poorly instructed agent is costly in terms of business errors, hallucinations and unpredictable behaviour. Designing these instructions rigorously is an engineering job in its own right, as is knowing how to control your LLM costs<\/a> in production.<\/p>\n\n\n\n

Evaluation and iteration: the real work of prompt engineering<\/h3>\n\n\n\n

The real thing prompt professional engineering<\/strong>, It's less about \u201cfinding the magic formula\u201d and more about \u201cmeasuring, iterating and improving\u201d. Knowing how to build representative sets of tests, assess the quality of the outputs, detect regressions between two versions of a model - these are lasting skills. Visit essential AI tools<\/a> s are increasingly incorporating\u2019LLM quality assessment<\/strong> natively in their interfaces.<\/p>\n\n\n\n

Translating a business need into a technical instruction: a rare skill<\/h3>\n\n\n\n

The true value of a good prompt engineer<\/strong>, is the ability to translate a complex business need into clear, unambiguous instructions. It's not a purely technical skill: it's about communication, structured thinking and understanding the domain. It cannot be automated - and that is precisely why it will remain strategic.<\/p>\n\n\n\n

Prompt engineer: a dedicated profession or a cross-disciplinary skill?<\/h2>\n\n\n\n

This is where the question is posed differently, and where the answer becomes really useful for companies.<\/p>\n\n\n\n

Why the job of \u201cprompt engineer\u201d is going to become rarer<\/h3>\n\n\n\n

Le prompt engineer<\/strong> as a dedicated full-time position in a traditional company is becoming increasingly rare. Not because the skill is losing its value, but because it will naturally be integrated into existing professions. The prompt engineering training<\/strong> doesn't disappear - it changes its recipient.<\/p>\n\n\n\n

How prompt engineering fits in with existing professions<\/h3>\n\n\n\n

The product manager who designs a AI agent<\/strong> will need to master system prompting. The developer who integrates a LLM in production<\/strong> will need to understand how instructions influence outputs. The consultant accompanying a digital transformation SMEs<\/strong> will need to be able to frame use cases with precision. These developments are part of the major web and mobile development trends<\/a> which redefine the skills expected of tech teams in 2026.<\/p>\n\n\n\n

The parallel with SEO, data literacy and cybersecurity<\/h3>\n\n\n\n

Prompt engineering doesn't disappear - it spreads.<\/strong> This is exactly what has happened to SEO, data literacy and IT security. These skills are no longer the prerogative of isolated specialists: they are part of the foundation expected of all digital professionals. In five years' time, mastering the basics of prompting ChatGPT<\/strong> or the prompt engineering agent IA<\/strong> will be as natural as knowing how to use a spreadsheet<\/p>\n\n\n\n

Iterates, your partner for integrating AI into your business<\/h2>\n\n\n\n

At Iterates, we help Belgian companies with their AI adoption<\/strong> - from initial experimentation to the deployment of complex systems in production. No generic solutions: we analyse your real needs and build approaches tailored to your context.<\/p>\n\n\n\n

Support and training for your teams in prompting<\/h3>\n\n\n\n

Before any development, we train your teams so that they understand the possibilities and limits of major language models<\/strong>. This shared understanding guarantees AI adoption in business<\/strong> The aim is to ensure that our customers benefit from a successful project, make optimum use of the tools deployed, and develop their skills on a long-term basis - not by relying on an external service provider.<\/p>\n\n\n\n

Development of customised AI agents and LLM applications<\/h3>\n\n\n\n

We have worked with Belgian SMEs<\/strong> in the implementation of\u2019AI agents<\/strong> to automate critical processes such as document analysis, automatic lead qualification and the generation of customised reports. Our achievements demonstrate the tangible impact of\u2019AI enterprise automation<\/strong> on productivity and competitiveness.<\/p>\n\n\n\n

From audit to go-live: our complete approach<\/h3>\n\n\n\n

Our methodology for consulting IA Brussels<\/strong> covers the entire project cycle: initial audit to identify opportunities, design of the optimum solution, IA application development<\/strong> iterative process, user training, secure deployment and post-launch support. This approach ensures that your investment generates a measurable and lasting return.<\/p>\n\n\n\n

Ready to structure your AI approach?<\/h2>\n\n\n\n

Le prompt engineering<\/strong> will not die. It will simply cease to be exotic and become commonplace - in the noble sense of the word. So the real question is not \u201cWill it last?\u201d but \u201cAre my teams ready?\u201d.\u201d<\/p>\n\n\n\n

\u2192 Let's discuss your AI strategy with Iterates<\/strong><\/p>\n\n\n\n

<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

Two years ago, prompt engineer was heralded as the most promising job of the decade. There were job offers for 300,000 $s a year in the United States. Today, some claim that large language models have become intelligent enough to do without precise instructions. So is prompt engineering a...<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1226],"tags":[],"class_list":["post-1005516","post","type-post","status-publish","format-standard","hentry","category-tendances"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/posts\/1005516","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/comments?post=1005516"}],"version-history":[{"count":0,"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/posts\/1005516\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/media?parent=1005516"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/categories?post=1005516"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iterates.be\/en\/wp-json\/wp\/v2\/tags?post=1005516"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}