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The Future Belongs to Those Who Talk to Machines, Not to Those Who Code Them

🧠 Introduction: The End of the Coder’s Reign?

For decades, the image of power in the tech world was clear: a developer, often in the shadows, their face illuminated by lines of code scrolling across their screen. If you had an idea, you needed them. They were the translator, the builder, the guardian of the digital temple. Without their mastery of machine language, your vision remained a simple dream.

This era is coming to an end.

What if I told you that the most valuable skill of the next decade won’t be writing Python, PHP, or JavaScript, but mastering… English? What if I told you that your ability to be clear, curious, and imaginative will soon be worth more than your mastery of algorithms?

This may sound provocative, especially coming from a developer who has spent his life coding. Yet my conviction is forged daily: the future no longer belongs to those who code machines, but to those who know how to talk to them.

In this article, we’ll see why this shift is inevitable, how this new “dialogue” works concretely, and how you can, starting today, cultivate this skill to become a key player in the AI revolution.


⚡ Part 1 – Context: The Fall of the Technical Wall

For a long time, digital creation has operated on a simple but frustrating model:

Idea (Human) ➡️ Translation (Developer) ➡️ Execution (Machine)

The developer was a necessary bottleneck. For a PrestaShop e-merchant, this translated into constant dependence:

  • “I’d like a personalized promotion, need to ask the dev.”
  • “I’d like to analyze customer feedback, need a script from the dev.”
  • “My idea for a new feature? Have to check the budget and dev time.”

This barrier between intention (business need) and action (technical result) created friction, delays, and costs. Many brilliant ideas died in a quote or an endless task list.

The arrival of language models (LLM) like GPT-4 has shattered this model. For the first time, the machine no longer needs a translator who speaks its language. It has learned to understand ours.

The new model looks like this:

Idea (Human) ➡️ Dialogue (Natural Language) ➡️ Execution (AI + Machine)

The “hard skill” (code) is gradually being replaced by a competence we have long qualified as a “soft skill”: communication. Power no longer resides in knowledge of an obscure syntax, but in the ability to formulate a clear, rich, and precise request.

This is unprecedented democratization. The architect, the marketer, the logistics manager, the e-merchant themselves… All can now “give orders” to the machine without an intermediary.


🚀 Part 2 – Analysis: What Does “Speaking Well” to a Machine Mean?

“Speaking” to an AI has nothing to do with typing a question into Google. It’s a discipline in its own right that has a name: Prompt Engineering. It’s the art and science of constructing the perfect instruction to get the perfect result.

Thinking that simply “asking” is enough is the beginner’s first mistake. AI is a super-powerful tool, but without direction, it’s lazy and tends toward the average (as we saw in a previous article). “Speaking well to it” means sculpting it, guiding it, constraining it.

A good “speaker” masters four key elements for each instruction:

1. The Role (Persona) 🎭

You’re not talking to a machine, you’re talking to an expert you’ve just summoned.

  • Bad: “Write a text about this product.”
  • Good: “You are an expert copywriter in luxury products, specialized in watchmaking…”

2. The Objective (Goal) 🎯

What must the AI accomplish? What is the final goal?

  • Bad: “Make a description.”
  • Good: “… Your objective is to write a product description that arouses desire and justifies a high price by highlighting artisanal craftsmanship.”

3. The Context (Context) 📚

This is the raw material. Data, examples, constraints.

  • Bad: “The product is a watch.”
  • Good: “… Here are the features: 42mm titanium case, Swiss automatic movement, calfskin leather strap. Here’s an example of a tone I like: [paste text]. Don’t mention the word ‘affordable’.”

4. The Format (Format) 📦

How should the result be structured?

  • Bad: “Give me the text.”
  • Good: “… Structure your response in JSON format with the following keys: seo_title, description_html, key_points (an array of 3 strings).”

Whoever masters these four pillars can make AI do incredibly complex tasks. They don’t code, they direct. They are the director, and the AI is their actor with a thousand faces.


🧮 Part 3 – Concrete Application: Augmented PrestaShop Customer Service (without a line of code)

Let’s take a case that paralyzes many e-merchants: customer service management. Emails flood in, often with the same questions: “Where’s my order?”, “How do I make a return?”.

The old approach (the coder):

Develop a complex ticketing module, set up a chatbot with rigid scenarios. Months of development, tens of thousands of dollars.

The new approach (the “speaker”):

Create a workflow in 15 minutes with a tool like n8n or Zapier.

Here’s the plan:

1. The Trigger

A new email arrives in the support@myshop.com inbox.

2. Action 1 - AI Analysis

The email content is sent to an AI (GPT-4, Claude…) with a master prompt written by our “speaker”.

Prompt example:

You are a customer support agent for a PrestaShop store. Analyze the following email. Your objective is to categorize it and extract key information. Respond ONLY in JSON.

Possible categories: "Order tracking", "Return request", "Product question", "Other".

Information to extract: "order_id", "product_name", "customer_sentiment" (positive, neutral, negative).

Here's the email: {email_content}

3. Action 2 - Information Retrieval

  • If the category is “Order tracking” and an order_id has been found, the workflow queries the PrestaShop API to retrieve the order status (e.g., “Shipped”, “In preparation”).
  • If the category is “Product question”, the workflow searches for info in a knowledge base (a simple Google Sheet).

4. Action 3 - AI Writing

The workflow sends a second request to the AI.

Prompt example:

You are still our support agent. The customer is asking where their order {order_id} is. The status in PrestaShop is "{order_status}". Write a clear, empathetic and reassuring response email in English. Address the customer by their first name if possible.

5. Action 4 - Final Action

The workflow can then:

  • Create a draft in the support mailbox, ready to be validated and sent with one click.
  • Or, for simple cases, respond automatically.

In this scenario, value was not created by writing PHP code. It was created by writing two prompts in English. The “developer” of this system is an excellent communicator who knew how to perfectly brief their AI assistant. They “talked” to the machine.


🌍 Part 4 – Vision & Future Impact: The Era of the “Conductor”

So, is this the end of developers? No. It’s a mutation.

Coders aren’t disappearing, they’re getting promoted. Their role is no longer to build every wall, but to design the foundations and plumbing of the house. They become AI Systems Architects. Their work:

  • Create and maintain robust APIs that “speakers” will use.
  • Ensure the security and performance of the whole.
  • Build even more powerful tools so that “speakers” can go even further.
  • Intervene on the 2% of ultra-complex problems where AI fails.

Code becomes a meta-skill, the infrastructure of dialogue.

Meanwhile, new professions emerge and existing professions transform:

  • The Marketer can create dynamic campaigns without technical help.
  • The SEO Expert can generate content strategies at scale by “briefing” an army of AI writers.
  • The E-merchant can prototype and test new features themselves.

“Soft skills” — curiosity, critical thinking, creativity, empathy, the ability to synthesize — are no longer “bonus” lines on a resume. They become the core of value creation. The machine handles the “how”, the human finally focuses on the “why”.


🎯 Conclusion: Learn to Speak

For years, we’ve learned to think like machines to be able to program them. Today, machines are learning to think like us to be able to understand us.

This reversal is the greatest opportunity of our generation. It’s not about replacing humans, but freeing them from syntax. It’s about making the power of creation accessible to all those who have a vision, an idea, a question.

Pure technical mastery, once a rampart, becomes a commodity. Mastery of dialogue, intention and context becomes the new differentiating factor.

Code was yesterday’s language. Conversation is tomorrow’s language.

The only question that remains is: are you ready to learn to speak?


Article published on November 26, 2025 by Nicolas Dabène - Web development and AI applied to e-commerce expert


Questions Fréquentes

Why do we say the future belongs to those who talk to machines rather than those who code them?

With the arrival of LLMs like GPT-4, machines now understand natural language. Developers are no longer needed as translators between human intention and machine execution. The key skill becomes the ability to formulate clear and precise requests in natural language, thus democratizing digital creation.

What is Prompt Engineering?

Prompt Engineering is the art and science of constructing the perfect instruction to get the perfect result from an AI. It’s not simply “asking” the AI, but sculpting it, guiding it, and constraining it with structured and precise instructions.

What are the 4 key elements for communicating well with an AI?

The 4 pillars are: 1) The Role (Persona) - defining the expert you’re invoking, 2) The Objective (Goal) - what the AI must accomplish, 3) The Context (Context) - data, examples and constraints, 4) The Format (Format) - how to structure the result. Mastering these elements allows you to transform AI into a super-powerful tool.

Will developers disappear with AI?

No, they’re evolving. Developers are becoming AI Systems Architects. Their role is no longer to build every feature, but to create robust APIs, ensure security, build infrastructures and intervene on complex problems where AI fails. Code becomes a meta-skill.

How does AI change the work of PrestaShop e-merchants?

E-merchants can now create complex workflows (automated customer service, data analysis, personalized promotions) without coding, using tools like n8n combined with well-written prompts. They move from reactive mode (depending on a developer) to proactive mode (directly dialoguing with automated systems).