Command engineering: Your guide to mastering artificial intelligence and avoiding its pitfalls
In the midst of the Fourth Industrial Revolution, artificial intelligence is no longer a science fiction concept or a technological luxury confined to laboratories; it has become an everyday reality permeating our offices and personal lives. With the emergence of Large Language Models (LLMs) like ChatGPT and others, a new term has emerged as the "password" to success in this era: Prompt Engineering . The difference between finding a brilliant answer that saves hours of work and falling into the trap of misinformation that could end a career lies in a single carefully crafted line.
Historical context: From rigid rules to creative generation
Historically, computer systems operated on the principle of "specific inputs leading to specific outputs" (rule-based systems). However, with the development of neural networks and deep learning, we have moved into the era of generative artificial intelligence, where the machine predicts the next word based on complex statistical probabilities. This radical shift has made the method of "communicating" with the machine the most vital skill; the machine possesses a vast ocean of information, but it needs a skilled "captain" to steer the ship, and this is where the importance of command engineering becomes paramount.
The pillars of command engineering: The intelligence of the question is half the answer
Technology expert Mu'ayyad Dabwan told Okaz that artificial intelligence is not a magic box, but rather a "mirror" reflecting the user's intelligence. To transform this tool from a mere advanced search engine into an expert assistant, a "command structure" must be built based on four fundamental pillars:
- Task definition: Use direct and clear command verbs such as (analyze, formulate, compare, summarize).
- Persona: Directing the machine to adopt a specific role (act as a legal expert, professional programmer, marketing consultant) to adjust the tone and depth of the response.
- Context: Providing the model with the necessary background, such as the target audience and the purpose of the text, to ensure the accuracy of the outputs.
- Output formatting: Determining the final form of the answer (comparison table, points, official report, programming code).
Dabwan adds: “The real engineer is the one who engages in dialogue with the machine and asks it to critique itself before approving the result, which saves 90% of professional work time.”.
The "digital hallucination" trap: when intelligence creates reality
Despite their immense capabilities, artificial intelligence models suffer from a phenomenon known as "hallucination," where they provide answers that appear confident and linguistically logical, but are factually incorrect. Okaz newspaper has observed serious legal ramifications of this issue
- In the United States: A Texas lawyer was fined $2,000 after filing a defense memo containing fake cases created by artificial intelligence.
- In Qatar: The Qatar Financial Centre Court issued a ruling in November 2025 against a lawyer who relied on imaginary legal precedents.
- In South Africa: A law firm was ordered to bear additional legal costs due to blind reliance on inaccurate technical outputs.
These incidents confirm that relying on technology without "human verification" and without precise command engineering that identifies sources can lead to professional disasters.
Economic impact and labor market: Transformation, not replacement
Economically, artificial intelligence has redrawn the map of global wealth, with the market capitalization of companies developing these technologies soaring into the trillion-dollar club. This growth is not merely a matter of numbers; it reflects a transformation in the structure of the labor market. According to consultant and social analyst Dr. Abdulrahman Al-Shahrani, machines are not stealing jobs, but rather eliminating routine tasks.
Among the most prominent sectors undergoing radical change are:
- Technical support: Shifting towards intelligent automated responses and reducing human reliance on repetitive tasks.
- Translation and editing: The translator has transformed from a "carrier" of words to a "editor" of cultural context.
- Legal research: reducing hours of searching through massive references to mere seconds.
Practical experience: Artificial intelligence in everyday life
Beyond large corporations, individuals can leverage command engineering to maximize their personal gains. The story of Hudhaifa, who is neither a mechanic nor an expert, is a prime example. Instead of succumbing to high dealership prices or the opaque nature of spare parts shops, Hudhaifa cleverly utilized artificial intelligence:
- Specify the exact specifications of his car (model, year, engine).
- Request original part numbers and approved replacements.
- Use smart translation to understand shipping policies and compare global suppliers.
The result was a savings of more than 50% of the cost, proving that the real value is not in paying the $20 subscription fee for the tool, but in the mental skill that operates this tool.
