From Commands to Communication with AI

Smart AI, but Sometimes Frustrating

Have you ever experienced this while talking with AI? It completely forgets what was said earlier or gives irrelevant answers without considering our unique situation. This frustration of having to start fresh every time, as if meeting a stranger, why does it happen?

It’s because AI was missing a crucial puzzle piece called ‘context.’ Just as we naturally consider previous memories, surroundings, and emotions in conversation, AI also needs the ability to understand this ‘context.’

To solve this and turn AI conversations into true ‘communication,’ a new concept called ‘Context Engineering’ has emerged. But to fully grasp this, we first need to look back at how we’ve communicated with AI over time.

Chapter 1: The Long Journey of Talking to AI

Humans have tried to communicate with machines and AI for a very long time. The methods have dramatically changed with technological advances, much like teaching a baby to speak.

Step 1: Speaking Through Holes (1950s-60s - Batch Processing)

Early computer interaction was hardly a conversation. Programmers punched holes in punch cards to create commands in 0s and 1s, feeding them to computers in batches and waiting a long time for results. Any slight rule violation caused errors. It was a very one-sided, rigid ‘command.’

Step 2: Speaking Their Own Language (1970s-80s - Command Line)

With personal computers, we could interact in real-time via the Command Line Interface (CLI). Typing fixed commands like dir, cd, or copy elicited immediate responses. We still had to learn the machine’s language, but this was the start of back-and-forth conversation.

Step 3: Speaking with Pictures (1980s-Present - Graphic User Interface)

The mouse and icons revolutionized interaction. No longer needing to memorize commands, we could communicate by clicking visible icons. The GUI (Graphic User Interface) made computers intuitive and friendly for everyone.

Step 4: Speaking Our Language (2010s-Present - Natural Language Processing)

With voice assistants and chatbots, we finally spoke to machines in our own language. However, AI mostly responded within preset scenarios. It could answer “What’s the weather today?” but struggled with “Is it hotter than yesterday?"—still unable to grasp context.

Finally, with the advent of large language models (LLMs) and the rise of Context Engineering, we can dream of true ‘communication’ with AI.

Chapter 2: Context Engineering, the Technology Filling AI’s Brain

So how exactly does context engineering enable AI to communicate like humans? Let’s dive deeper. It goes beyond just crafting good prompts; it systematically designs the ‘information environment’ that allows AI to think and act smartly.

Just as we solve problems by combining knowledge, internet searches, and advice from others, we create such an environment for AI.

Core Technology 1: Giving AI an External Library (RAG)

AI’s fatal flaw is knowing only what it has learned. It doesn’t know yesterday’s events or internal company rules. Retrieval-Augmented Generation (RAG) solves this.

• Simple analogy: It’s like giving a brilliant but naive genius a ‘giant digital library pass.’ When asked a question, AI first visits this library (external databases, internal documents) to find the latest or expert information. Then it uses that to generate the most accurate, reliable answer.

Core Technology 2: The Magic Map That Teaches AI Meaning (Vector Database)

For RAG to work well, AI must quickly find relevant info among countless books. This is where the Vector Database comes in.

• Simple analogy: A normal library organizes books alphabetically or by genre, but a vector database is a magical library organized by ‘meaning.’ Words like ’love’ are near ‘partner,’ ’excitement,’ ‘breakup,’ while ‘car’ is near ’engine,’ ‘wheel,’ ‘driving.’ AI instantly teleports to the meaning closest to the question to find relevant info. So even vague queries like “a wheeled vehicle” yield precise ‘car’ information.

Core Technology 3: The Ability to Remember, Learn, and Act

Context engineering also gives AI human-like communication abilities.

• 🧠 Memory: Remembers previous conversations so it understands references like “that thing we talked about earlier.”
• 🛠️ Tools: Gives AI ‘hands and feet’ to execute external programs like booking flights or hotels in real time.
• 📜 System Instructions: Assigns AI specific roles (e.g., friendly financial expert) with consistent tone and behavior.

When all these elements combine organically, AI transcends rigid machines to become a true communication partner.

Chapter 3: The Future with AI and the Role of Context Engineering

Advances in context engineering will completely change how we collaborate with AI. We will no longer be supervisors issuing and correcting commands but designers and conductors creating environments where AI can perform at its best.

Anecdote: 2030, My AI Project Manager ‘Jupiter’

In 2030, I’m leading a new product development project. My AI project manager ‘Jupiter’ is more than a simple assistant.

1. [Automatic Project Context Learning] At project start, Jupiter accesses the company cloud to study past similar projects’ plans, meeting notes, and final reports. It analyzes success and failure factors and predicts risks, reporting them to me.
2. [Tailored Communication with Team Members] Jupiter remembers each team member’s work style and past performance. It gives clear, technical instructions to Developer A and uses visual references and emotional language with Designer B, maximizing each member’s potential.
3. [Autonomous Problem Solving] When real-time logistics data detects a supply issue overseas, Jupiter immediately searches for alternative suppliers worldwide, compares quotes, quality, and delivery times, and presents three options. After I choose option two, it sends the contract draft and schedules a video meeting on my calendar.

Throughout, I only ask, “Jupiter, how’s the project going?” or “What’s the best solution for the parts issue?” Jupiter, with a perfectly designed information environment, understands context and finds optimal solutions independently.

Opening the Era of True Communication

From punching holes in cards to convey our will to machines, to an era where AI understands not only our words but the hidden intentions and situations behind them, we have come a long way.

Context engineering is both the pinnacle and a new beginning of this journey. Beyond technology, it raises philosophical questions about how AI and humans can understand, trust, and grow together. Like a skilled conductor creating a beautiful score and stage for a great orchestra, context engineers craft the environment for AI to perform at its best. Isn’t this the new role we all need to embrace living with AI?