Today there is a lot of buzz on AI but many people don't understand fully. This is purely in public interest and I deliberately not used AI to correct English or grammar.
Generative AI vs Agentic AI
Chatbots, image generators, text generators, code generators, audio generators. Reactive systems — they wait for you to prompt them, then generate something in response.
Proactive systems made of one or more AI agents acting as a unit. They pursue goals with a series of actions — perceiving, deciding, acting, learning — with minimal human intervention.
Generative AI — the pattern matching machine
Generative AI systems are essentially pattern matching machines. They identify the correlation between words, pixels, sound waves and more. They learn these patterns from the massive datasets used for training them.
This is where most AI-related concerns happen — like the impersonation of a human's voice. Once a human's voice pitch is captured, it can be used to sound sentences as if that human is talking. Similarly, we can make new movies with deceased actors using this technique.
Generative AI is reactive. It waits for you to prompt it. Once you do, its job is to generate something based on that prompt — and nothing more.
Agentic AI — the goal-pursuing system
Agentic AI systems are not reactive like Generative AI. They are proactive systems — a combination of one or more AI agents acting as one unit.
Like Generative AI, Agentic AI also starts with a prompt. But that prompt is then used to pursue goals (desired outcomes) with a series of actions. An Agentic system:
1. Perceives its environment → 2. Decides an action to take → 3. Executes that action → 4. Learns from the output
This cycle continues until the goal has been achieved — all with minimal human intervention.
Agentic AI is an engineering control system with an LLM as the brain — instead of a human brain or fixed programming logic — making decisions for workflows until the goal is achieved. We can have a bunch of programs (tools) and let the LLM decide when to use what tool.
What do they have in common?
Both Generative AI and Agentic AI share a common foundation: Large Language Models (LLMs).
Looking ahead, the most powerful AI systems may not be purely Generative or purely Agentic — but intelligent collaborators using both together.
The more accurate an LLM's decision, the closer it comes to a human decision. This is where past data plays a vital role. However, keep in mind — for the most part there is a correlation between past decisions and future outcomes, but this is not 100% accurate and AI can go wrong.
"Junk in, junk out." If the data being used to train the model is bad, the model gives bad decisions. The quality of your data determines the quality of your AI.
What is a Prompt?
A prompt is human-like sentences that an LLM can understand — as if you are talking to another human — and it behaves accordingly.
"You are an expert math teacher. Please solve this problem."
This gives the LLM a persona. By telling it who it is and what you want, you get far better and more relevant responses. The quality of your prompt directly shapes the quality of the AI's output.
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