When AI Starts Thinking for Itself: Welcome to Agentic AI

Alright, so we've established that raw LLMs are brilliant but passive. But what if we could give them a bit more… independence?

That's where the "next evolution" of AI, known as Agentic AI (or Autonomous AI), steps onto the stage. This isn't just about clever prompts anymore; it's about systems that can "make decisions on their own" and "take actions".

Imagine you tell your AI a broad goal, like "prepare for Sarah's maternity leave" or "onboard the new intern joining next Monday". A standard LLM would struggle because these aren't simple, single-step questions. These are "complex tasks" that "require multi-step reasoning and multi-step planning".

This is the fundamental shift: in Agentic AI, the LLM transforms from a reactive content generator into the "decision maker in the workflow". It acts as the "orchestrator, or reasoning engine," that understands complex tasks, generates solutions, and coordinates various specialised models and external tools to achieve a goal with "limited supervision". This means it's proactive, not just reactive.

Agentic AI systems work through a fascinating four-step problem-solving process:

• Perceive: They gather and process data from various sources – sensors, databases, digital interfaces.

• Reason: The LLM, acting as the orchestrator, analyses this data to understand the situation, generate solutions, and plan a path forward. This often involves techniques like Retrieval Augmented Generation (RAG) to access external or proprietary data.

• Act: Based on their plans, they "execute tasks" by integrating with external tools and software via APIs. This could mean sending an email, scheduling a meeting, or even making a purchase.

• Learn: Crucially, they "continuously improve through a feedback loop". They can even critique their own output and iterate autonomously until specific criteria are met, removing the need for human trial-and-error in many cases. For instance, an agent might draft a LinkedIn post, then use another LLM to critique it against best practices, repeating the cycle until it's perfect.

From compiling news articles into social media posts to identifying skiers in video footage, Agentic AI is designed to handle tasks with a degree of autonomy that goes far beyond what we've seen before.

It’s about machines doing the thinking and doing, not just the generating.