The AI That Runs Itself: Agentic AI explained simply
Your straightforward guide to self-driving business AI
🚀 Quick Take (15-Second Summary) 🚀
Forget everything you've heard about AI being just another tech buzzword. Agentic AI is different - it's AI that actually thinks and acts for itself. Today, I'm excited to be working in this product development space. I can tell you now, this will change everything. It's the game-changer that will transform businesses.
The evolution is going to be mind-blowing! Whilst traditional AI needs constant human oversight, Agentic AI will optimise human intervention. This isn't just about automation, it's about AI making decisions with business intelligence.
Let's tuck in so I can show you why, from my learnings from a real-world built Agentic AI product.
The hidden truth about AI that runs itself
Picture this: You've just implemented a chatbot that handles customer queries. It does the job, but it needs constant tweaking, training, and supervision. Now imagine an AI system that not only handles those queries but also:
Spots patterns in customer complaints before they become trends.
Automatically adjusts its responses based on what works.
Identifies product issues from customer feedback.
Proactively suggests service improvements.
That's Agentic AI in action. And it's already happening.
"Most businesses are still treating AI like a smart intern - following orders brilliantly but needing constant supervision. Agentic AI is more like having a seasoned executive who takes initiative."
Why this matters more than you think
Here's a sobering statistic: 85% of AI implementations fail to deliver expected value. But I believe companies who will use Agentic AI will likely see a different story. Let me break down why.
The shift to self-driving AI
The big difference isn't in the technology - it's in the autonomy. Think about how Tesla moved from cruise control to self-driving capabilities. That's what's happening with AI right now. Traditional AI systems need constant human oversight, like cruise control needs a driver. Agentic AI? It makes decisions on its own, learning and adapting. It continues until a human interrupts it.
With Templonix (our Prototype Platform) a PoC for learning about Agentic AI, companies using Agentic AI will see:
Eduction in decision-making delays.
Decrease in routine human interventions.
Faster response to market changes.
Beyond the Buzzwords: A Real Example - Netflix's Game-Changing System
Netflix isn't just using AI to recommend shows anymore. Their Agentic AI system:
Predicts content performance before release.
Manages global content rights.
Optimises streaming quality in real-time.
The result? An improvement in viewer engagement and substantial cost savings in content acquisition.
The implementation secret nobody talks about
Here's the truth: The technology isn't the hard part. It's the integration. After implementing Agentic AI, I've found three critical success factors will impact any company:
The hard truth about implementation
Here's what I'm seeing and learning from getting Agentic AI working in the real world, through Templonix:
The 60-30-10 Rule
60% of success comes from preparation of guardrails, tools, templates
30% from integration with plug-ins
10% from the actual AI technology working with human-in-the-loop.
Through our work at Templonix, the 60-30-10 rule has emerged as a critical framework for successful Agentic AI deployment:
The 60% Foundation: Guardrails, Tools, and Toolchains
The majority of success hinges on meticulous preparation of guardrails, tools, and templates. Setting strong guardrails that define what to do and not to do helps. It defines which reusable tools are allowed (e.g., a search engine) and develops toolchains (i.e., connecting tools to work together).
What I've found is when we neglect this groundwork, the Agentic AI system falters. These guardrails aren't just restrictions - they're the framework that enables autonomous operation to flow.
The 30% Integration Layer: Plugin Architecture
Plugin integration forms the vital connective tissue of your Agentic AI system. This means creating flexible interfaces. They will let your AI work with existing systems. I've found that well-chosen plugins (like Twitter) don't just make Agentic AI great; they create intelligent pathways for learning and decision-making.
They must be robust enough to handle unexpected scenarios while maintaining system integrity.
The 10% AI Technology: Human-in-the-Loop Operations
The actual AI technology, with human oversight, is the smallest but most visible part of the implementation. It's not about constant supervision. It's about key moments where human judgment adds value. I've learned that success means to minimise interventions and maximise their impact when needed.
This ratio challenges conventional wisdom. It often focuses too much on the AI tech. In practice, it's the prep and integration that matter. They will determine if your Agentic AI works well or becomes an underused tool.
Key Takeaways
✅ The Autonomy Mindset: It's not about building an AI assistant - it's about creating a self-running system that makes decisions independently within defined boundaries.
🔄 The 60-30-10 Rule in Practice
60%: Build guardrails, tools, and templates first.
30%: Focus on plugin integration that works.
10%: Implement AI with strategic human oversight.
🎯 Implementation Reality: Check Success isn't about AI sophistication - it's about proper preparation, clear boundaries, and seamless integration with existing systems.
âš¡ Three Non-Negotiables
Clean, reliable data infrastructure.
Strong governance framework.
Well-planned people strategy.
💡 Bonus Insight: The best Agentic AI implementations minimise human interruption rather than requiring constant oversight.
Until next time, keep it real and keep it practical.
Drop a comment below if you've got war stories of your own to share - I read every response.
Cheers, Tim