Paul Brown
Colt
The next level of ai is here. "AI is leaving us all behind"
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is the next ai advancement 'agentic ai'
Yes, agentic AI is widely considered the defining advancement of the current era (2025–2026). While previous iterations focused on "Generative AI" (creating text or images based on prompts), the shift to "Agentic AI" marks a move toward systems that don't just talk, but act.
Here is a breakdown of why this is considered the "next big leap" and what it actually looks like in practice.
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is the next ai advancement 'agentic ai'
Yes, agentic AI is widely considered the defining advancement of the current era (2025–2026). While previous iterations focused on "Generative AI" (creating text or images based on prompts), the shift to "Agentic AI" marks a move toward systems that don't just talk, but act.
Here is a breakdown of why this is considered the "next big leap" and what it actually looks like in practice.
What Makes it "Agentic"?
The core difference lies in autonomy. Traditional AI is passive; it waits for a prompt and provides a single response. Agentic AI is active; you give it a goal, and it determines the steps to reach it.| Feature | Generative AI (Chatbots) | Agentic AI (Agents) |
|---|---|---|
| Input | Specific prompt (e.g., "Write an email") | High-level goal (e.g., "Organize a trip") |
| Action | Generates text/media | Interacts with software, APIs, and tools |
| Logic | Linear response | Loops of reasoning, planning, and self-correction |
| Autonomy | Requires constant human steering | Can run in the background to complete tasks |
Key Advancements in 2026
In 2026, we are seeing this play out across several major sectors:- Software Orchestration: Instead of you copy-pasting data between Excel and a CRM, an agent can "surf" your computer or use APIs to move data, send emails, and update records across different platforms.
- Self-Healing Systems: In cybersecurity and IT, agentic AI is being used to monitor networks and autonomously patch vulnerabilities the moment they are detected.
- Professional Services: In industries like law or finance, agents are being deployed to conduct multi-step research, verify findings across multiple databases, and draft comprehensive reports with minimal human oversight.
- The "Virtual Staff" Model: Major tech players (Microsoft, Salesforce, Google) have shifted their "Copilots" to "Agents" that act as delegated staff members rather than just writing assistants.
Challenges and "The Hype"
While the potential is massive, there are significant hurdles:- Cost & Compute: Running an agent that "thinks" through 50 steps to solve a problem uses significantly more processing power (and money) than a single chat response.
- Reliability: Agents can sometimes "hallucinate" an action (like deleting a file they shouldn't) or get stuck in logic loops.
- Governance: Many companies are struggling with how to give an AI "permission" to spend money or sign documents on their behalf.