Agentic AI
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Beyond Prompting: Enter Agentic AI
The rise of Agentic AI has ushered in a new era of productivity gains when it comes to software development and other process automation. Large Language Models (LLMs) are designed to read natural language prompts, analyze them using the given context, and provide some output using its training data. The training data is not real-time and does not have rule-based training. Therefore, it cannot be reliably used for traditional programming which is highly structured, deterministic and verifiable. Sure you can generate some code samples using LLMs, but the accuracy cannot be assessed without human intervention.
Some Business Use Cases for Agentic AI
Real-time log monitorin
IoT sensor data, website logs etc.
Supply Chain Order Management
Check inventory levels and place orders with suppliers based on predefined rules.
Online Fraud Prevention
Monitor refund transactions on your payment gateway to detect anomalies.
Unit Testing Software
Once the code has been written, use Agentic AI to automate Unit Testing
Data Ingestion
Validate data for batch or stream processing
For organization performing lots of manual repititive tasks, performance gains using Agentic AI is real and worth exploring.