In enterprise data analytics, querying relational warehouses has traditionally required specialized SQL knowledge or static business intelligence dashboards. With modern generative AI, organizations are transitioning to autonomous Text-to-SQL data agents capable of translating ambiguous business questions into valid SQL queries, …
Handling Tool Calling Errors, Retries, and Fallbacks in Autonomous AI Agents with Python
In autonomous artificial intelligence systems, Large Language Models (LLMs) do not operate in a vacuum. To perform real-world work, agents rely on tool calling (also known as function calling) to inspect production databases, execute shell commands, retrieve live API payloads, …
Tool Calling in AI Agents: How LLMs Execute Real-World Actions in 2026
Introduction: Why Tool Calling Is the Backbone of Modern AI Agents
Large Language Models (LLMs) are incredibly powerful at understanding and generating text. But here’s the truth — text alone isn’t enough. If an AI agent can only talk …
Harnessing LLMs and Generative AI: The Rise of Autonomous AI Agents
Understanding the Rise of AI Agents
Artificial Intelligence (AI) agents, powered by advanced algorithms and large language models (LLMs), are rapidly becoming a driving force behind innovation in fields like software development, customer service, and more. These autonomous systems perform …