Systems | Development | Analytics | API | Testing

With Deloitte predicting that 25% of companies using Generative AI will launch agentic AI pilots or proofs of concept in 2025, is your testing strategy ready for the agentic revolution? This highlights the pace at which the modern software development industry, already demanding continuous operational speed improvements, heightened efficiency, and superior product quality, is turning to advanced AI.

AI has become the talk of the town nowadays, right? There are tons of AI tools available for different tasks, and new advancements are coming up daily like vibe coding. But how do you actually do vibe coding? Or how do you try out these models? You could use tools like ChatGPT or Claude, but they come with restrictions, and you often need to pay to access full features. What if you don’t want your data to become part of their training models? That’s where open source coding models come in.

The workplace is on the brink of a transformation unlike anything we’ve seen before. With the rise of AI agents—autonomous software entities capable of executing tasks, making decisions, and even optimizing workflows—the way we define work itself is evolving. While automation and AI-assisted processes have been gradually reshaping industries, the concept of the agentic enterprise takes this a step further, shifting from AI as a tool to AI as an active participant in business operations.

Even in light of recent return-to-work mandates, it’s clear that the way we work has changed. Remote and hybrid teams are now the norm, and while this shift has brought flexibility, it’s also introduced unique challenges for AI and ML teams. One of the most pressing issues is ensuring seamless access to the compute resources needed to run machine learning workloads.

In the rapidly evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? According to insightsoftware and Hanover Research’s recent Embedded Analytics Report, developers see AI as the most important trend of the next five years.

Artificial intelligence (AI) is no longer a futuristic concept—it’s here, and it’s transforming the way enterprises operate, innovate, and compete. From automating workflows to delivering data-driven insights, AI is reshaping industries and creating new opportunities. But as AI becomes more integrated into our lives and businesses, a critical question arises: Who owns and controls the AI agents that are increasingly making decisions on our behalf?

AI agents are all the rage these days. Poised as the next big thing after Gen AI…is there substance underneath all the hype? The answer is a resounding yes. For instance, the 2024 State of AI Agents report revealed that 51% of AI professionals are already using AI agents, while 78% of enterprises and mid-sized companies have active plans to put AI agents into production. However, doing this successfully requires paying attention to certain key factors.

We’ve all heard of digital assistants that perform specific tasks based on our requests. But what if these digital assistants could operate with ever more autonomy? While this requires an intelligent system, such as an autonomous AI agent, capable of recognizing opportunities and acting on them without constant human input or explicit instructions, the good news is that organizations no longer need specialized developers to build their own agents.