As AI systems tackle increasingly complex problems, single-model architectures are starting to show their limits. Agent Mesh introduces a new approach: a network of specialized AI agents that collaborate dynamically to achieve shared goals. Instead of relying on one generalist model, an agent mesh distributes work across agents focused on reasoning, data retrieval, execution, validation, […]

APIs built with human developers as primary users are increasingly unsuited for AI agents, which don’t share human intuitions or access to “tribal knowledge.” Legacy APIs often rely on undocumented behaviors, inconsistencies, or implicit expectations that humans can compensate for—but AI agents cannot. Problems with Legacy APIs What Needs to Change A very detailed analysis […]

The traditional approach to distributed computing—built around frameworks like MapReduce and microservices—is ill-suited for the demands of modern AI, especially large language models (LLMs). The remarkable cost efficiency achieved by DeepSeek in training its LLMs (at a fraction of the cost of industry giants like OpenAI) underscores a fundamental mismatch between legacy infrastructure and the […]

🔍 What is AI in CyberSecurity? AI in cybersecurity involves analyzing vast and varied data—log files, network traffic, user behavior, device activity, cloud services—to detect anomalies or threats, then translate them into actionable insights. 🚀 How It Works 🛠️ Key Use Cases 🏆 Benefits of AI in Cybersecurity ✅ Best Practices for Adopting AI 🔮 […]

AI agents are expected to replace many jobs in the near future, according to forecasts from McKinsey and Goldman Sachs. However, these agents are not as all-powerful as they may appear. In reality, they function more like specialized assistants—similar to travel agents—who perform specific tasks well when given clear, detailed instructions. Large Language Models (LLMs) […]

🧠 Understanding Agentic Workflows Agentic workflows represent a paradigm shift in software development, particularly within microservices architectures. Unlike traditional workflows, which rely on predefined, static sequences of operations, agentic workflows leverage autonomous AI agents to dynamically manage tasks and processes. These agents can make decisions, adapt to changing conditions, and collaborate with other agents to […]

Generally, AI is non-deterministic software, unlike most software, which typically produces deterministic outcomes, meaning the result is predictable: if this happens, then that follows. This predictability allows for unit tests and clear functional requirements. If the software behaves unexpectedly, we file a bug and revise the code until it behaves as expected. In contrast, Generative […]

Serverless has revolutionized the tech industry in recent years, leveling the playing field by providing organizations with instant access to the same resources. This has given startups and smaller businesses a competitive edge, allowing them to move quickly due to fewer established processes compared to larger, more traditional organizations. Serverless technology facilitates this agility. The […]

Microservices application typically contains numerous autonomous services that follow continuous delivery pattern. Each service is part of the application and is placed in a separate repo with an independent ci/cd pipeline. Each repo is tagged with its independent version, which is then mapped to the application version and documented to keep track of the application […]

The systems are becoming more complex as the adoption of microservices and distributed cloud architecture grows. Though there are a wide range of tools to help build robust and fault tolerant systems, ultimately this complexity is making it difficult to predict failures. Failures are always a burden on finances. One method for identifying failures before […]