Couple of years ago, the command line interacts used to be treated as 1990’s style of application development. However, since the launch of Claude Code, CLI has become the de-facto […]
Category: Agentic DevOps
Agent Lightning vs SuperOptiX: Microsoft Enters the Agent Optimization Race
The Battle for Agent Optimization Supremacy Has Begun How a Superagentic AI’s pioneering vision built on top of OSS research became validated by Microsoft Research, and why the race is […]
Introducing Forward Deployed Agents: A New Business Model for the Agentic AI Era
AI agents are everywhere now. Every conference, meetup, and organization is discussing them. Across industries, we are witnessing a once-in-a-generation shift driven by AI and agentic technologies. The field of […]
Codex CLI: Running GPT-OSS and Local Coding Models with Ollama, LM Studio, and MLX
Agentic coding is evolving rapidly, reshaping how developers interact with AI to generate code. Instead of being locked inside full-blown IDEs, many are moving back toward lightweight, flexible command-line interfaces. […]
Superagentic AI is Coming to San Francisco: Exhibiting at ODSC AI West 2025
We’re beyond excited to share some big news: Superagentic AI is exhibiting at ODSC AI West 2025, the #1 AI Builders Conference, in SF taking place October 28–30, 2025 at […]
GEPA DSPy Optimizer in SuperOptiX: Revolutionizing AI Agent Optimization Through Reflective Prompt Evolution
The landscape of AI agent optimization has fundamentally shifted with the introduction of GEPA as a DSPy optimizer. Unlike traditional optimization approaches that rely on trial-and-error or reinforcement learning, GEPA […]
Optimas + SuperOptiX: Global‑Reward Optimization for DSPy, CrewAI, AutoGen, and OpenAI Agents SDK
Optimization has been central to SuperOptiX from day one regardless it’s prompt, weights, parameters or compute. It began with DSPy-style programmatic prompt engineering and teleprompting as it was the only framework […]
SuperOptiX Memory: A Practical Guide for Building Agents That Remember
Modern AI agents are just limited to chatbots or prompt-in, answer-out. To feel coherent and genuinely helpful over time, they need to remember. Agent memory is the capability that lets […]
SuperOptiX: A Deep Technical Dive into the Next-Generation AI Agent Framework
SuperOptiX: A Deep Technical Dive Building Intelligent Agents with DSPy, RAG, Memory, and Observability Built by Superagentic AI • Official Website • Documentation Introduction SuperOptiX represents a paradigm shift in […]
Advanced AI Agent Observability with DSPy, MLFlow, and SuperOptiX
As AI agents become increasingly sophisticated and deployed in production environments, the need for comprehensive observability has never been more critical. While traditional monitoring tools focus on infrastructure metrics, AI […]