SuperPosts

Announcing DSPy Code: The CLI to Build and Optimize Your DSPy Code

Meet the DSPy-native CLI that embeds GEPA optimization, codebase RAG, and MCP connectivity into one slash-command workflow. Launch projects faster and ship agentic systems with production-grade confidence.

Superagentic AI Featured on UKAI Podcast: How Agentic AI Will Rewrite Businesses in the UK and Beyond

Agentic AI is rapidly becoming the next major shift in how businesses operate. Dive deep into this transformation on the UKAI Business of AI Podcast with UKAI CEO Tim Flagg.

Agent Optimization: Beyond Context Engineering

A deep dive into why agentic AI has captured attention yet remains difficult to adopt. Exploring the shift from context engineering to systematic optimization for building reliable, future-proof agentic systems.

Superagentic AI at the House of Lords Roundtable: Preparing the UK for the Agentic AI Era

Superagentic AI participated in a strategic roundtable at the House of Lords, discussing how Agentic AI will transform jobs, education, and businesses in the UK.

Super CLI: The First-ever Agent-Native CLI Built for Developing and Optimizing AI Agents

Introducing Super CLI - the first command-line interface purpose-built for the agent era. Build, evaluate, and optimize AI agents with natural language interaction and revolutionary features.

Agent Lightning vs SuperOptiX: Microsoft Enters the Race

How Superagentic AI's pioneering vision became validated by Microsoft Research. Explore how Agent Lightning and SuperOptiX compete or complement each other.

Superagentic AI Showcased Full-Stack Agentic Optimization at ODSC AI San Francisco

Superagentic AI proudly exhibited at ODSC AI West 2025 in San Francisco, showcasing our pioneering work on Full-Stack Agent Optimization. From hundreds of conversations to a packed startup pitch session, ODSC marked a milestone in our journey.

Introducing Forward Deployed Agents: A New Business Model

Discover FDA—Forward Deployed Agents, the business model designed for the agentic AI era. Instead of selling licenses, we deploy agents to learn, adapt, and deliver value.

Superagentic AI Bringing Agent Optimization to ODSC AI SF

Superagentic AI is coming to ODSC West 2025 in San Francisco to share knowledge about Agentic AI optimization. Learn about our talk on "The Optimization Layer for Agentic AI" and visit our booth #18.

Introducing SuperRadar: The Global Intelligence Radar

The first real-time, unbiased, globally comprehensive AI agent tooling radar built by developers, for developers. Track 300+ tools from 18+ countries with real benchmarks and adoption signals.

Superagentic AI Joins UK AI Trade Association to Shape the Future of Agentic AI

Superagentic AI joins UKAI, the leading voice for AI in the UK, to help shape standards, governance, and best practices for the agentic AI era.

Agentic Context Engineering: Prompting Strikes Back

Stanford's Agent Context Engineering (ACE) framework introduces a new paradigm where context evolves as a living playbook through structured feedback loops. Explore how prompting returns in a more sophisticated form to govern adaptive AI systems.

Intelligent RAG Optimization with GEPA: Revolutionizing Knowledge Retrieval

Discover how GEPA (Genetic Pareto) revolutionizes RAG system optimization through natural language reflection and genetic pareto optimization across multiple vector databases.

Codex CLI: Running GPT-OSS and Local Coding Models with Ollama, LM Studio, and MLX

Discover how OpenAI's Codex CLI revolutionizes local AI development by supporting GPT-OSS models through Ollama, LM Studio, and MLX. The first universal coding CLI.

GEPA DSPy Optimizer in SuperOptiX: Revolutionizing AI Agent Optimization Through Reflective Prompt Evolution

Discover how SuperOptiX integrates GEPA as a first-class DSPy optimizer, enabling developers to achieve dramatic performance improvements with minimal training data through reflective prompt evolution.

Optimas + SuperOptiX: Global-Reward Optimization for DSPy, CrewAI, AutoGen, and OpenAI Agents SDK

Discover how SuperOptiX integrates with Stanford's Optimas framework to provide global-reward optimization across multiple AI agent frameworks including DSPy, CrewAI, AutoGen, and OpenAI Agents SDK.

SuperOptiX Memory: A Practical Guide for Building Agents That Remember

Learn how to implement powerful memory systems in SuperOptiX agents for building AI that remembers conversations, preferences, and experiences across sessions.

SuperOptiX: A Deep Technical Dive into the Next-Generation AI Agent Framework

Explore the architectural foundations of SuperOptiX - a comprehensive AI agent framework that combines DSPy's declarative power with enterprise-grade RAG, memory, observability, and tool ecosystem.

GEPA: The Game-Changing DSPy Optimizer for Agentic AI

Discover GEPA (Genetic-Pareto Prompt Optimizer) - a revolutionary approach to prompt optimization that uses natural language reflection and evolutionary search to outperform reinforcement learning by up to 35x fewer rollouts.

3 Months of Superagentic AI: From Vision to Velocity

90 Days. 1 Framework. 16 Blogs. 2 Products. Infinite Momentum. Celebrating three months of Superagentic AI - from official incorporation to building a global movement in the agentic era.

Advanced AI Agent Observability with DSPy, MLFlow, and SuperOptiX

A comprehensive guide to production-grade AI agent observability using DSPy, MLFlow, and SuperOptiX. Learn how to monitor, debug, and optimize agent systems with seamless integration.

The Ultimate Guide to All-in-One Self-Hosted & Enterprise Model Management with SuperOptiX

Discover how SuperOptiX revolutionizes local model management with unified CLI, intelligent backend selection, and seamless integration for enterprise-grade AI deployments.

SuperSpec: Context Engineering and BDD for Agentic AI

SuperSpec unites Context Engineering and Behaviour-Driven Development (BDD) for the age of agentic AI. Learn how this declarative DSL bridges context, testing, and optimization for autonomous agents.

SuperOptiX vs Agent Bricks: DSPy-Powered Titans of Agentic AI

Comprehensive comparison of SuperOptiX and Agent Bricks - two DSPy-powered frameworks with different philosophies: engineering discipline vs automated magic.

Multi-Agent or Not: That is the Question

Exploring when to use multi-agent systems and when to avoid them in AI development. The debate around agent architecture decisions.

Context Engineering: Path towards better Agent Engineering

Building on the foundations of prompt engineering, Context Engineering is reshaping how we interact with and optimize large language models.

Rise of Agent-Driven Autonomous AI Startups

Sam Altman's vision from YC's AI Startup School and how Superagentic AI is building at the intersection of seismic AI shifts.

Software 3.0: Software is Changing Again and Again

Understanding the evolution towards natural language programming and its implications for the future of software development.

DSPy 3.0, AgentBricks, and SuperNetiX: The Future of Agent Development

Explore the latest advancements in AI agent development with DSPy 3.0, Databricks' AgentBricks, and how SuperNetiX framework is positioned.

Agentic DevOps for the Rest of Us: New Era of Intelligent SDLC

Discover how Agentic DevOps is revolutionizing software development with intelligent agents that enhance every stage of the SDLC.

Introducing AgentVectorDB: The Memory Core for Agentic AI

A powerful open-source memory architecture for AI agents, with cognitive layers for human-like memory.

From UX to DevEx to AgentEx: Designing the Future of Experience

As AI evolves from tools to autonomous agents, a new frontier of experience design emerges. Discover how AgentEx is reshaping what we build.

Introducing Superagentic AI: A New Model for an Agent-First World

Superagentic is not a startup. It's a new breed of company designed for the Agentic Era, one that builds tools for Agents, with Agents, and by Agents.

Introducing Agenspy: Protocol-First Agent Framework

A next-generation framework bringing structure, interoperability, and production-readiness to AI agents with first-class protocol support for MCP and Agent2Agent.