Recently, OpenClaw took off like a one of the greatest breakthrough in the AI. People are going crazy to setup OpenClaw to automate the tasks. All looked very good until […]
Category: Agent Optimization
Gemma 4 with MLX for Local Agentic AI at Superagentic AI
At Superagentic AI, we have published a new MLX 4-bit conversion of Gemma 4 31B IT for Apple Silicon workflows. The model is now available on Hugging Face at SuperagenticAI/gemma-4-31b-it-4bit-mlx. […]
Meta-Harness: A Self-Optimizing Harness Around Coding Agents
Stanford AI lab just released the Meta Harness paper which covers the meta harness strategy that self-optimise. Most conversations about coding agents focus on the model. People compare model quality, […]
Harness Engineering: Why It’s Suddenly the Hottest Topic in AI Agent Engineering
If you build agents, you already know the feeling: the model is smarter than ever, yet your agent still flakes on long tasks, loses context, or ships brittle code. The […]
Turbocharge Pydantic AI + SurrealDB RAG with TurboAgents and TurboQuant
Google Research released the TurboQuant, the game changing compression technique also Superagentic AI released the TurboAgents to showcase the use of the TurboQuant in the real Agentic AI systems. This post […]
Introducing Agentnetes: Self-Discovering AI Agent Swarms, On Demand
On 21 March, I attended Zero to Agent London, a hackathon hosted by Google DeepMind and Vercel. The challenge was simple: build something with agents. The result was Agentnetes, an […]
CodexOpt: Optimize AGENTS.md and SKILL.md for Codex with GEPA-Inspired Feedback
Modern coding agents are getting better fast. But for most teams, one problem remains stubbornly manual: the instructions that shape agent behavior. A repo might have an AGENTS.md. It might […]
Agent Engineering 101 at GDG London: How to Build Reliable AI Systems
Last week I had the chance to speak at GDG London Build with AI 2026. My session, Agent Engineering 101: How to Build Reliable AI Systems, is now live as […]
OpenClaw ACP: What Coding Agent Users Need to Know About Protocol Gaps
An analysis of where OpenClaw’s ACP bridge works, where it diverges from the protocol, and when it is not suitable for your coding agent workflow. OpenClaw ACP Is a Bridge, Not […]
Building Agent Memory on SurrealDB Across Modern Agent Frameworks with SuperOptiX
Agent Memory is one of the hot topic in the Agentic AI space as everyone trying to solve this for once. AI agents usually end up with a fragmented memory […]