Midlantics A2A
Observe, govern, and protect your AI agent systems
What it does
Your agents are running. Do you know what they did last night? Midlantics A2A is a governance layer for multi-agent AI systems — four modules that work independently or together: → Observe — tracing for agent action. Open source. → Policy — YAML rules that block or flag agent. → Approval — human gate for high-risk actions. Notified email. → Firewall — scans every message for prompt injection and PII before it reaches your LLM. Under 2ms, runs locally. VPC-native. No data leaves your perimeter.
Does the same job
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Much of my work right now involves complex, long-running, multi-agentic teams of agents. I kept running into the same problem: “How do I keep these guys in line?” Rules weren’t cutting it, and we needed a scalable, agentic-native STANDARD I could count on. There wasn’t one. So I built one. Here are two open-source protocols that extend A2A, granting AI agents behavioral contracts and runtime integrity monitoring: - Agent Alignment Protocol (AAP): What an agent can do / has done. - Agent Integrity Protocol (AIP): What an agent is thinking about doing / is allowed to do. The problem:…
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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