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I've been working on a new programming language for AI agents. I would love your input on what makes programming languages good for AI agents, especially syntax, compiler, and tooling that could help AI agents write code. What makes Sigil good for coding agents? I've turned conventions into compiler rules whenever possible. The compiler owns the canonical printer and every AST has one accepted textual representation. For almost every syntax feature I tried to save tokens. Order and naming conventions are enforced. No more "I think this argument is important so it should come first." Most…
Apr 2026
- 23LC
Prompt instructions like 'never do X' don't hold up in production. LLMs ignore them when context gets long or users push hard. Limits sits between your agent and the real world. Every action — database writes, API calls, refunds — gets intercepted and checked against your rules before it executes. Deterministically. No LLM involved in enforcement. Three modes: Conditions: hard rules on structured data Guideance: validate LLM output before it reaches the user and give the agent chance to reason and retry Guardrails: scan for PII, toxicity, prompt injection etc One line to integrate: npm…
Feb 2026 · limits.dev
- 24TM
AgentRQ is a (optionally) human-in-the-loop, self learning closed loop task manager for agents. Agents can create and schedule tasks for themself and work on them on their own schedule. In high level it comes with one supervisor MCP that controls workspaces(worker agents) and unlimited number of isolated workspace MCPs (self learning agents). Each workspace/agent has a mission/persona for the agent. And self-learning-loop note. I am using it about 6 weeks in production, and completed more than 500 tasks. I just released the opensource version(as is in production) under Apache 2.0…
Apr 2026 · github.com
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