Limits – Control layer for AI agents that take real actions
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…
Limits – Control layer for AI agents that take real actions launched on February 25, 2026 with 9 votes, #1,122 of 16,627 launches that month and more than 75% of that year's launches.
What it does
FirstFlow reads every session, finds where users get lost, and guides them back in real time. Your agent gets smarter with every session.
In the maker’s words, at launch
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.…
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TrueFoundry AI GatewayDec 2025 · truefoundry.com · ▲315Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…
KastraJul 2026 · kastra.ai · ▲332Hi HN, Fernando and I built Kastra. Kastra intercepts AI agent tool calls and evaluates them against deterministic policies before they execute. We built this product to control pre- and post-inference workloads. This is aimed at developers using coding agents like Claude Code, Codex, Cursor, and OpenClaw. Kastra pushes an allow, hold, and deny decision before the action runs. You can build these policies in plain English from the web app. The interception engine evaluates the tools, targets, and parameters of every action at sub 1ms at a scale of billions of interceptions per day. We also…
20+ Claude Code agents coordinating on real work (open source)Feb 2026 · github.com · ▲53Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Cased – protect any command line tool in minutes2021 · cased.com · ▲5We’re shipping an execution model that sits between LLM code generation and autonomous agents. The LLM generates only the glue logic between two deterministic interfaces: - a UI schema the frontend knows how to render - a constrained runtime interface exposed by the backend, from specific functions like list_comments to broader primitives like a restricted http_call Both interfaces are fixed, typed, and inspectable. The LLM can’t invent UI components or backend capabilities. It only composes what already exists. This is adjacent to A2UI, but the cut is different. A2UI renders agent actions…
AI Rules & Context LibraryMay 2026 · ai-rules-context-library.terminalvelocityai.tech · ▲2Precision Context Protocols for High-Fidelity AI.
LLMs can be susceptible to a new kind of malware2023 · github.com · ▲17New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
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