{"slug": "your-ai-agent-has-too-much-power", "title": "Your AI Agent Has Too Much Power", "summary": "A developer has released AvantGate, an open-source TypeScript library that enforces guardrails, PII redaction, budget limits, and tool-call validation in-process rather than through an external LLMOps stack. The project, whose in-process engine is called AG-Men, aims to stop prompt injection, token-loop budget drain, and unauthorized tool side effects before they reach backend APIs. The author argues that container-heavy monitoring setups such as Langfuse, Helicone, and OpenLit often cost lean teams more in maintenance and compute than the LLM calls themselves.", "body_md": "If you've connected an LLM to tool calling, APIs, or database queries recently, you know the feeling: **agents are terrifyingly unpredictable.**\n\nGiving an LLM the ability to decide its own next step means shifting from passive text generation to **active system execution**. In demos, it looks like magic: the agent reasons, picks a tool, fetches data, and loops until the task is solved.\n\nIn real life?\n\nThe traditional answer to this is the classic **LLMOps sledgehammer**: spin up Docker containers for Langfuse, Helicone, OpenLit, a vector database, ClickHouse, Redis, and an S3 bucket just to trace calls and apply basic guardrails.\n\nFor most developers and lean teams, **the monitoring infrastructure ends up costing more in maintenance and compute than the LLM calls themselves.**\n\nThere is a better way: handling security, guardrails, and cost controls **in-process**, directly at the application runtime level.\n\nWhen building autonomous workflows or multi-step agents, security vulnerabilities aren't theoretical — they fall into three clear failure modes:\n\n```\n[User / External Input]\n         │\n         ▼\n ┌───────────────┐\n │   Prompt /    │  <-- 1. Prompt Injection / Malicious Context\n │ Ingested Data │\n └───────┬───────┘\n         ▼\n ┌───────────────┐\n │  LLM Engine   │  <-- 2. Token Loop & Budget Drainage (Hallucination)\n └───────┬───────┘\n         ▼\n ┌───────────────┐\n │ Tool Execution│  <-- 3. Unauthorized Side-Effects / PII Exfiltration\n └───────────────┘\n```\n\nMeet AG-Men (avantGate's in-process engine): a tiny, sub-millisecond guardian that sits directly between your model's thoughts and your backend APIs.\n\n**[Avant Gate](https://github.com/thienban/avantGate)** runs directly in your TypeScript process.\n\nImagine a user submits an invoice query packed with an indirect prompt injection and a customer's raw credit card. Here is how the AG-Men defend your runtime step by step:\n\n`529 Overloaded`. The Shapeshifter catches the fall mid-air and swaps to a backup provider, landing the mission safely without a glitch.\nHere is how you wrap your agent runtime with `avantGate` in TypeScript:\n\n``` js\nimport { AvantGate } from 'avantgate';\n\nconst gate = new AvantGate({\n  budget: {\n    maxCostPerMinute: 0.50, // Circuit breaker: halts calls if threshold is reached\n    maxTokensPerTurn: 4000\n  },\n  pii: {\n    redact: ['email', 'credit-card'],\n    maskChar: '*'\n  },\n  fallback: [\n    'anthropic/claude-3-5-sonnet',\n    'openai/gpt-4o-mini'\n  ]\n});\n```\n\nIn an agentic workflow, you must never let the model invoke tools with unchecked parameters. You can intercept and validate both the step input and the agent's intent:\n\n``` js\nimport { z } from 'zod';\n\n// Define strict contract for the tool\nconst SearchDatabaseSchema = z.object({\n  query: z.string().max(200),\n  limit: z.number().int().min(1).max(20),\n});\n\nasync function runSecuredAgentStep(userPrompt: string) {\n  // 1. AvantGate sanitizes input (PII redaction) & checks budget in-process\n  const safeExecution = await gate.run(async (context) => {\n\n    const response = await context.completion({\n      model: 'anthropic/claude-3-5-sonnet',\n      messages: [{ role: 'user', content: userPrompt }],\n      tools: [\n        {\n          name: 'search_database',\n          description: 'Search internal records',\n          parameters: SearchDatabaseSchema,\n        },\n      ],\n    });\n\n    // 2. Validate agent tool calls before execution\n    if (response.toolCalls) {\n      for (const call of response.toolCalls) {\n        if (call.name === 'search_database') {\n          const validatedArgs = SearchDatabaseSchema.parse(call.args);\n          return await executeInternalSearch(validatedArgs);\n        }\n      }\n    }\n\n    return response.content;\n  });\n\n  return safeExecution;\n}\n```\n\nIf an injection attempts to inject `DROP TABLE` or trigger a recursive chain that blows past your token limits, `avantGate` halts the execution context before it wrecks your infrastructure.\n\n| Concern | External LLMOps Stack | In-Process Control Plane (avantGate) | \n|---|---|---|\n| **Infra overhead** | Docker, Postgres, ClickHouse, Redis | **Zero** (Pure TypeScript module) | \n| **Network Latency** | Additional network hops per call | **Sub-millisecond** (runs in memory) | \n| **Data Privacy** | Prompts/logs stored in external databases | **Zero egress** (data never leaves your runtime) | \n| **Maintenance** | Migrations, backups, version upgrades | **Update** avantGate | \n\nAgents are the future of software engineering, but building agents without deterministic boundaries is an invitation for disaster. You don't need a 5-container infrastructure stack to build secure, cost-contained AI tools.\n\nCheck out the project and docs on GitHub:\n\n👉 [Avant Gate](https://github.com/thienban/avantGate)", "url": "https://wpnews.pro/news/your-ai-agent-has-too-much-power", "canonical_source": "https://dev.to/thienban/your-ai-agent-has-too-much-power-2bah", "published_at": "2026-09-23 19:39:37+00:00", "updated_at": "2026-09-23 20:29:12.137746+00:00", "lang": "en", "topics": ["ai-agents", "ai-safety", "ai-tools", "developer-tools", "mlops"], "entities": ["AvantGate", "AG-Men", "Langfuse", "Helicone", "OpenLit", "Anthropic", "OpenAI", "Claude 3.5 Sonnet"], "alternates": {"html": "https://wpnews.pro/news/your-ai-agent-has-too-much-power", "markdown": "https://wpnews.pro/news/your-ai-agent-has-too-much-power.md", "text": "https://wpnews.pro/news/your-ai-agent-has-too-much-power.txt", "jsonld": "https://wpnews.pro/news/your-ai-agent-has-too-much-power.jsonld"}}