RunVeto – A Simple Kill Switch for Autonomous AI Agents

Hacker News

Hey HN, I’m a software engineer with 5 years of experience, and I’ve been building autonomous agents recently using LangChain. I noticed that we are giving these agents too much "autonomy" without enough "governance". The specific problem I faced was Agent Sprawl/Recursion. A test bot got stuck in a recursive loop and almost ran up a significant OpenAI bill before I noticed and killed the process manually. So, I’m building RunVeto.xyz as a minimal governance layer—a control plane for agent guardrails. It sits between your agent and the LLM API, framework-agnostic, and integrates with one line of code. What I’m planning to implement: Hard-Cap Budgeting: Set strict token/cost limits to kill any task before it breaks the bank. Global 'Veto' Button: Pause or terminate any active agent process from a central dashboard. PII Shield: Automatic scrubbing of sensitive data (PII) before it hits the LLM. 'Chain-of-Thought' Audit: Real-time visibility into agent planning logs. I'm currently pre-MVP and using this landing page to validate the core features and find "founding developers" to guide the roadmap. I'd love to hear this community's critique. Have you encountered "recursive loops" in your own agent workflows? What’s your biggest operational nightmare with agents? The landing page has an embedded survey. I’m eager to hear your thoughts. No fluff, just safety.

Visit product View on Hacker NewsFeb 27, 2026

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, openai · Missing: mac, macos, cursor

94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

16%16% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

AgentFolio – Reputation registry for autonomous AI agents20%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AgentFolio – Reputation registry for autonomous AI agents

Hacker News1

Cryptographic passports for autonomous AI agents (Schnorr and ZK)23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Cryptographic passports for autonomous AI agents (Schnorr and ZK)

Hacker News2

Cryptographic passports for autonomous AI agents (Schnorr and ZK)37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Cryptographic passports for autonomous AI agents (Schnorr and ZK)

Hacker News1

ParsePort - A kill switch for Parse45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ParsePort - A kill switch for Parse

Hacker News17

Aidress – Coordination layer for autonomous AI agents23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Aidress – Coordination layer for autonomous AI agents

Hacker News4

Aegize – Infrastructure for autonomous AI agents36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Aegize – Infrastructure for autonomous AI agents

Hacker News1

Pauling.AI39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pauling.AI is the first autonomous AI Chemist.

Indie Hackers

Limitrum61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Policy kernel for autonomous AI agents

Product Hunt+1

AgentRunner.ai47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Build autonomous AI agents

Indie Hackers1ai

TryOpenClaw67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Cloud hosting for autonomous AI agents

Indie Hackers1$500/moai

Browse all products Analyze your launch