Compare/AI Subroutines vs Hermes Agent

AI tool comparison

AI Subroutines vs Hermes Agent

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

A

Automation

AI Subroutines

Record a browser task once, replay it 500x at zero token cost

Ship

75%

Panel ship

Community

Free

Entry

AI Subroutines from rtrvr.ai are a new automation primitive: you record a browser task once (a form submission, a LinkedIn connection, a CRM update), and that recording becomes a deterministic, callable tool that AI agents can invoke with different parameters — without spending tokens on every run. Unlike Playwright, Browser-Use, or other out-of-process solutions, Subroutines execute entirely inside your browser tab, inheriting your live session cookies, CSRF tokens, and signed headers automatically. The technical approach is clever. During recording, the system captures network requests and DOM interactions, then ranks captured requests to identify the actual API call (filtering out analytics and telemetry). Replay-hostile identifiers are stripped while stable endpoints are preserved. The result is a script that runs in your browser context — no session rebuilding, no key extraction, no proxy rotation needed. The AI handles parameter selection; the script handles execution. The business case is clear for outreach and operations teams: bulk LinkedIn campaigns, CRM mass-updates, scraping pipelines, and form submissions that would cost hundreds of tokens per run instead execute as cheap deterministic scripts. The model positions Subroutines as the "function call" layer beneath AI agents — the actions that don't need intelligence every time they fire.

H

AI Agents

Hermes Agent

Self-improving AI agent that learns new skills and runs on 200+ models

Ship

75%

Panel ship

Community

Free

Entry

Hermes Agent is an open-source autonomous agent from Nous Research that actually gets better the more you use it. After completing complex tasks, it writes new skills to its own library — essentially bootstrapping its own capabilities over time. It's model-agnostic (200+ models via OpenRouter), self-hosts cleanly on a $5 VPS, and spans 6 terminal backends including SSH, Docker, and serverless Modal. The multi-platform messaging integration is genuinely useful: Telegram, Discord, Slack, WhatsApp, Signal, and email all pipe through a single gateway, so your agent can respond across every channel without separate bots. Persistent FTS5 memory means it remembers context across sessions. With 26k stars and 271 contributors already, this is moving fast. The one-line curl install and automatic project scaffolding make the onboarding friction unusually low for a project of this ambition.

Decision
AI Subroutines
Hermes Agent
Panel verdict
Ship · 3 ship / 1 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Free tier available (paid plans TBD)
Free / Open Source (MIT)
Best for
Record a browser task once, replay it 500x at zero token cost
Self-improving AI agent that learns new skills and runs on 200+ models
Category
Automation
AI Agents

Reviewer scorecard

Builder
80/100 · ship

The 'record once, replay many' pattern solves a real cost problem in agent pipelines. The in-browser execution model is clever — you get auth context for free instead of fighting with session management. This is the kind of tool that drops into existing workflows without requiring a rewrite.

80/100 · ship

Model-agnostic + multi-platform messaging + self-hosted for $5/month is the trifecta I've wanted from an agent framework. The skill-creation loop is genuinely novel — most agent frameworks require you to hardcode tools, but Hermes writes them from experience. The curl installer working out of the box sealed it for me.

Skeptic
45/100 · skip

Browser automation that runs inside your session is exactly the attack surface that malicious sites exploit. Subroutines executing in-tab with full cookie access means a compromised script could do real damage. The 'zero token cost' claim also obscures that you still need LLM calls for parameter selection — the savings are real but overstated.

45/100 · skip

An agent that writes its own skills is also an agent that can write broken or insecure skills, and Nous Research's security track record is thin. 271 contributors on a project with autonomous code execution is a supply-chain red flag. I'd audit extensively before giving this access to anything sensitive.

Futurist
80/100 · ship

This is the 'compilation' step for agentic workflows — moving from 'LLM decides every click' to 'LLM selects a pre-compiled action.' That separation of concerns (intelligence vs. execution) is how you scale agent operations from one-off demos to production pipelines. The pattern will be widely copied.

80/100 · ship

This is the closest thing to a general-purpose agent OS that exists in open source right now. The self-improving skill loop is a primitive form of recursive self-improvement — not AGI, but the architecture patterns being proven here will matter enormously in 2-3 years.

Creator
80/100 · ship

For creators doing outreach, social posting, or newsletter campaigns, this is genuinely transformative. Recording a campaign action once and letting AI handle personalization at scale is the efficiency unlock that makes solo creator businesses actually viable at volume.

80/100 · ship

Having one agent respond across every messaging platform with persistent memory means I can actually run creative workflows — briefing docs, newsletter drafts, social scheduling — without babysitting separate bots per channel. The cron scheduling for recurring automations is the cherry on top.

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