// Automation Stack — 04
Ecommerce businesses are drowning in manual ops and random AI plugins. I deploy open-source agents — Hermes Agent by Nous Research, OpenClaw, and Grok — inside your own infrastructure, with the guardrails that keep your data yours. Fully automated operations. Zero leaked secrets.
// A — The stack
Not one vendor — a stack. Each tool does what it's genuinely best at, wired together with an orchestration layer that keeps every action logged, gated, and reversible.
HERMES — MESSENGER OF THE GODS · NOUS RESEARCH
HERMES AGENT
NOUS RESEARCH — OPEN SOURCE (MIT)
A self-hosted AI agent with persistent memory, scheduled tasks, and a messaging gateway (Telegram, WhatsApp, Discord, email). It lives on YOUR infrastructure, learns your store, and runs the operational loop — briefings, follow-ups, catalog sweeps — around the clock.
OPENCLAW
OPEN SOURCE — SELF-HOSTED GATEWAY
An open-source personal-agent gateway that connects your automations to the chat apps you actually live in. Approve refunds from WhatsApp, get stockout alerts on Telegram, run the whole store from your pocket — without handing data to another SaaS.
GROK
xAI
Frontier reasoning with live signal from X. Used inside the stack for social-commerce monitoring, competitor movement, and support escalation drafts — always behind the same guardrails as every other model step.
SAMCTL ORCHESTRATION
BUILT IN-HOUSE — YOURS TO KEEP
The custom orchestration layer around the agents: queues, idempotency keys, retries, audit logs, and human review gates. The agents are the talent; this is the discipline that makes them safe to unleash on a real business.
INDEPENDENCE NOTE — Hermes Agent is an open-source project by Nous Research; OpenClaw and Grok are maintained by their respective teams. Samcommerce.dev is an independent practice and is not affiliated with or endorsed by any of them. I deploy and engineer around these tools because they're the best ones for the job.
// B — Recipes
Concrete workflows, shipped and running — each one a human gate away from touching money or customers.
01Order & fulfillment ops
New order → agent validates the address, drafts the label, updates status, flags anomalies. Weird orders get a human gate; normal ones never touch you.
02Nightly catalog QA
Every night the agent sweeps the catalog: missing fields, weak images, price drift, broken variants. You wake up to a reviewable fix-list — not customer complaints.
03Support triage & drafts
Inbox and chat messages classified, answered from your actual policies, refunds escalated with context. You approve; the agent does the typing.
04The morning briefing
Sales, stock risk, overnight incidents, ad movement — compressed into one message before your first coffee. Hermes remembers what you asked about last time.
05Webhook & inventory watch
Stuck webhooks, sync failures, stockout risk, price mismatches — detected and alerted before customers ever see them.
06Marketing ops
Campaign drafts from real product data, feed hygiene checks, review responses queued for approval. Your voice, your policies, ten times the throughput.
// C — Safety model
Every business is bolting on AI tools; almost none are checking where their data goes. This is the part most implementations skip — and the reason mine are safe to run on a real business.
01Self-hosted first
Hermes runs in your container, on your server — the same isolation discipline as every other stack I operate. Your ops brain is not a browser tab on someone else's cloud.
02Least-privilege credentials
Agents get scoped API keys, read-only by default, elevated per workflow with expiry. An agent can see what its job needs — nothing else.
03Data boundaries
Customer PII is redacted before it reaches any hosted model. Where the data can't leave, local models do the step. The stack works for you — it doesn't feed you to it.
04Human gates on consequences
Anything that spends money or contacts a customer stops at a confirmation. The agent prepares; you decide. No exceptions.
05Audit everything
Every automated action is logged against the record it touched — replayable, searchable, explainable. 'Why did it do that?' is a query, not a mystery.
06Cost caps & evals
Model steps run with evaluation sets and hard spending limits. 'It seemed smarter' is not a deployment criterion.
// D — Engagement
// E — In production
The discipline behind these agents isn't theoretical — it operates production systems today.
// F — FAQ
It's open source (MIT, by Nous Research), self-hosted, has persistent memory, and connects to the channels you already use. Your store's operations brain runs where your data lives — not on a subscription tab.
That's the first thing the audit answers. The stack defaults to redaction before any hosted model call, scoped credentials, and local models where the data can't leave. Most stores using random AI plugins today are far more exposed than they think.
No. Agents bolt onto Shopify, WooCommerce, or custom platforms through APIs and webhooks. Your store keeps selling; the operations layer around it gets automated.
Scoped per store after the audit — the pilot is deliberately small so you see real automation on real data before committing to the full deployment.
// Engage
I'll map where your store leaks data to random AI tools, where the real automation upside is, and what a Hermes-powered pilot would look like — in plain language, on your actual stack.