One AI. Endless output. Meet the automation farm behind Rarebit
We rebuilt our delivery pipeline around AI agents — research, code, content, and ops run as automations while humans direct, review, and ship — this site included. Small teams. Impossible things.
See what's running
Agents are running · 24/7|
PR reviewed & merged
The farm never sleeps
- 202PRs merged · 30 days
- 40KGem downloads
- 6Open-source gems
- 0Managers
Counted from public GitHub & RubyGems at build time. Managers: genuinely zero.
Workflows that run themselves
The automations on our own farm — the same ones we bring to every AI adoption engagement.
Lead intake & enrichment
Inbound prospects are researched, scored, and routed by agents before a human reads the email.
Content engine
Briefs become drafts, edits, and scheduled posts through a pipeline that's reviewed, not hand-cranked.
Code review & shipping
Agents triage issues, open pull requests, babysit CI to green, and reviewed PRs auto-land.
Reporting & analytics
Metrics are collected, summarized, and narrated into weekly updates nobody has to assemble by hand.
Back-office ops
Invoices, contracts, and bookkeeping run as supervised automations with a paper trail.
QA & monitoring
Synthetic checks, error triage, and incident summaries around the clock — the farm never sleeps.
AI woven into every workflow
Agent-first delivery
Every engagement starts by mapping which workflows an agent can own end-to-end — and which need a human in the loop.
Human-in-the-loop by design
Your tools, not new ones
We plug agents into the tools teams already use. The same automations that run Rarebit run our client work — no new platform to adopt.
How an engagement runs
Map the workflows
A working session over your actual queues. We leave with a list: what an agent can own end-to-end, what needs a human in the loop, and what isn't worth automating.
First automation live
One workflow, production-grade: agent on the queue, human on the approval. You watch it run before we go wider.
The farm runs
More queues, same pattern. You get the receipts — what ran, what shipped, where a human signed off — and you can take the keys any time.
The factory is running
Real automations. Real results. Right now — a look inside the farm.
- rarebit-static-v3#233Field notes: rate-limiting-and-ci-cleanup-across-repositories14 Jul
- standard_id-google#66chore(deps): bump the actions group with 2 updates14 Jul
- standard_health#39chore(deps): Bump the actions group with 2 updates14 Jul
Client work · 30 runs across 20 private systems; mixed categories; 77% green. (replayed on a 24h delay)
One operator
The leverage of an agency, without the overhead. Agents work every queue; a human signs off on what ships.
Live operations feed
Agents on every queue
Humans approve the merge
Workflow evolution · every second|
Direct the farm
Workflows are dispatched in plain language. The farm figures out the rest and reports back with receipts.
Throughput, on tap
Research, drafts, reviews, deploys — the queue drains itself. What used to take a team a week lands before stand-up.
What we're building
Agent fleet orchestration
Specialized agents on every queue — research, code, content, ops — coordinated from a single control plane.
Client-facing dashboards
Watch the automations work: a live operations feed, runs and green-rate, a trend, and what shipped this week — running now at /operations.
Self-healing pipelines
Automations that detect their own failures, retry with context, and summarize the incident when they can't.
Open-source primitives
The auth, audit, ledger, and circuit-breaker building blocks we run on are open source — use them.
Build the unusual with Rarebit
Human creativity. Amplified. Point your AI at our MCP server and tell us which workflow you'd automate first — we'll show you what the farm can do with it, the same way it made this page.
Connect your AI
