Hire AI automation engineers who plan for the 2am failure
Our engineers build automation the way they build software: version-controlled, with a named owner when a run fails. You interview them before anyone starts.
The short version
4 things that decide this
- 01Senior engineers only, who build the failure path before the demo path: retries, dead-letter queues, and an alert with a name on it.
- 02You interview every engineer yourself before they join, so nobody arrives as a profile picked for you.
- 03Workflows live in your repo under version control, not only inside a tool's own canvas, so a change is reviewable and reversible.
- 04They scope what should not be automated and say so, rather than forcing a process through a tool that will make it worse.
What an automation engineer actually does here
Most automation attempts stall at the same point. A person builds the version that works once, on the day they tested it. Then they leave and nobody can safely touch it.
For Little Tree Confections we built a system that turns Fireflies meeting transcripts into routed ClickUp tasks and a daily brief. It reads the live ClickUp structure instead of a hardcoded map, so routing keeps working as departments change. Error handling and execution logs keep the pipeline visible. For ZhoopZhoop, a multi-branch collision repair business, we built voice agents on Twilio, Deepgram and OpenAI. They answer inbound calls and place outbound calls to suppliers for parts quotes, with every call, transcript and quote logged to one dashboard across branches.
Neither system is a chained set of demo steps. Both were built to keep running after the engineer who built them stopped watching. Maidily runs the same way. Automated scheduling and reminders cut no-shows 75% and collected payments 4X faster. It held up under a full week of real bookings, not a single test run.
What they take off your plate
The failure path, built first
Retries with backoff, a dead-letter path for runs that still fail, and an alert that names the run. Most automation dies silently, not loudly.
Workflows under version control
Exported to your repo and reviewed like any code change, so the record of why a step exists outlives the person who added it.
A named owner when an API breaks
Third-party services change their contracts without warning. Someone on the build is accountable for noticing and fixing it, not just for shipping day one.
The call on what not to automate
A process with too many exceptions or too little structure gets worse under automation. We say so before building it, not after it breaks.
AI steps kept honest
A model reading a transcript or a document needs a check on its output. We add the validation step that stops one bad extraction becoming forty wrong tasks.
- TriggerWebhook, schedule, or call
- ValidateReject bad input early
- ActThe integration or the call
- RetryBackoff, then dead-letter
- AlertA named person hears about it
Most tools you tried to build this yourself stop at the third box. That gap is the whole job.
Automation that ran past launch day
“They were incredibly responsive.”
Mony · CEO, Maidily
How hiring works
- 01
Tell us what broke
A free call about the process, the tools it touches, and who notices when it stops. If the process should not be automated at all, we say so on that call.
- 02
Meet the engineers
We shortlist against the workflows you actually run, and you interview them yourself. Decline anyone and we go back to the shortlist.
- 03
They embed
Your repo, your tools, your standups. One engineer owns the automation and is named as the person who answers for it.
- 04
They hand over
Version-controlled workflows, credentials you control, and a person on your team who can change a step without calling anyone. Where a team would rather not carry the pager, we keep it under a service level we agree. The first 2 months of support and maintenance are free, with every build.
Stack
Automation and voice
- n8n (self-hosted and Cloud)
- Twilio
- Deepgram
- Webhooks
- Queue mode
Models and integrations
- OpenAI GPT-4o
- Claude
- Fireflies.ai
- ClickUp
- Notion
Practices
- Version-controlled workflows
- Retry and dead-letter paths
- Run alerting
- Execution logging
Bring us the process that keeps breaking
Show us the workflow and the tools behind it. The scoping call is free, and you will leave knowing whether this is an automation problem or a process problem.
01How is this different from hiring a freelancer off a job board?+
You get an engineer who has already built automation that runs unattended in production, plus a company accountable if it breaks. A freelancer hire is a hiring risk you carry alone. If our engineer is not right, we replace them.
02Our Zapier or Make workflow already broke once. Can you fix what exists instead of rebuilding it?+
Usually, yes. We audit what is running first and change it in reviewable steps rather than replacing a working automation to put our name on it. Where the tool itself is the ceiling, we say so and explain what moving off it would take.
03What working hours overlap do we get with your team?+
A daily overlap with your hours, fixed before anyone starts. Debugging a broken integration is a conversation, not a ticket, so standups and pairing happen while both sides are awake. We agree the window during scoping.
04Who owns the workflows and credentials once the engagement ends?+
Yours, from the first commit. Workflows sit in your repository and credentials sit in your infrastructure under your control, so nothing about ending the engagement requires our cooperation.
05What if our process turns out to be the wrong fit for automation?+
We say so on the scoping call, before any build starts. A process with too many exceptions or no written rules gets worse under automation. Forcing it through a tool wastes your time and ours. Where automation is not the answer, we tell you what is.
06What actually determines the price of automation work?+
How many systems the process touches, how badly each one behaves when it fails, and whether the rules were ever written down. Scoping calls are free. Every build starts with a fixed-fee Blueprint: an engineer reads your real systems and writes the plan, with a fixed price for each milestone rather than a guess. The fee is credited in full against the build, and if the plan isn't one you'd act on, you don't pay for it.
