03B·Automations
The workflow your team runs every day, wired up cleanly.
Focused automations built around the tools and data you already have. AI-assisted where AI genuinely helps, plain code where it does not. Small, deliberate, and durable.
GoAlgo Studio
Sheet 03B of 06
Rev 2026-07
What ships
The artifacts you get back.
- →A working automation running against your real systems, not a demo
- →Clear integration with the tools you already use, email, sheets, CRM, ERP, chat, ticketing
- →AI in the loop where it earns its place: classification, extraction, drafting, routing
- →Human-in-the-loop checkpoints for anything below a confidence threshold you set
- →Logs, retries, and a small dashboard so failures are visible, not silent
- →A short runbook so your team can own it after handoff
The sprint shape
How the engagement runs.
- 01Map the workflowOne session with the person who runs the workflow today. The engineers watch, ask, and write it down.
- 02Prove the risky bitsThe one or two steps most likely to break, usually the AI-driven ones, get built and tested first.
- 03Wire the endsIntegrations to your systems. Auth, rate limits, retries. Boring, but this is where automations quietly die.
- 04Pilot on real workThe engineers run it beside your team for a week. Everything is logged. Every miss becomes a fix.
- 05Hand offRunbook, dashboard, on-call cheat sheet. This team does not become a permanent dependency.
Typical duration
1 - 4 weeks
How it's scoped
One 45-minute scoping call. I name the outcome, the shape, and the fee on that call. Written SOW within 48 hours.
Not in this engagement
Explicitly out of scope.
- Rebuilding your core systems (that is a build engagement)
- Long-term SRE / operations of the automation
- One-off scripts with no observability, those don't ship
- Automations that replace human judgment where human judgment is the point
Common questions
FAQ.
- How do you decide when to use AI versus plain code?
- If the step needs judgment on unstructured input, read this email, classify this ticket, extract these fields from a scan: AI earns its place. If the step is deterministic, move this row, call this endpoint, format this date, the engineers use plain code. Mixing them is the point of the engagement.
- Do you use no-code tools like Zapier or n8n?
- When they are the right answer, yes. For anything with real volume, error handling, or custom logic, the engineers usually reach for code, and I tell you honestly which fits and why.
- What if the workflow is not well-defined?
- That is what step 01 is for. Half the value of an automation engagement is forcing the workflow to be written down clearly, before it is coded. Sometimes the clarity alone is enough.
- Who runs the automation after you leave?
- Your team. You get back a runbook and a dashboard. If a step breaks, the log tells you what and where. Follow-up is available on a fixed-fee basis if you want it, but the automation is not this team's dependency.