Show Notes
AI doesn't run in a vacuum. It runs inside a world: the platforms your work lives on, the records that hold the truth, the rules about what happens next. Most AI disappointment isn't a model problem. It's that there was never a world built around it.
Season 1 of Notion in Practice was about AI inside Notion. Season 2 is about building the bigger world that surrounds it: the integrations, automations and structure that decide whether your AI has anything worth thinking about.
Tim Jeffries and Jerwin Parker open the season with the frame they use across every build: a digital operating system has four parts, the world, the work, the players and the rules. Inside that world, work splits into deterministic work, where you know the inputs and the outputs and can write the rule, and judgement work, where something has to think.
This isn't automation versus AI. It's how you build somewhere both of them can do their best work.
Build the world properly and the two compound each other: the plumbing keeps the records true, and the judgement runs on something worth reading. Skip it, and you have a clever model guessing in the dark, and paying a premium to move an email.
In this episode: Why most businesses run an archipelago of disconnected platforms, and what that costs in duplicated truth The two halves of every job (plumbing and judgement), and the three kinds of player that can now do either Onboarding a referral, split task by task, so you can see exactly where the line falls Why deterministic work is cheap, precise and loud when it fails, and why that's a feature A live look at the email worker that reads a whole Google Workspace domain and files every client email against the right project What it means when the system knows more about a job than any individual on the team How small a worker should be, and why one that does five things becomes a mess fast The run log: 10,000 records, and why observability came before the fleet Real numbers: about a dollar a meeting for deep AI follow-up, versus US$1.20 for 741 automation runs What breaks, why bridges collapse, and debugging a worker with a coding agent an hour before recording
Three actionable takeaways: Break the job into tasks before you choose which player should perform it. Label each task plumbing or judgement, then cast the cheapest player that can do it well. Keep each worker small and single-domain. Same process, several triggers is fine. Different workflows in one worker is a mess waiting to happen. Build the log before you build the fleet. If you can't see what ran overnight, you don't have a system, you have a hope.
Resources Mentioned Season 1 finale with Notion's Head of AI Notion workers / developer platform AI / Personal Agent Starter Kit: https://www.smoothops.consulting/notionaistarterkit Substack: https://smoothopsconsulting.substack.com/
Coming up this season: the businesses actually running this. Law firms, designers, film people. What worked, what didn't, and what it cost.
Who this is for: founders, operators and consultants who have the AI part working and now need the connective tissue underneath it to be reliable, cheap and visible.
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More from Notion in Practice
Flight Centre Travel Group's Matt Upton explains how his automation team uses Notion, Notion Workers and Notion AI skills at enterprise scale, and why nothing gets automated until the process behind it is fixed. Matt is Head of Automation and Innovation for Flight Centre's Asia Pacific corporate brands, leading a team of around 30 across five brands from India and the Middle East to Japan, Australia and New Zealand. Inside a 12,500-person business, the work ranges from multi-step customer onboarding automations to five-minute tasks done 500 times a day. He joins Tim Jeffries and Jerwin Parker on Notion in Practice to walk through how his part of the business made Notion its single source of truth. Information used to be spread across Confluence, Azure DevOps, SharePoint, OneDrive and local files, and nothing joined up. Flight Centre's corporate technology teams now have roughly 1,000 Notion seats. "I tell people if it's not in Notion, it doesn't exist," Matt says, and that rule is what made the change stick. Who this is for Operations, automation and technology leaders fitting Notion, Workers and Notion AI into an existing enterprise stack, and smaller teams who want the same discipline without the headcount. Why can't you automate a bad process? Because automation speeds up whatever process it runs on. Matt's team won't automate anything until it has been through a continuous improvement pass. As Tim puts it, automating a bad process just makes the chaos go faster and the mess grow quicker. How did Notion take hold at Flight Centre? Microsoft Loop opened the door. Notion had been in the business for years with only a handful of real users, and once teams saw collaborative documents working in Loop, a few people pointed out that Notion already did this at scale. How does Matt's team sync Smartsheet and Azure DevOps with Notion? With Notion Workers, small pieces of code deployed to Notion. Matt has seven or eight Smartsheets plus Azure DevOps syncing into Notion databases this way, set up in a short conversation with a coding tool and left to run without babysitting. Most Workers do one plain job like this. How do you build a Notion Worker? Start with a brief. Tim gets clear on the problem with Notion AI, then hands the brief and the Worker docs to Claude Code. His Worker was deployed and working within an hour. Do you have to migrate everything into Notion? No. Smartsheet and Azure DevOps stay where they are as the data layer, Notion becomes the context and reporting layer on top, and Workers keep the two in sync. The episode also covers Notion as "the Switzerland of AI", connecting different models and tools. Three actionable takeaways Run a continuous improvement pass before you automate anything. Leave your system of record where it is and use Notion Workers to sync the data into Notion. Start every Worker with a brief from Notion AI, then point a coding tool at the brief and the Worker docs. Resources mentioned Tim's article "You already have a digital operating system": https://smoothopsconsulting.substack.com/p/you-already-have-a-digital-operating
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