Notion AI Custom Agents: What You Actually Pay For + The 3 Layer Guide (Agents, Skills, Guides) E09

Notion AI Custom Agents: What You Actually Pay For + The 3 Layer Guide (Agents, Skills, Guides) E09

In Episode 9 of Notion in Practice, Tim Jeffries and Jerwin Parker tackle the question on every Notion power user's mind: what will custom agents actually cost and is it worth it? With usage-based pricing for Notion custom agents rolling out, Tim and Jerwin discuss what stays free (personal agent / Nosy, enterprise search, meeting notes) and what gets metered (custom agents). They walk through the three-layer model Smooth Ops uses to architect AI inside Notion: Agents, Skills, and Guides and why this structure keeps costs predictable while making your AI dramatically smarter. In this episode: * What you actually pay for in Notion AI (and what's free) * The three-layer model: agents as orchestration, skills as SOPs, guides as reference material * A real example: how Tim's calendar-sync custom agent costs ~$150 AUD/month and why it earns its keep How picking the right LLM (Haiku vs Sonnet vs Opus) per agent changes your bill * Why clean databases are the non-negotiable foundation before any AI work * When to reach for Claude + Notion MCP instead of staying inside Notion * Meet Al, Tim's chief-of-staff personal agent, and how he handles every domain via dynamic skill-matching * Why every skill needs an owner and a verification cadence: governance, not just authoring Three actionable takeaways: 1. Start with your data structure: clean, well-named databases are the foundation everything else relies on. 2. Set up your personal agent (Nosy) with strong custom instructions before you build a single custom agent. 3. Build skills as separate, reusable pages and keep custom agents lightweight: they should orchestrate, not contain logic. Who this is for: New, Intermediate-to-advanced Notion users, consultants and operators who want to use Notion AI without burning through credits: especially anyone planning their custom agent strategy ahead of usage-based pricing. 🎁 Tim's special offer for listeners: If you're struggling to set up your personal agent instructions, reach out to Tim directly: he's giving away a free instructions starter kit to anyone who asks. (Mentioned around the takeaways at the end of the episode.) 📚 Further reading: Tim's Substack article Structure is the Strategy: open.substack.com/pub/smoothopsconsulting [http://open.substack.com/pub/smoothopsconsulting] 👉 Subscribe wherever you get your podcasts and on YouTube @NotioninPractice for weekly real-world Notion + AI workflows.

Lawyer to Ops Lead: Building an Agent-Powered Startup | George Turnbull, Jerwin Parker, Tim Jeffries

What happens when a former lawyer becomes Head of Operations at a scaling startup and decides to build an entire ops function using Notion agents? In this episode, George f [https://au.linkedin.com/in/george-turnbull-b712689a]rom Calcs joins Tim and Jerwin [https://au.linkedin.com/in/jerwinparker] to share how she's using Notion AI agents to automate document hygiene, recruitment, onboarding, OKR reporting, and even Slack channel governance. After scaling Linktree from 40 to 160 people on Notion, George knows what foundational building blocks matter and why they matter even more in the age of AI. We dig into: 🔹 The AskOps Agent - A Slack-based bot that answers operational questions, surfaces missing policies, and tracks how often questions are asked so the team knows where documentation gaps exist. 🔹 Database Hygiene at Scale - How George uses verification agents that run weekly checks on document ownership, last-edited dates, and software renewals - so nothing falls through the cracks. 🔹 Recruitment Without a TA Tool - Calcs runs its entire applicant tracking process inside Notion: Zapier brings in applications, a Notion agent manages candidate progression, and all communication is captured in one profile. 🔹 OKR Summaries on Autopilot - A fortnightly agent scans the scorecard, summarises what's on track and off track, and posts the update to Slack - a task George used to do manually in slide decks. 🔹 The Agent Org Chart Problem - As the number of agents grows, George shares what's missing: visibility into what agents are doing, better failure notifications, and a way to see the orchestration layer. 🔹 AI Tool Sprawl - Notion agents vs. Slack AI vs. Claude vs. Zapier: how a small company decides where to build without paying for everything. Three Actionable Takeaways: 1. Build agents to meet people where they work - if your team lives in Slack, bring Notion's power to them there. 2. Invest in your foundational context layer first - clean databases with ownership, verification, and hygiene agents make everything else (including AI) work better. 3. Experiment now, structure later - the free agent window is closing, so build, test, and learn before pricing forces discipline. Resources Mentioned: Notion [https://www.notion.so/] · Calcs [http://calcs.com/] · Linktree [https://linktr.ee/] · Slack [https://slack.com/] · Linear [https://linear.app/] · Claude [https://claude.ai/] · Zapier [https://zapier.com/] 🎧 This episode is for ops leaders, founders, Notion power users, and anyone building AI-powered workflows in a small team.

How a Deep Tech Venture Capital firm Runs on Notion (Darja Nelson) | E07 Tim Jeffries, Jerwin Parker

In Episode 7 of Notion in Practice, Jerwin and Tim chat with Darja Nelson, [https://nz.linkedin.com/in/darja-nelson] Operating Partner at Bridgewest Ventures: New [https://bridgewest.ventures/] Zealand's leading deep tech venture capital firm that invests in early-stage deep tech companies. Darja shares how her team of six uses Notion to manage a pipeline of 300+ pitches a year, support five active portfolio companies, and produce investor reporting all while she spends six to seven hours a day in meetings. This episode covers the real, practical impact of AI meeting notes, how custom agents are starting to automate pipeline updates, and why the skills that matter for new hires are fundamentally changing. Three Actionable Takeaways 1. Own your system as a team: Don't treat your Notion workspace as a one-off project. Hold regular sessions to review, improve, and build onboarding guidance - the team that owns the system gets the most out of it. 2. Hire for wisdom, not just analysis: AI handles the traditional grind. Look for people who can critically evaluate output, ask the right questions, and make good decisions with the information AI surfaces. 3. Make meetings your institutional memory: Store meeting notes centrally, make them searchable, and use custom agents to automate follow-up - so nothing falls through the cracks, even on six-call days. If you enjoyed the episode, subscribe for more real-world Notion workflows. More deep dives into custom agents, onboarding workflows, and how teams are building governance around their Notion systems. Resources mentioned * Tim Jeffries' article: Why Your Notion Workspace Design Matters for AI [https://www.smoothops.consulting/Structure-is-the-Strategy-Notion-AI-Retrieval-and-Why-Your-Workspace-Design-Matters-33ed8a5c5fec4a4487132640a541429b] * Notion AI Meeting Notes * Notion Custom Agents * Notion Skills (new AI feature in workspace settings) * Hosts * Jerwin Parker Roberto: LinkedIn: http://www.linkedin.com/in/jerwinparker [http://www.linkedin.com/in/jerwinparker] * Tim Jeffries: LinkedIn: https://au.linkedin.com/in/timjeffries [https://au.linkedin.com/in/timjeffries]

Notion Custom Agents Deep Dive: Triggers, Permissions, and Real Use Cases

Custom Agents are the next step for Notion AI: not just answering questions, but running real workflows in the background. In this hosts-only deep dive, Tim Jeffries and Jerwin Parker break down what Custom Agents are, how they differ from the “regular” Notion AI experience, and how to think about implementing them safely in a team. Tim and Jerwin walks through the Custom Agents interface, including triggers, activity logs, permissions, and integrations, then shares a set of practical agents Smooth Ops has been using to reduce admin overhead and increase project context. IN THIS EPISODE, WE COVER * Custom Agents vs Notion AI: what changes when AI can run autonomously * Personalized instructions and playbooks: the foundation for consistent outputs * Triggers: schedule-based runs, property-based triggers, and Slack/Calendar/Mail possibilities * Permissions and governance: what the agent can access, and how sharing agents can extend access * Real examples (Tim): meeting follow-up, Slack context capture, email-to-CRM logging, lead intake automation, and project status updates * Real example (Jerwin @ TrustOnCloud): a meeting triage custom agent for a marketing leader to capture actions, track accountability, and keep momentum after internal calls * Ambient context: why Tim rebuilds a daily context page overnight so AI stays “stateful” across conversations THREE ACTIONABLE TAKEAWAYS 1. Takeaway #1: Start with personalized instructions + playbooks before you build agents. Build a reliable “baseline assistant” first, then turn repeatable playbooks into agents once you trust the workflow. 2. Takeaway #2: Treat agents like employees: define the job, grant minimal access, then audit regularly. Good outcomes come from clear instructions, tight permissions, and reviewing activity logs. 3. Takeaway #3: Use agents to capture context automatically (meetings, Slack, email) so work stays “stateful.” The more structured context lives in Notion, the less the AI has to guess, and the better the outputs become. * Hosts: * Tim Jeffries — Website [http://smoothops.consulting] · LinkedIn [http://linkedin.com/in/timjeffries] · Instagram [https://instagram.com/timjeffries] · YouTube [https://youtube.com/@smoothopsconsulting] * Jerwin Parker — Website [https://jerwin.notion.site] · LinkedIn [http://linkedin.com/in/jerwinparker] · Instagram [https://www.instagram.com/jerw.in/] · YouTube [https://youtube.com/@jerwinparker] * Resource Tim mentioned (Episode gift): https://www.notion.com/templates/how-to-build-ai-playbooks [https://www.notion.com/templates/how-to-build-ai-playbooks] WHO THIS IS FOR Operators, consultants, founders, and Notion power users who want to automate repeatable work, reduce cognitive load, and keep project context up to date without relying on memory. Subscribe for more practical episodes on building real systems in Notion, with workflows you can copy and adapt.

Why AI Won’t Kill Consulting (But It Will Kill Busywork): Nick Tucker | Tim Jeffries & Jerwin Parker

In Episode 5 of Notion in Practice, Jerwin and Tim sit down with Nick Tucker. He is an experienced management consultant, psychologist and people leader, driven by a desire to make the world a better place to work. Nick shares how he uses Notion as the operating system for his consulting practice: a “second brain” that captures context, keeps the admin tidy, and makes work easier to deliver with partners. This is not a hype episode. It’s a practical look at where AI is genuinely creating leverage, what still needs human judgment, and why adoption remains the hard part. WHAT WE COVER * Nick’s background (strategy, culture change, organisational psychology) and how he discovered Notion * Notion as a “second brain” that “keeps receipts”: admin + context + delivery * Why AI challenges the traditional consulting leverage model (and what replaces it) * The 4 workflow shifts: project management, meeting notes, pipeline/commercials, and IP management * Using AI for feedback/coaching via custom rubrics (discovery calls) * Adoption is still the hardest part: tools get deployed, but usage stays low * AI as a thinking partner (mental models + frameworks like Pyramid Principle) * What surprised Nick: inconsistency (“hungover graduate” days) * What’s next: “get the reps in” and keep feeding context as the system grows TOP TAKEAWAYS (FROM THE CONVERSATION) 1. AI changes the consulting advantage: The differentiator moves from producing repeatable “deck work” to using good judgment. The real skill is deciding what’s useful from endless AI output. 2. Notion works best as an operating system (not another tool): A flexible “second brain” that keeps your delivery, context, and admin in one place, built around how you think and work. 3. Four workflow upgrades drive leverage: Project management (single source of truth), meeting capture (searchable conversations), pipeline/commercial tracking (accountability), and IP management (drafting guides faster). 4. Use AI for feedback and coaching, not just tasks: Call-review rubrics and automatic retros help people improve without the social friction of “I’ve got feedback for you.” 5. Adoption is the real bottleneck: The tools can be there, but if people do not use them, nothing compounds. Systems that make work easier win adoption. RESOURCES MENTIONED * Nick Tucker on LinkedIn: https://au.linkedin.com/in/nick-tucker- [https://au.linkedin.com/in/nick-tucker-] * Buoyant Partners (company): https://www.buoyant.partners/ [https://www.buoyant.partners/] * Hosts * Jerwin Parker Roberto: LinkedIn http://www.linkedin.com/in/jerwinparker [http://www.linkedin.com/in/jerwinparker] * Tim Jeffries: Instagram https://au.linkedin.com/in/timjeffries [https://au.linkedin.com/in/timjeffries] * AI call-review rubrics (concept): https://smoothopsconsulting.notion.site/AI-Thinking-Partner-Playbook-Setup-Guide-1c0149969f724589a840a541fa434a75?source=copy_link [https://smoothopsconsulting.notion.site/AI-Thinking-Partner-Playbook-Setup-Guide-1c0149969f724589a840a541fa434a75?source=copy_link] (AI Thinking Partner Playbook, Setup Guide) * Pyramid Principle (framework mentioned)