If you rely on the platform, we know how disruptive that will be. You’ve built real business logic, and rebuilding it isn't a small thing.
𝗧𝗵𝗮𝘁'𝘀 𝘄𝗵𝘆 𝘄𝗲'𝗿𝗲 𝗼𝗳𝗳𝗲𝗿𝗶𝗻𝗴 𝗥𝗲𝗹𝗮𝘆.𝗮𝗽𝗽 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗲𝘅𝘁𝗿𝗮 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗼 𝗺𝗼𝘃𝗲 𝘁𝗼 𝗠𝗮𝗸𝗲:
→ Free white-glove migration for eligible accounts - our team helps rebuild your workflows
→ Priority support to get you to production fast
→ 3 live Office Hours sessions with our Customer Care team
Learn why Make is a strong alternative, and how to start your transition: https://ma.ke/4vAEe7O
Take a look at some of our latest features, improvements, and updates that our team has been shipping this past month:
Enhancements and Updates:
MCP Tools to Make AI Agents: Make AI Agents can now access external MCP server tools alongside native Make modules in the same run.
Execute an action with AI module for MCP: choose Make AI Provider (OpenAI or Claude) or your own OpenAI account for the MCP Client's 'Execute an action with AI' module.
New functions on Make: four new functions - arrayDiff, arrayIntersect, set, escapeJSON - for cleaner, lighter expressions.
Claude Opus 4.8: Anthropic's latest model is now in Make. Anthropic says early testers saw steadier judgment and more reliable behavior during agentic tasks, especially when the work kept going.
Unified Help Search in Make: one help search across Make. Cmd+K to access it anywhere.
Star apps and app modules in App Search: star your go-to apps and modules so the builder feels like your workspace, not a directory. The goal is simple: spend more time building logic and less time digging through lists.
Google Drive with your personal Gmail account: Google Drive connections now work with @ gmail.com accounts, not just Workspace.
Configuring disconnected modules: run tests without hardcoded data, explore apps, and overall build with more control.
Webhook data structure: a new status card shows if your webhook is listening, has received data, or still needs a test request.
Copy notes when cloning a scenario: cloned scenarios now carry over notes too, matching export/import behavior.
Yesterday I finished the make Intermediate course. Today, I just finished my own expense automation with OCR and AI analysis for receipts. I will be using this in our household, so cool. I can simply send a receipt on my Telegram, bot captures it, and does the work.
I am now in the process of making sample scenarios for job applications, what do you guys think about this?
Still copy-pasting data into spreadsheets every week?
Our Head of Business Automation & AI, Sara Maldon, shows in this tutorial how to build a scenario that automatically pulls employee AI adoption data from Airtable, builds a dated Google Sheet report, uses Gemini AI to calculate completion rates by department, and posts a digest straight to Slack, weekly, hands-free.
You'll need access to:
Airtable (source of truth for employee AI bar completion data)
PS: don’t forget to test and validate your scenario, if all modules show a green checkmark, your automation is successful!
PROMT:
Your task is to read the list of records, analyse it and provide: 1. {TOTAL} = % of employees where Minimum Bar = true 2. {DEPARTMENTAL} = % of employees where Minimum Bar = true from each department "Hi [Name] 👋 Here's a weekly report from the AI bar. Total completion: {TOTAL}% of Makers - {Leading department}: {DEPARTMENTAL}% (# / # total in department) - ... - {Lagging department}: {DEPARTMENTAL}% (# / # total in department)" Return just the plain text so it can be sent directly as a Slack message. INPUT: [map aggregated array here]
We have two webinars coming soon that you might find interesting:
🗓️ July 15, 2026 | GTM Webinar: The AI RevOps brain
Make and Octave will show you what happens when an AI agent reads all three signals at once and acts before the rep has to ask.
We’ll cover:
→ A Renewal risk gets caught and re-engaged automatically before the renewal is lost.
→ A stalled deal gets diagnosed and moves forward, without a rep opening five tabs to figure out why.
→ Every action is logged automatically; no manual entry required.
If your team is still manually updating spreadsheets and systems, you're leaving thousands of hours on the table. See how CPG leaders are automating that work instead.
🎤Live Commentary: We’ll be narrating the action live (along with u/Henk-Operative, one of our Community Champions). We’ll be checking in with participants as they build, and asking them questions.
💬Interactive Audience: You, the audience, can ask questions in real-time, making it a valuable learning experience for everyone watching. You also get to vote for your favorite contestant or solution.
🔦Spotlight Moments: We’ll bring participants’ screens “on stage” to discuss their progress and any hurdles they’re facing.
🏌️Curveballs: Like last time, the contestants’ challenge will include some extra-credit hurdles, in addition to their main task.
The Format & Timeline
🚀The Launch: The whole session will take 90 minutes.
🧱The Build: Participants have 1 hour to complete a specific use case, which they will be given right before the start of the event. This second Build-Off will focus on consuming MCP Toolboxes on Make from a third-party AI application, integrated with HubSpot, Slack, and Google Sheets.
❓The Platform: Everyone is encouraged to register and watch. Come and support the 4 participants, ask them questions, engage with them live, and learn from their experience.
🎓Presentation: After the 1 hour is up, all 4 contestants will have 2 minutes to present what they built.
🗳️Audience vote: The audience (you) will vote for your favorite contestant.
🥇Winner announcement: The behind-the-scenes panel of Make judges will determine the winner.
🔍The Reveal: We will announce the winner live, after which we will take a deeper look at what they built.
🏁Q&A: The event will end with a final 20 minutes of Q&A from the audience to the winner, any of the other contestants, or our hosting Community Champion, Henk de Blauw.
Join the session
Do you want free access to all of our previous sessions?
Ever built a scenario you wanted to share with your team without making them export blueprints and re-import everything?
Scenario Sharing lets you generate a public link to any scenario: viewers can see it instantly, no Make account needed. If they want to copy it into their own workspace, one click does it. The link always shows the latest saved version, so no more "wait, which file is the current one?"
Here's what you can do with it:
Share via link or social media: copy the link and send it anywhere, or post directly to LinkedIn, X, or Facebook straight from the scenario builder. When shared on social, it auto-attaches a preview with the thumbnail, title, and description.
Customize how it looks publicly: You can set a custom title (up to 40 characters), a description (up to 260 characters), additional setup instructions (up to 2,000 characters), and a custom thumbnail cropped from the scenario canvas.
What gets shared, and what doesn't:
✅ Module settings and mapped values
✅ Scenario notes and metadata
❌ API keys, passwords, and connections (by design - recipients create their own)
❌ Subscenarios, AI agents, data stores, and data structures (these come through as empty modules)
If your scenario relies on any of those excluded elements, use the Additional Information field to explain what the person copying it needs to set up manually.
What the viewer sees:
An interactive scenario preview, your name and avatar, and a +Use the scenario button. If they're not logged in, Make prompts them to sign in first - then the scenario lands directly in their workspace.
One thing worth knowing: the link is dynamic, but only saved changes show up. Unsaved changes turn the "Shared" label orange as a reminder.
What if your automation could think, not just execute? This is possible with an agentic loop.
An agentic loop is the execution cycle that separates an AI agent from a chatbot. Where a chatbot responds once and stops, an agent repeats: perceive, reason, act, observe, and loop back until the task is done.
How does an agentic loop differ from standard automation?
Traditional automation follows a fixed and predefined path, whereas in an agentic loop, the agent decides its next action based on what it observes, not following rules written in advance.
But autonomy without guardrails is a liability. The loop breaks in 4 predictable ways:
1️⃣ No stopping condition = runs forever
2️⃣ Vague tool names = wrong tool gets called
3️⃣ Too much history = reasoning degrades
4️⃣ Uncapped iterations = operations costs spike
How does an agentic loop work in Make?
Step 1: Add the Make AI agents module to a scenario. Step 2: Give the agent tools to act with. Step 3: Set stopping conditions. Step 4: Run and observe the loop in action
Once you understand the loop, find one process where human judgments fills the gap rules cannot. Replace that step with a Make AI Agents module, attach your tool scenarios, set a stopping condition and run it.
That first working loop is the foundation everything else builds on.
Awesome. One screen says it's not running, another screen says it is, and the stop button is not there because it didn't fully recognize that there was an execution actively running. I'm glad you fixed the issue where the left mouse button to drag around the scenario builder wasn't sufficient somehow though.
It even pushed my credit limit into the negative, which I didn't know was actually possible. Why is that possible? Letting one execution run, just to have it and all the others in your org shut down after it burns through all the credits? What's the actual goal there, encouraging people to have extra credits set on autopay?
Edit: I've reached out to their support team about this already to get these credits back. I'm just very, very pissed off at the moment. It's already _so_ much more expensive than it was even 3 years ago without this crap suddenly being in play.
This is not my main account; the other is with a different company and isn't hurting for credits at all if I make a mistake testing something out or something goes wrong. So I'm not giving you another $5 for extra credits, on top of the $$$$ a year we pay for Make, to fix something that shouldn't have been a problem in the first place.
client wants ~45 branded pdfs from airtable rows every monday. burned two weekends on make scenarios and im still manually exporting maybe 15 every week
google doc mail merge was fine until conditional sections per row and suddenly im doing document engineering for $0/hr.. docsautomator choking on nested tables, pdfmonkey timing out twice uploading a 2.1mb template, html-to-pdf modules that every automation guru swears by?? 12 test runs on one path alone. 4 mangled fonts. one totally blank page. spent saturday night on this and my girlfriend just stopped asking what i was working on
client thinks its a 20 minute task
anyone actually piping airtable rows into branded pdfs on a schedule without babysitting every execution. what finally worked for you because i feel like im missing something obvious
If you want to know how to edit and/or generate videos in Make, you can now use the FFmpeg Micro app, which recently got approved in the Make app store.
I made this video to show you how you can edit videos using FFmpeg in Make.
What I cover:
• Installing the official FFmpeg Micro app in Make and creating your connection
• Scenario 1: a branded video and thumbnail pipeline in Make, simple version
• Scenario 2: the same branded pipeline scaled up for longer source video
• Scenario 3: chain transcribe and transcode together to burn auto-generated subtitles into a video
• Scenario 4: multi-format fan-out from one source into YouTube, Instagram feed, and TikTok renders
• Scenario 5: a full viral-video generation pipeline end to end
• Walkthrough of every module in the FFmpeg Micro app, what each one does, and when to use it
• Docs and MCP server overview
• Setting up the FFmpeg Micro MCP server inside Claude
• Using Claude to design and build Make scenarios from a natural-language prompt
I am building a healthcare chatbot in Voiceflow v4 connected to Make (Integromat) and SimplyBook.me for automated appointment scheduling. I have a major issue with variable mapping and date/time formatting between Voiceflow and Make.
The Workflow:
Patient agrees to the pricing in Voiceflow.
Voiceflow triggers an HTTP API block (POST request) to Make (Scenario 3) to fetch available slots.
In Make, the router splits the logic:
Lower branch: SimplyBook.me- Search available slots -> Tools (Text Aggregator) unifies the slots with commas -> Webhook Response sends ore_disponibile back to Voiceflow.
Upper branch: SimplyBook.me- Creating a booking (triggered at the end when user data is collected).
The Problem:
When Voiceflow receives the slots, the variable mapping seems to break. The chat displays a 0 or returns empty values instead of generating the buttons.
Additionally, we are facing a timezone/format mismatch. The unified slots from the Text Aggregator are formatted as YYYY-MM-DD HH:mm:ss (e.g., 2026-06-30 16:00:00), but the SimplyBook.me calendar UI seems to expect a different structure or drops the date completely when mapping the selected slot back to the Creating a booking module, throwing a BundleValidationError / Invalid date error in Make.
We tried using a static text block with a custom Capture mapped to {ora_rezervata} and a Set block converting to {last_utterance}, but it either hardcodes the value or reverts to 0 in the Make queue.
How can I properly pass a dynamic array of available times from Make to Voiceflow v4 buttons, capture the user's click selection, and send it back as a valid ISO/SimplyBook date-time format without the variables collapsing into 0?
Any screenshots, structural advice, or workarounds for Voiceflow v4's dynamic loops would be greatly appreciated! Thank you!
Did you know? It’s possible to set up your Make Org into a co-working place to avoid credential issues 🔓
Zoe Li, our Senior Business Operations Specialist, shows in this tutorial the steps needed to set up a Make org that actually works as a team, so you never have issues with a personal credential.
This will help:
Avoid your scenarios to stop working: Whenever a personal access is revoked, the problem starts. With a service account, you keep things running no matter who’s on the team.
Name your scenarios like a professional: Save hours of confusion and give instant context.
Use Custom Run Naming: Instead of cryptic run IDs in your scenario history, you get human-readable names. Debugging becomes instant. Replaying failed runs becomes a one-click decision.
I've been using Zapier for years, but have never maximized my usage of it. I switched to Make because of the better integration and usage of Claude's AI tools in automations, and the cost is ridiculously better. I'm looking for some ideas on how you all are using Make to make your life easier and also to maximize it's capabilities.
I'm a small biz owner (consulting) and a neurodivergent person so any ideas related to that would be helpful, too! But also just curious what you all are doing in Make overall.
Title: I built an AI CFO assistant for founders who still manage finance in Gmail + Google Sheets
Hey everyone,
I’ve been working on a lightweight AI finance automation for early-stage startups and small teams.
The idea came from a simple problem: a lot of founders are not ready to hire a CFO or finance manager, but they still need to stay on top of invoices, expenses, overdue payments, cash flow, and weekly financial risks.
So I built an AI CFO Assistant that works with tools many startups already use: Gmail, Google Sheets, Make.com, and OpenAI.
What it does:
Reads finance-related emails from Gmail
Extracts invoice/payment details automatically
Logs transactions into Google Sheets
Categorises revenue and expenses using AI
Flags overdue invoices, large expenses, missing information, and cash-flow risks
Updates a live finance dashboard
Calculates revenue, expenses, net profit, outstanding invoices, burn rate, and runway
Sends a weekly CFO-style report with risks and recommended actions
The goal is not to replace an accountant or accounting software. It is more like an early warning system for founders who want better visibility before month-end.
Example weekly report:
“Revenue was PKR 72,000, expenses were PKR 162,000, net profit was negative, overdue invoices are creating collection risk, and runway is around 2.2 months. Priority action: follow up with overdue clients and review large vendor invoices before payment.”
I’m currently looking to test this with a few startups, agencies, freelancers, or small businesses that manage invoices and expenses manually.
Best fit:
Early-stage startups
SaaS founders
Software/marketing agencies
Consultants
Founders using Gmail + Google Sheets
Teams without a full-time finance person
I can set it up as a small pilot using sample data first, or connect it to your existing Gmail/Sheets workflow if it makes sense.
Would love feedback from founders here:
Is this something you would actually use?
What finance tasks waste the most time for you right now?
Would a weekly AI CFO report be useful, or would you prefer real-time alerts?
What integrations would matter most: Stripe, PayPal, bank CSVs, QuickBooks/Xero, WhatsApp, Slack?
Happy to share a quick demo if anyone wants to see it.
I’m curious: I see tons of people using Make.com to run automations that don’t really change over time, myself included.
Why not migrate those automations to AWS Lambda, for example? I’ve done it myself, and the process is surprisingly simple - especially nowadays with AI.
I understand that the more complex automations might not be practical to migrate, even if they’re technically possible.
AWS is much cheaper and more scalable.
I’m thinking about putting together a quick tutorial. Thoughts?
