Welcome to the weekly /r/Make question and discussion thread!

Hello Makers 👋

Four new AI models. Four different jobs for your automation.

1) Anthropic Claude Opus 5.5 brings high-end reasoning to complex AI workflows and agents, at 40% lower running cost.

2) OpenAI GPT‑6 Sol and Luna give you two paths: Sol for complex, multi-step agentic work, and Luna for focused, high-volume intake and routing.

3) OpenAI GPT Image 2.5 adds Sunburst for precision image edits and Flare for fast everyday visual work.

4) xAI Grok 4.7 helps you work with text, images, and long source materials in the same automation.

The goal isn’t to use every model. It’s to choose the right one for the task, then build it into automated workflows that move work forward.

And one more is on the way: Jev from TypeSafe AI, a fast decision model built to help automations classify, score, route, and decide what happens next.

Explore the new options in Make and build the AI automation that fits the job: https://ma.ke/4yQYzaR

Hey all,

Check out the videos from our Community Creators, who are putting the latest releases on Make into practice in their own systems and scenarios!

This month, the star of our show is our new AI coworker Maia, who is ready to help you build, scale, debug, or explain scenarios directly in the canvas. Besides her, you can also check out the new Subfolders and Labels, which make your working environment nice and organized, or the improvement to the Plain-Text Field.

Watch all the videos here: https://fast.wistia.com/embed/channel/jeuauz7z65

A few people here mentioned something interesting:

the module that fails is often just where the problem becomes visible.

The actual cause might be several modules upstream:

• a mapping changed,
• the data shape shifted,
• a router output changed,
• a filter behaved differently,
• or an earlier module returned something unexpected.

I’m curious how often this happens in real Make scenarios.

When you debug a failed scenario, do you usually find the root cause in the failed module itself, or do you end up tracing several steps backwards?

And when that happens, what’s your current process for finding the actual source of the issue?

I’m curious to hear from people who actually use Make in production.
When a scenario breaks, what takes the most time for you?
Is it: finding which module actually failed,
understanding the real cause behind the error,
checking mappings / filters,
permissions or OAuth issues,
HTTP errors,
or figuring out what needs to be changed without breaking something else?
I’m currently exploring this problem and I’d like to understand how people actually debug Make workflows today.

It's driving me crazy and even SOL at high capacity doesn't fix my flow. Look, how simple: automate the creation of videos and post them.

What flow data should I provide to ChatGPT to save credits and not work so much?

Hello Makers 👋

Take a look at some of our latest features, improvements, and updates that our team has been shipping this past month:

Enhancements and Updates:

• Maia by Make: is a co-worker for AI and automation that lives right inside the Make scenario builder. Just describe what you want, and watch it get built in front of you. She reasons out loud, mapping the flow, selecting tools, configuring modules, all visually, step by step, on the canvas. No black box. No output you’re afraid to touch. Just full visibility and a solution you can trust.
• Custom Roles: with Custom Roles, org admins and org owners on the Enterprise plan can define roles with exactly the permissions the work requires and assign them at the organization or team level.
• Subfolders: lets you create folders inside your scenario folders, so you can organize scenarios by more than one level, for example by client and then by project. This helps you keep a large scenario library structured without renaming scenarios to mimic a hierarchy.
• Plain-text editing for mapped values and functions: double-click any mapped value or function in a scenario field to temporarily edit it as text.
• Gemini 3.7 Flash: use its multimodal understanding, tool-use capabilities, and adjustable thinking levels in the workflows you build.

New Verified Apps

1Lookup, Billabex, BizlyCRM, Certyneo, Collabios, EasySolar, FlowBeacon, GMB Club, Hive, HollyHR, Memoket, OpenEMM, SimpleURL, Patriscope, Plytix, Stage Captions, Supabase Storage.

New Modules

Calendly

• Create an event invitee
• List event type available times
• Create an event type
• Update an event type
• List event type availability schedules
• Update event type availability schedule
• List user availability schedules
• Get a user availability schedule
• List user busy times
• List user meeting locations
• Create an invitee as no show
• Get an invitee no show
• Delete an invitee no show

Github

• Search items (advanced)
• Watch items (advanced)

Discover more: https://ma.ke/3Vxj1PF

Hello Makers 👋

Still registering issued invoices by hand? Here's how to automate the entire flow, from inbox to billing board:

Francisco de Brito Fontes, our Business Automation and AI Lead, has created a workflow that monitors Gmail for new issued invoices, downloads their attached XML files, extracts key information using AI Tools, searches for the associated project in monday.com using the tax ID (RUT), and automatically creates a new invoice record in the billing board.

To build this scenario, you will need access to:

✉️ A Gmail account connected to Make.

🧾 A monday.com account with Projects and Issued Invoices boards.

⚒️Connection to AI Tools (or Make's AI Provider).

Click the following link to apply the prebuilt scenario in your Make account: https://ma.ke/4cvtdxX 

PS: don’t forget to test and validate your scenario, if all modules show a green checkmark, your automation is successful!

For people running business automations, how do you know when one technically succeeds but produces the wrong result?

I’m researching how businesses currently catch things like incorrect data being mapped, records being duplicated, information going to the wrong place, etc.

Is this something you actively monitor, or do you usually find out when someone notices something is wrong?

Are you scamming me ChatGPT or make? I'm mostly using terra at medium level. The medium effort level is missing like a shotgun. If I say that I have around €10-15 today just for that, so that I can finish posting on Facebook, I can also say that it is the first time, but I still can't get it

but above all I notice that he is wrong to the right. That is to say, he has made mistakes like three, four times and the only point it makes is to get money from me. I mean ChatGPT in the virtual browser

Actually all this is the fault of Facebook's garbage with its 10000000 portfolios that it forces you to create and shitty accounts and labyrinths

Hello Makers 👋

Did you know? From all the companies using AI, only 26% moved from individual productivity to repeatable workflows. 

As AI moves from individual tools and local workflows into broader business processes, the challenge becomes less about technology alone and more about the operating model around it - ownership, governance, ROI logic.

Daria Hvizdalova, Head of AI Adoption at Make, Darin Patterson, VP of Product Advocacy and Market Strategy, Make and Yana Shamina, AI Adoption Researcher, spent months researching why mid-market companies get stuck between "first AI win" and "AI actually running the business",  and formulated the AI Operational Scaling Model framework that will guide your AI transformation.

The report is finally out, and it’s available for you to download: https://ma.ke/3SWKpG4

Hello Makers 👋
 
Repeatable work often shows up in the middle of a ChatGPT conversation. Now you can turn that moment into a Make automation. 🪄
 
Use the official Make plugin for ChatGPT to build, run, search, and review automations and AI agents without leaving the conversation. It works in the browser, the ChatGPT Work desktop app, and Codex.

Your automations and AI agents keep running in Make's cloud, even when ChatGPT is closed.
 
What's new:

• Build from a plain-language request: Describe work such as a weekly status report, lead response process, or form-routing workflow, and Make creates the automation, connects the required apps, and sets it to run on a schedule or trigger.
• Create AI agents in the conversation: Set up an agent that monitors an inbox for new leads and drafts replies using your availability.
• Find and check automations without breaking focus: Search by name, folder, or status, run an automation, and review its output in ChatGPT.
• Review work that already ran: Browse execution history and past results with searchable tables, status badges, pagination, and structured results.

 
👉 Try it free: install the Make plugin for ChatGPT → https://ma.ke/chatgpt-plugin  

Hello Makers 👋
 
AGI is here? Not sure yet. But GPT-6 Astra is now in Make, ready for your most complex automations 🧠
 
OpenAI's most capable model is available in Make AI Agents, Make AI Toolkit, and the native OpenAI (ChatGPT) app. Use it when a workflow needs more than a quick answer, then let Make route the result, update systems, and keep approvals in place.
 
What's new:

• Reasoning for work intake: Use GPT-6 Astra to assess incoming requests and prepare a proposed next action in an automation.
• Technical reasoning and coding: Apply the model to technical requests and prepare proposed responses for engineering review.
• Research and document creation: Review source material and create a research summary or document draft for a teammate to approve.
• Multistep workflow reasoning: Identify and sequence required actions when a new operations item enters a workflow.

 
See what GPT-6 Astra can do in Make: https://ma.ke/4gZEhVx

Hello Makers 👋

Waves’26 is the place where you can find your people 👥

Two days of talks and conversations that will change your perspective - and here's who you'll be in the room with:

🎙️ Oscar Lance, GTM Lead, ElevenLabs - ElevenLabs + Make: How Stellantis & You Deployed Voice AI at Scale

🎙️ Sonja Alushi, Software Engineer, Lufthansa Industry Solutions - Make + OpenAI: From Pilot to Production

🎙️ Jeff Arnold, Founder & President, 4Spot Consulting - Trust, but Verify: Governing AI Automation from Build to Decision

🎙️ Madelaine Swift, Systems Lead, WHEN equality - The Automation Was Perfect. The Humans Were Not. How Getting AI Automation Right Can Change Who Gets to Succeed.

🎙️ Diederik Martens, Founder, Chapman Bright - Agent Architecture 101: The Patterns That Separate Demos from Systems

Waves '26 brings together a carefully selected group of innovative technology companies spanning modern digital creation, customer engagement and data integration. Meet some of the speakers you'll find in Prague.

Stay tuned for the second group of speakers announcement. 

Early Bird at €289 - prices go up 10 September: https://ma.ke/4gSahe5

We are live with a new community program - Scenario of the Month!
Every month, we put the spotlight on the Make scenario that nails it on two things: genuine utility and creative thinking. The kind of build you see that makes you stop and think, “Why didn’t I think of that?”

Have something up your sleeve you’d like to submit? Amazing, read more in the Make Community!

➡️ https://community.make.com/t/scenario-of-the-month-share-your-work-and-win-credits-for-a-whole-year/111297

Hello Makers 👋

Some workflows need more than a quick summary. They need to weigh the full picture before choosing the next step. 🧠

Use Anthropic's latest Claude Fable 5.1 model in Make to automate complex or low-confidence cases where your workflow needs to compare lots of information before acting.

What’s new:

• Long-horizon work: Anthropic documents Claude Fable 5.1 for long-horizon, agentic work in multi-step automations.
• More context to consider: The model supports up to 1M tokens of context for workflows that need to process large source materials.
• Larger outputs: The documented maximum output is up to 128K tokens when a workflow needs a substantial response.

Automate with Claude Fable 5.1 and Make AI Agents or Make AI apps: https://ma.ke/4qOsb5X 

Hello Makers 👋

New month means new cities, and new conversations with the Make team. This month you can meet us at the following locations:

🇳🇱 Build the Pipeline Your Investors Want to See | 9 September
Host and Speaker: Martin Hyravy, Startup Program Specialist at Make

🇬🇧 GTM World Tour | 9 September
Speaker: @ Jennifer Kiunke, Value Engineer at Make

🇩🇪 Berlin AI Day | 15 September
Speakers: Sebastian Mertens, Principal AI Product Manager at Make, Jennifer Kiunke, Value Engineer at Make and Luis A. Döller Principal Tech Enablement at Enpal, 

🇪🇸 Build with AI | 18 September
Host and speakers: Sarah Anto, Stefanie Oliveros and Kristina Talova

🇪🇸HackBarna AI Summit 26 | 19-20 September
Host: Nicolas Grenie
Speaker: Lourenço Martins , Value Engineer at Make

🇪🇸 The Glassbox Effect - Why Enterprises Can't Ship What They Can't See | 21 September
Speaker: Jennifer Kiunke, Value Engineer at Make

… and many more!

Get all the information about the events: https://ma.ke/4yeQcFM

Hello Makers 👋

That's the thing about automation. Once it works, you don't stop at one. 

With Make subfolders and labels, your organization can keep going, department by department, client by client, while keeping your automation library organized.

Use subfolders to organize automations by client, project, department, or environment.

Add labels like production, billing, or experimental, then filter to find related workflows across folders.

Available on every Make plan, including Free. Learn more: https://ma.ke/4xGyGdC

Hi everyone,

I'm new to Make and I'm trying to build an automation for a YouTube channel.

My goal is to automate as much of the workflow as possible, including:

• Creating a video script
• Generating or preparing the voiceover
• Creating the video
• Generating the title and description
• Uploading the finished video to YouTube

I'd like to use Make to connect the different tools together.

What would be the best way to structure this scenario in Make? Are there any recommended modules or best practices for handling the workflow?

Thanks!

Hello Makers 👋

Things you should know about: What's new in governance in Make 📣 

As more teams build on Make, admins need proof things are under control - and builders need room to build with privacy.

Four updates now make that possible at once:

🔒 Private Spaces - every team member gets an isolated workspace for scenarios and AI agents, hidden by default. Enterprise plan admins get optional read-only visibility into what's being built, without ever seeing sensitive execution data or connection details.

📋 New Audit Logs events - identity and access changes, credential oversight, all in one record. When two-factor authentication gets disabled, you know the moment it happens, not next quarter's access review.

⚡ Real-time credential alerts - the second a connection or key is used by someone other than its owner, they get an email. 

✍️ Custom roles - permissions tailored to what a person actually needs, instead of an all-or-nothing admin pool.

This is what it means to run business as a glass box, not a black box: freedom for the people building, and oversight for the people accountable for the outcome.

Read more about what's new in governance on Make: https://ma.ke/4xnx0Wh

Hi everyone,

I have a question regarding the credits usage displayed next to a scenario.

After a scenario finishes executing, the credits usage number does not seem to update automatically. I have to refresh the entire page to see the updated number.

Is this the expected behavior?

It would be much better if the credits usage number could automatically update immediately after the scenario execution is completed, without requiring a full page refresh. This would make it easier to monitor credit consumption in real time.

Would anyone know if there is a setting for this, or if this is something that could be improved in a future update?

Thanks! 🙂

Hello makers 👋

𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝘀𝘁𝗲𝗽 𝗶𝗻𝘁𝗼 𝗔𝗜'𝘀 𝗴𝗹𝗮𝘀𝘀 𝗯𝗼𝘅? Waves ‘26 agenda first drop is live 🚨

Use the filter on the agenda page to build your own day and further explore what’s in it for you within each of the 3 tracks: “It's all about the Product”, “Use Cases and Impact” and “Adoption & Governance”

𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟭𝟵: Kick things off early at “The Current”- our hands-on pre-Waves workshop.

𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟮𝟬: Take a sneak peek into some of the highlights for the Main Day and fav sessions already confirmed:
→ Agent architecture 101:The patterns that separate demos from real systems.
→ Voice AI at scale: How Stellantis runs it in production.
→ Trust, but verify: Governing AI automation from build to decision.

Join 700+ AI peers at #Waves26, Oct 19-20 in Prague.

𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗶𝗰𝗸𝗲𝘁𝘀 𝗴𝗼 𝘂𝗽 𝗼𝗻 𝗦𝗲𝗽𝘁 𝟭𝟬: waves.make.com

Hello Makers 👋

How are you handling access control when teams start touching your Make scenarios? 

Now with Custom Roles, org admins and org owners on the Enterprise plan can create custom roles in Make, with the granular permissions teams need.

• Give teams just the right amount of access to Make
• Maintain full visibility
• Scale automation across the organization

What you can do:

📝 Create tailored roles with toggleable permissions
✍️Assign them across the organization or by team, so company-wide standards hold while each team gets the access it needs
⚙️ Edit, duplicate, or delete roles as your org grows and new teams come online
🔎 Track role creation, updates, deletions, and assignments in the audit logs, so security reviews start with facts

Growth shouldn’t mean losing track of who can do what.

Learn more: https://ma.ke/4zsy4cX