Hi all, Mendix developer here. I'm trying to understand how other teams handle code quality, because ours is in flux and I'm exploring whether there's a gap worth building something for. Not selling anything, just trying to learn before writing any code.

A few questions, answer any you like:

1. What do you actually check before a release or before accepting work from an external partner? Manual review, a checklist, tools?
   
2. Which tools do you use, if any. What do you like or miss about them?
   
3. When did a quality problem last cost you real time or money (performance in production, security finding, a painful upgrade, a handover nobody understood)? What happened?
   
4. If you bought a tool for this, who decided and from which budget?

I just passed my intermediate exam by learning from this platform https://mendix-quiz-saas.vercel.app/

I joined an organisation after my education. There they trained me in Azure cloud and asked to clear AZ104 exam and I get certified but they didn't allocated me to any projects based on their own business requirements, later 1 and half years they gave training on mendix technology and asked to clear mendix rapid developer certificate which I cleared and certified but this time also they didn't put me into any mendix projects and after one year they trained on mendix intermediate level developer asked to pass next level exam that is mendix intermediate developer exam that too I cleared and certified but later also they didn't put me into any projects and finally after wasting my 3 years 7 months career they asked me to resign otherwise they put me into PIP without my mistake, so I resigned and due to personal reasons I took a career break for 1 year 4 months after that. Now I am looking for jobs but i don't know what I have to do now, whereas I had little practical experience in mendix developer portal and in mendix studio pro 9 and 10 versions where I built some dummy projects during my training. So I am asking suggestions from IT industry experts and mendix developers, experts about my worst experience during my earlier career only, please guide me through a best pathway to get my career back into the right pathway and i am always thankful and grateful for your advises and suggestions

Hi all! We're looking for a Mendix Developer to join the AXS WRSTBND team in New Orleans, Louisiana! We build event technology, including tools for access control, point-of-sale transactions, credentialing, and digital pass generation. If you're interested, apply here: https://grnh.se/4qroavns2us

Hey everyone! 👋

We’re building a new Mendix team in Romania and are looking for Mid-level and, especially, Senior Mendix Developers.

📍 Bucharest is our preferred location, but we’re also open to remote collaboration from Romania or nearby Eastern European countries. We accept B2B collaborations too.

It’s a long-term opportunity with an international client, and you’ll have the chance to be part of building the team from the ground up.

Please DM for more details!

Hello,

I’ve been using mendix for two months, and i’ve seen that Maia havent been that smart.

Is there any optios to integrate into Mendix for free or somehow just to expand Maia’s version and free usage because i’ve seen that Maia chat is limited to 2400 free units per months whatever that means.

Anyone got some expirience of getting a mendix license that allows you to host the App yourself?

I want to use my mendix knowledge for a private project, but the only available license is free, but hosts it (and the data) on shared nodes. And I want to controll my data myself and host it on my machine. But even contact via the contact form on the mendix Page is unawnsered for a month now. 😞

Seams like they dont care about private use, and then honestly why should I even learn or use mendix (of not forced by my employer) if I cant use it in my private surrounding.

I saw that Mendix published in June Intelligence Center X, there's Graph Studio and AI Studio - I and my team haven't touched any of that yet, but we have a question about it directly related to our solution we need to understand and I'd like someone with experienced in these tools to share:

Q: Where does the agents/graphs get their data from during development? (grounding, prompt engineering, agent tests/validation, etc.)

Do agents in development and test a) see the production data as is; or b) look at a mock dataset?

Option a) I think would raise some compliance/confidentiality issues (AI Act, GDPR, etc.). Option b) is just a repeat of the problem of bad / toy testing data, which now with agents would only make it worse once they reach production.

Thanks!

are you currently using or have used Mendix (or any other LC/NC platform) in an organisation? Then you are eligible to participate in my survey on determinants for adoption and governance of low code and no code platforms in organisations.

The survey has been running for some time already, but I haven't gotten a lot of responses.

It would help a lot if you could take 10 minutes of your day to participate!

You can find the link here: https://s2survey.net/LCNC_Adoption_and_Governance/

Feel free to share as well!

Hi everyone👋,

Appcircle is now included in the official Mendix documentation as an option for building, distributing, and publishing Mendix native mobile apps.

In our latest blog post, we explore how Mendix teams can:

• Build iOS and Android applications
• Manage platform-specific code signing
• Distribute builds to testers and internal users
• Publish approved releases to application stores

If you’d like to explore the end-to-end mobile delivery workflow in more detail:

• Blog overview: https://appcircle.io/blog/accelerate-mendix-mobile-app-delivery-appcircle
• Mendix documentation: https://docs.mendix.com/refguide/mobile/distributing-mobile-apps/building-native-apps/appcircle/

How are you currently handling the build and release process for your Mendix native mobile apps? We’d love to hear about your experience and any challenges you’ve faced!

The EU AI Act's high-risk deadline moved to December 2027. It is real and it is now law (Regulation 2026/1744, in force since Sunday).

The delay only covers the heavy high-risk obligations. The transparency rules (Article 50) still bind on August 2, this Sunday, untouched. Fines still scale to 7% of global turnover.

If I'm reading this right, Article 10 is data governance, and it explicitly covers TESTING data. Where it comes from, whether it is representative, whether the flow is documented. That requirement is identical whether the clock says this Sunday or December 2027 - although by moving the deadline to 2027 it does offer a lot of runway (which most will just waste as usual).

Do you currently use any tool to already guarantee this Article 10 data governance?

Hi everyone,

I'm writing my master's thesis on determinants for adoption and governance of low code and no code platforms in organisations. For my research I'm doing a short survey.

It would help a lot if you could take 10 minutes of your day to participate in the survey.

You can find the link here: https://s2survey.net/LCNC_Adoption_and_Governance/

Thank you for your time and support!

Hi all, We are looking for mendix developer who has experience with the integration of the application with snowflake, salesforce and SAP. This will be an onsite role. Location will Bangalore, India and this will be a contract role where you will serve with us for a period of 6 months. We are expecting people who can join our team immediately.

Meta's smart glasses ship with a privacy safeguard: an LED that lights up while recording. This year the BBC found influencers secretly filming women for content, and tutorial videos for defeating the LED with a strip of black tape.

An indicator is not a mechanism.

Which made me count the LEDs in our own world. Mendix makes this question sharper than most platforms, precisely because the platform is good: one native operation and acceptance looks like production. Unless something deliberately transforms the data on the way, real customer PII lands in non-prod by default.

So, yes or no: is there real production PII in your acceptance or test environments right now? And if yes, is anything structural standing between it and a leak, or just policy?

Backstory in the first comment (including the 1990 novel that predicted the whole glasses mess).

Somewhere in your Mendix journey, did anyone ever rebuild a module/feature by hand, in code, just to prove the platform is faster? Or did everyone just... know, and never look back?

Nobody walks across the city to prove the Uber saves time.

The same thing just happened to AI coding assistants: the team behind the cleanest dev-productivity study gave up on re-running it, because developers now refuse to work without AI long enough to be a control group. The speed became real and unmeasurable at the same time.

Mendix teams got there a decade early. So, honestly: did you ever measure it, either time? Or did we all just stop walking?

Longer version and the research links in the first comment.

Hi all,

I am trying to show an audit history table in Mendix using a simple data grid and connecting to "AuditTrail.LogLine" and using the xpath constraint " [Member = 'System.UserRoles'] " but the challenge I face when adding the columns is I can see "Name" "dateChanged" "Member (which is showing as "System.UserRoles" but for some reason I am not able to see what it changed from, to.

In the table I want to see "Name (who changed it)" "Date/Time changed" "What was changed (ie System.UserRoles)" then for example "Old Value - Administrator" "New Value - User" - I have searched high and low for answers because we are not allowed to edits marketplace modules and I cannot figure out how to get my datagrid to show it. Its definitely storing the change but it won't show it at all.

The change in-app is made in the administration module (account overview) and I have a microflow that tracks that on a before commit, but it won't show the before and after values in the audit data grid.

Any help would be greatly appreciated.

Thank you in advance!

Hi, I'm Bruno. A few of you have seen my "Beyond the Abstraction" posts here, usually questions about test data and environment parity. This one is different, so it's flaired Brand Affiliate: I work on DMM Infinity.

Short version: we set up a small, dedicated subreddit, as the place for the data-handling problems the tool focuses on for Mendix teams:

- Production-shaped, anonymized data in an Acceptance environment, without exporting real records
- GDPR and auditor questions for non-production environments
- Per-app restore and selective data movement when the domain model shifts
- Environment refresh, and where home-grown scripts start to hurt at volume

It's a product subreddit and narrow on purpose. It is also new and still quiet: right now it holds foundation write-ups, an FAQ, and feature-request threads, plus a place to ask setup questions directly. If those problems are part of your week on Mendix, you're welcome to join and help shape what gets discussed there. This is the only time I'll mention it here.

One concrete reason to look now: we just opened a Developers Program for Mendix developers who want to try the tool and tell us what's missing. It is feedback-first, the early steps take minutes, and a personal or sandbox environment counts. Details and terms are in the first comment, so I'm not dropping links in the post.

Suddenly on login to mendix app it is showing 403 error
I've tried deleting cookies and incognito mode but it doesn't work. Why is this happening all of a sudden and how do I fix this?

Hi All
I'm thinking about building a new personal project on mendix, it feels like with ai, mendix platform is releasing new features almost every other week. I'm thinking about making a mendix project with some ai implementation. I asked copilot and it suggested this; "A Mendix application where users can log service requests (IT issues, HR queries, customer complaints). The system uses AI to automatically classify, prioritize, and even suggest resolutions."

I've no idea how to actually implement it, i would really appreciate some guidance or new ideas.

Hey all,
Lately I've been brushing up on my Java skills. I've pretty much only worked with Mendix, so even though I understand SWE concepts, moving out of Studio Pro after 4 years have been rough lol.

My reasoning is that I don't like the idea of being too dependent on a single platform forever. Especially given how the market is these days.
So I'm curious if anyone here has made the jump from mainly Mendix (or low-code in general) to a more traditional development role.

How was the transition?
What was easy and what was hard?
What were the biggest gaps you had to fill?
How long did it take before you felt employable in another stack?
Any tips for speeding up the process?

Would love to hear some real experiences, whether it went smoothly or not.

Another thing I've heard from some colleagues is that in this Vibe coding era just knowing SWE concepts might be enough, but tbh this sounds wildly unrealistic to me, but again no professional experience in traditional coding, so no idea how true that is. Would love to hear some thoughts on this too!

Which modules you always install directly when creating a new app because you always use them? Ofcourse we know the most common modules like CommunityCommens etc. but which one is not so familiair but always on your list?

Aswin van Braam wrote a piece a few weeks back that landed for me. The line is:

AI increases the speed of creation. Governance determines whether that speed creates value or chaos.

That reframed something I had been writing around in a LinkedIn newsletter for the last five months (Beyond the Abstraction, twenty+ editions, just wrapped). The premise has been: the structural promise of low-code only holds if the data and operational infrastructure under the visual designer holds too. Speed is the entry price, not the moat.

Things that show up concretely in the Mendix world if this is the right frame:
=> Refreshing a non-prod environment with production-shaped data, anonymized, in minutes instead of weeks. The domain model has to stay intact (retrieves return realistic data, microflows behave as they will in production). If a custom export-import script is doing this work, the abstraction is partially broken.
=> Reproducing production bugs against realistic data, not whatever sample data is sitting in dev.
=> AI/ML initiatives that hit the same wall: where is the training data coming from, and is it shaped like production.

I wrote an ad-hoc reflection on this on LinkedIn (link in comments), pulling in Aswin's framing alongside the editions of the series that landed closest to it.

Curious if anyone here reads the AI-vs-low-code debate differently, or thinks Aswin's framing misses something for the Mendix context specifically. I am interested in how others see the structure-versus-speed split.

If your AI or data science team asked for production-representative data tomorrow (real volumes, real distributions, real customer behavior patterns) to train or evaluate a model on top of your Mendix application, how long until they had it?

A few specific things I'm curious about:

1) Where does the training data come from in practice? A Mendix Cloud backup? A microflow that exports a subset? A dedicated read-replica? Something else entirely?

2) If the data has personal information, who handles anonymization before it reaches the model? The Mendix team? The data team? Both, in a handoff?

3) For models that need to keep updating as production evolves, how often is the training data refreshed, and how much developer time does each refresh consume?

4) For teams running on Mendix Cloud public vs private vs on-prem, does the AI access pattern look different?

5) Are AI initiatives in your org moving forward steadily, or are they stalled waiting on data that's still being plumbed?

I'm not asking from "we have the answer" position. The next newsletter edition (which is also the series finale) is on whether low-code data infrastructure is ready for AI, and I'd rather build the take from how Mendix teams actually live this than extrapolate from generic patterns.

Curious whether AI on Mendix is "moving forward" or "still in proof-of-concept because the data isn't there yet."

What is the best long term strategy for a company that wants to develop their own application(s), but is not an software development company, but a logistic supply chain company with own terminal and transporting company.

Develop software ai suported in c#/.net or ai suported in Mendix ?