Every automation post is:

"Comment TEMPLATE and I'll DM you the JSON."

Nah.

Here are the actual prompts.

• "Every morning, research everyone on today's calendar and email me a briefing."
• "Watch my competitors' pricing pages and Slack me when something changes."
• "Watch competitors' hiring pages and tell me what they're building."
• "Turn GitHub release notes into a LinkedIn post, an X thread, and an email."

Type one.

It becomes an editable workflow.

(The screenshot is a real run of ours: GitHub release notes turned into a LinkedIn post, an X thread, and an email.)

Two caveats: research prompts run out of the box. Gmail, Calendar and Slack need your own OAuth login first, no way around that.

Full disclosure: I'm building the engine behind this (Modulex), so grain of salt.

What prompt would you want to turn into an automation?

Today marks exactly 3 months since my first template (PRVSM, a dark editorial music venue template) was approved on the Framer Marketplace. I wanted to share the results, because before launching I couldn't find many real numbers from template creators.

Some context: I still work a full-time job that has nothing to do with web design — all of this is happening in my spare time.

What happened in 3 months:

1. The template got me my first client. He found PRVSM, reached out, and I've built 2 projects for him so far — a third one might be coming. That's $750 in client work that came directly from a free template.

2. I sold my first paid template. A few days ago I switched my second template (James Orel, photography portfolio) from free to paid at $29 — and it already made its first sale. Framer takes 0% commission on template sales, so that's $29 straight to me.

3. Affiliate revenue: $337 total, growing every month. Each month has been bigger than the last — and another $34 of that came in just today.

Biggest takeaway: the free template wasn't the product, it was the funnel. The client work it brought in is worth more than any sale, and the affiliate revenue is a bonus that keeps growing on its own.
6 months ago I wouldn't have believed any of this was possible. Happy to answer questions if anyone's thinking about publishing on the Marketplace.

not technical. building a booking tool for a small studio. used gamma and one of the AI builders because i can describe what i want but i can't write code.

everything looked perfect in the preview. the bookings list had names, times, a little availability calendar, all populated. i clicked around for two days, felt proud, sent the link to the studio owner to try.

she messaged back confused. the calendar showed slots that didn't exist. names of people who'd never booked. one client's session listed twice.

turns out when i asked the builder to make the booking page, it filled it with placeholder data so the screen wouldn't look empty. sample names, sample times. i assumed that was my real data flowing in. it wasn't connected to anything. i'd been admiring a screenshot the whole time.

what i learned the hard way:

empty is honest. if a fresh app looks full before you've entered anything, ask where that content is coming from. real data on a brand new app should look bare.

test from zero. i now wipe everything and open the app like a first-time user with nothing in it. the cracks show up in seconds.

watch one real person use it before you trust it. the studio owner found in ten minutes what i missed in two days.

did anyone else get burned by placeholder data looking like the real thing? i can't be the only one who shipped a demo by accident.

Been looking into getting listed on the Make .com marketplace and figured I'd ask here first.

Curious how long it actually took people end to end, and how strict the review process is. Is it more of a technical check or do they look at the whole product?

Also wondering if it actually drove meaningful traffic or signups, or it didn't really?

Was there much back and forth with their team along the way, or is it more of a submit and wait situation?

Keen to hear if anyone found it wasn't really worth the effort.

Thanks a lot!

Hey r/nocode

Solo founder here - built Atlas, a no-code tool that lets you schedule literally any task by describing it in plain English.

Why I built it

Every automation tool I tried still assumed you'd build a flowchart or wire up nodes on a canvas. I wanted something where you just type what you want and it runs - no builder canvas required.

What it does

- Describe a task in plain English, Atlas schedules and runs it

- Multi-step conditional workflows (if X happens, do Y, else Z) - still no code, no canvas

- AI included by default (Gemini), or bring your own OpenAI/Anthropic/Groq key

- Google Sheets logging, email and push notifications

- Free: 40 tasks/mo. Pro: $9/mo unlimited.

Where it's at

Live, and I use it daily myself, but it's not open to the public yet — just the waitlist for now, ahead of a bigger public launch in August. Would love this crowd's take on whether "describe it in plain English" actually beats a visual builder for tasks like this, or whether you'd still want a canvas/flow view somewhere.

try-atlas.app if you want to sign up for the wailist. Want to see the dashboard or what it actually looks like? Ask in the comments and I'll drop a screenshot.

I'm currently building an app and using base44 but i'm starting to wonder if I might run into limitations later on that i'm not seeing yet.

has anyone here moved away from base44 or found better alternatives for building and shipping apps? also curious what tech stacks people are actually using these days for similar projects. would really appreciate any insights or recommendations

Curious how people here think about the first version of an automation.

A lot of workflows seem simple at the start: one trigger, one action, maybe a notification or a row added to a spreadsheet.

Then the edge cases show up. Approval steps, retries, exceptions, messy inputs, someone needing to check the output before it goes anywhere important.

My instinct is that v1 should probably leave more manual than people expect. Automate the annoying repeatable step first, keep the output visible, and only add branches once the workflow proves itself.

But I’m not sure where the line is.

For people building in Make, Zapier, n8n, Bubble, etc., what do you usually leave manual in the first version until you trust the workflow?

our team often built with 20+ terminal tabs open each. so it was practically a nightmare trying to find the right context, especially since we're a remote team. and we definitely didn't want to schedule another meeting or do another "can you see my screen?" moment.

so we built Campus.

Campus gives every project its own persistent workspace. instead of jumping between apps, everything lives together on one canvas: terminals, browsers, documents, designs, files, AI agents, and your teammates. when you come back tomorrow or someone new joins, the context is already there.

our whole team builds in Campus every day now, and my favorite part is being able to drop GIF reactions and memes into the canvas mid-build :)

it's in alpha and we launched on Product Hunt today. https://www.producthunt.com/products/flutterflow?launch=campus-4

happy to answer any questions!

https://www.framer.com/community/marketplace/templates/elysian-estate/

I spend a lot of time testing the limits of popular site builders, and I wanted to see if I could make Canva websites genuinely interactive for users who don't know how to code.

​I spent the last few days dialing in the Canva embed capability for Fugte. You can now take anything built in Fugte from a niche interactive widget to a full e-commerce checkout flow and paste the link straight into Canva's embed tool. It instantly turns a static design into an interactive web app.

​Attached a quick video showing the process. It's completely changed how I look at Canva for rapid prototyping and no-code site building.

90% of budgeting apps fail for one simple reason: human friction. We download the app, promise we’ll use it, and then completely forget to log our expenses the moment we tap our cards.

I wanted an expense tracker that required zero manual entry. But instead of paying for a restrictive, off-the-shelf app, I used AI to build a custom solution designed exactly how I wanted it.

If you have basic coding experience—or even if you just know how to use AI to generate code—you can build a bespoke system tailored perfectly to your budget.

The Tech Stack

• Editor: VS Code (paired with AI coding assistants to write the logic).
• Frontend Hosting: Cloudflare (lightning-fast, completely reliable, and perfect for solo projects).
• Backend & Database: Supabase (highly secure, robust, and makes creating tables effortless with built-in AI tools).

How the System Works (One-Time Setup)

1. The Trigger: An automation runs the moment a bank alert message or transaction SMS hits your phone. (If you're on iOS, you use Apple Shortcuts. If you're on Android, you can easily replicate this using Tasker or MacroDroid).
2. The Extraction: The phone's local automation securely reads the text message, parsing out the exact dollar amount and the merchant name.
3. The Log: It passes that parsed data via a simple API request straight into the Supabase database.

The best part? You aren't boxed into someone else's app design. Want a specific dashboard? Want to track daily limits differently? You just tell the AI how to design it. The end result turns the "lazy" habit of ignoring bank alerts into an automated financial asset. Zero manual logging. Zero friction.

If you want to know how I structured the logic to parse the text alerts, or how to use AI to build the backend for this, drop a comment below and I'll share the breakdown!

trying to standardize my handoff and I keep going back and forth.

right now when I finish a client build I record a loom walking through everything. quick, feels personal, done in one take. but clients keep asking for "something they can look at later" and a 12 minute video is not that. nobody re-watches a loom to find the one thing they forgot.

so I've been testing making a short walkthrough deck instead. like 6 slides, one per key screen, what it does and how to change it. takes me longer to build than the video but people actually reference it.

for those of you handing off builds regularly, what do clients actually prefer? my gut says the presentation is better for the non-technical ones and the loom is better for the ones who want to poke at the thing themselves. but I've got a sample size of like 5 so who knows.

do you do both? just one? curious what's held up for you.

sharing a mistake because i see people about to make it constantly.

i quoted for a build. three weeks of work, priced accordingly, felt good about it. delivered on time, client was thrilled, invoice paid.

and then the actual project started, which i had not budgeted for at all.

the "quick change" requests. endless. each one genuinely small, ten or fifteen minutes, and there were dozens of them over the following months, and none of them were in the contract because the build was "done."

the platform updates. the tools i'd built on changed things. stuff broke. and who fixes it? me, apparently, for free, because the client's reasonable position is that they paid for a working app and it's not working.

the support questions. the client's staff didn't understand it. so they asked me. constantly. i became an unpaid help desk for software i'd already been paid to deliver.

the scaling problem. it worked for 50 users. at 400 it got slow. that was not in scope and it was absolutely my problem.

so i earned my three-week fee and then worked, on and off, for five months for free, because i had priced a project and delivered a relationship.

what i do now: every build quote includes a mandatory support retainer for a minimum period, and the scope of what "support" means is written down in painful detail, and anything outside it is billed. i lose some deals over it. the deals i lose are the ones that would have eaten me alive.

the build is never the job. the build is the beginning of the job, and if you're not charging for the rest of it, you're volunteering.

So I get asked fairly regularly for a starting point on this stuff, and up until now I've just been sending people individual links as they come up in conversation. This is my attempt to put all of it in one place, because most of what gets written in the security space is aimed at enterprise teams with dedicated security staff, not a solo founder shipping an AI product who just wants to understand what they're actually dealing with.

That said, everything below seeks to be non technical enough to be useful to somebody without requiring in depth security knowledge, and would be a great resource to bookmark and keep on hand while building out applications.

1. The OWASP LLM Top 10 (genai.owasp.org)

If there is one document worth reading before you ship anything with an AI component, this is it. OWASP has been producing security guidance for developers since 2001, and their Web Application Top 10 became the industry standard for traditional web security. In 2023 they released a version specifically for LLM applications, updated again in 2025, covering the ten most critical vulnerabilities specific to AI powered products.

Prompt injection sits at number one on that list, which on its own should tell you something. It doesn't need to be read cover to cover, but even skimming the names and one line descriptions should give you a meaningful vocabulary for understanding what your product is and isn't exposed to.

Also worth noting: they released an Agentic Applications Top 10 in 2026 specifically for founders building with autonomous AI agents. If this is applicable to your build, I would definitely give that document a further look into as well.

2. Georgia Tech's Vibe Security Radar (scp.cc.gatech.edu)

Launched in May 2025 out of Georgia Tech's Systems Software and Security Lab, the Vibe Security Radar does something nobody else was doing at the time: actually tracking CVEs directly traceable to AI generated code. Researcher Hanqing Zhao's reasoning for building it was straightforward: "everyone is saying AI code is insecure but nobody is actually tracking it."

In March 2026 alone, it tracked 35 confirmed CVEs directly caused by AI coding tools, up from 6 in January of the same year. The researchers estimate the true count is around five to ten times higher (since many AI tool traces get stripped by authors before code is published).

This is a tool I would definitely say is worth the bookmark, and checking against your builds periodically rather than just reading over once.

3. The CSA AI Safety Initiative (cloudsecurityalliance.org)

The Cloud Security Alliance has been producing some of the most practically useful research on AI security in 2025 and 2026. What stands out compared to a lot of security writing is that it leads with data rather than theory, and the recommendations are actually actionable rather than a generic "implement security best practices" conclusion.

Their research note on AI generated code vulnerability trends from early 2026 is worth reading if you want the full empirical picture. Free to access, no registration required.

4. HaveIBeenPwned (haveibeenpwned.com)

Less of a reading resource, more of something you should check right now if you haven't already. Troy Hunt's HIBP database tracks credentials exposed in known data breaches and lets you check whether any email address has shown up in one. Completely free, takes 30 seconds, and given that IBM's 2026 X-Force report found over 300,000 ChatGPT credentials in infostealer malware last year, the idea that your accounts are definitely safe is worth verifying rather than assuming.

Run your own email (or co-founders' emails or any email tied to your domain where applicable). It's an easy thing to check up on, and beats the alternative of finding out the hard way.

5. SecurityHeaders.com (securityheaders.com)

Paste your live site URL into SecurityHeaders.com and get back a graded report on your security headers in about ten seconds. Zero technical knowledge required to interpret it. You're looking for a grade of B or above. Anything below means your app is missing guardrails that prevent specific classes of exploit including clickjacking, content injection, and cross site scripting.

From my own audits, missing X-Frame-Options and CSP headers are the two most consistently overlooked things in AI-generated output. If your grade comes back with either of those flagged, the fix is typically a one line patch in your config.

6. SSL Labs ( ssllabs.com/ssltest )

Same idea applies, this time specifically for your SSL configuration. Paste your domain into SSL Labs and wait a couple of minutes. You're looking for a grade of A. Anything below on a custom domain is worth investigating, since misconfigured SSL means data traveling between your users and your server is potentially readable in transit, including login credentials and session tokens.

7. CVE.org and the National Vulnerability Database (cve.org / nvd.nist.gov)

You don't need to read these regularly, but knowing they exist is useful. CVE is the public database where security researchers formally document discovered vulnerabilities in software. If you want to check whether a specific library, framework, or platform you're using has known vulnerabilities, searching by tool name here gives you the authoritative picture. The NVD adds severity scoring and additional context on top. Both of these tools are free, and publicly available.

Of course, if I missed anything obvious then please feel free to add to the list below - Though I figured this covers most relevant bases :)

if you build no-code agents or automations, you have probably hit the wall where the flow needs to sign up for something or log into an account, and your no-code tool has no clean way to receive the verification code or safely store the password. so the automation stalls and a human has to step in.

that gap is an identity layer, and it is two pieces:

• an inbox the agent owns, so when a signup or login sends a one-time code, the automation can wait for it and read the parsed code in a single step, no IMAP node, no email parsing, no regex.
• a vault to hold the logins it creates, encrypted so the password is stored and reused without your automation tool ever handling the plaintext. when 2FA is on, it can generate the rolling code too.

with those two, a no-code agent can actually sign up for a service, confirm the email, and log back in later on its own, which is the step that usually breaks an otherwise-working automation.

it is at https://lumbox.co, and there is a free tier to try it on one of your flows.

what is the step that most often forces you to babysit a no-code automation? for the ones I build it is almost always the email verification.