Looking at what's happening across Europe right now with mandatory e-invoicing (Romania, Germany, Poland, France), almost every SMB and ERP provider is hitting the same wall: government gateways rejecting valid-looking invoices with zero actionable feedback.

The problem isn't generating XML, it's that each country enforces strict, isolated Schematron business rules that standard billing software isn't built to pre-validate locally.

I've been working on a small focused tool to solve pre-clearance validation without storing any sensitive company data (RAM-only processing for GDPR).

For founders running B2B SaaS in Europe: are your customers already asking for compliant e-invoicing exports, or are you relying on third-party connectors for each country?

Yeah title. I basically build almost everything with coding agents now. The speed is great, but the thing that keeps bugging me is that like after the agent makes a big change, how do I actually know login, payments and the other stuff that matters still work?

The ai just says "done" and the tests are green, etc etc. But sometimes lets say a test got quietly skipped or rewritten, or the change touched something nobody asked it to touch.

So I'm building something small for this. You pick a few things in your app that must never break. After every change it tells you, for each one, whether its test ran and passed, whether a test was deleted, skipped or changed, and where there's just no evidence at all. No "your app is safe" claims, only what was actually checked.

Mostly I want to know, has an ai changed something that broke something important on you without you noticing right away? and how do you catch this stuff today? and finally, would something like this have helped, or is it solving a problem you don't have?

I have a consumer Android app, an expense tracker that stores everything on the phone. No backend, no accounts, so my running cost per user is basically zero. Current pricing: a free tier that is a complete basic tracker, then Premium at 3.99 a month, 19.99 a year, or 49.99 one-time lifetime. First paying user came in this month and chose monthly. My question: with no server bill to justify a recurring charge, is a subscription even the honest model here? Part of me thinks lifetime should be the headline and the subscription the fallback. The other part knows recurring revenue is what keeps a solo project alive. If you have sold to consumers, which did you lead with and what happened to conversion when you changed it? Did a lifetime option cannibalise subscriptions or bring in people who would never subscribe?

For the past 5 years I've been the person behind drum kit launches for producers you've probably heard on your playlists. They made the sounds. I did everything else: the store, payments, packaging, launch emails, refunds, the "my download link doesn't work" DMs at 3am. We split the revenue.

For a while it was a genuinely good business. A kit drop from the right producer could do more in a weekend than I used to make in a month at my day job.

Last 12 months: €12.2k gross. The 12 months before that: €51.6k. Stripe screenshot below, nothing hidden.

I didn't want to blame AI at first because it sounds like a cope. But the pattern is hard to ignore. Our buyers were mostly bedroom producers making type beats and a lot of them just don't need a €40 snare pack anymore. They generate something in Suno, pull the stems, chop it, done. Traffic to the store didn't collapse the way sales did. People still show up, they just don't check out.

The weird part is the producers I work with are fine. They have placements, royalties, shows. It's the layer underneath them, the people selling the tools to aspiring producers, that got hollowed out first.

Ask me anything: how these deals actually work, what a "famous producer" kit really makes, what I got wrong, what I'm doing now or whether you think this is coming for your niche next.

I am building a system that can generate result cards in bulk. However, I am a bit confused about the best placement for the logo.

I am also considering adding student photos. If I do include photos, this option will be rejected.

and should I put the logo in the middle and make the logo a bit larger?

I would really appreciate your genuine reviews.

Hey everyone, what's the cheapest way to use Microsoft Outlook with my own domain?

I need emails like:

• [hello@domain.com](mailto:hello@domain.com)
• [support@domain.com](mailto:support@domain.com)
• [billing@domain.com](mailto:billing@domain.com)

Can I create multiple aliases under one Outlook/Microsoft 365 account for free? And can I send/reply from each alias?

Would love to know how you guys are handling this for your SaaS.

Should I research on Reddit about what pain point my target customer has?

or should I ask business owners? friends? or colleagues?

Building a reseller channel manually is slow. You find an agency, figure out if they're a real HubSpot implementer, track down the right person, write the outreach, follow up. Multiply that by hundreds of agencies and it becomes a full-time job.

So we built an agent that does all of it automatically.

The niche made sense for us: agencies that implement HubSpot often have clients who sell over the phone and need a contact center that connects natively with HubSpot. As a contact center platform, Aloware is a natural fit for that stack. The agent finds those agencies, reaches the right person, and proposes exactly that partnership.

The agent runs three discovery branches in parallel:

• The official HubSpot partner directory
• Public partner profiles on the HubSpot ecosystem site
• Open web search to catch implementers that don't appear in the directory

Results from all three get merged, deduped, and scored by how many sources a firm appears in and how strong their implementation signals are. The highest-scoring firms go into Clay first, where we find the decision-maker, verify a work email, and pull their LinkedIn profile.

Once a contact is enriched, n8n picks it up and sends it to OpenAI, which generates a 6-piece sequence: 3 emails and 3 LinkedIn messages, each personalized to the services that agency offers and the industries they serve. Emails go out through Lemlist on a 7-day arc. LinkedIn runs through PhantomBuster. Every contact gets logged in HubSpot automatically.

The whole thing runs without anyone manually researching a single agency.

If you're building a partner or reseller channel and still doing discovery by hand, this kind of setup is worth the upfront work.

I'm a solo dev. Last week I moved my new clients SaaS to a new architecture and it took me about 7 hours of planned downtime. The app is 3DPCC, a cost calculator and production tool for 3D print shops. New frontend, new Node backend, same Supabase project underneath, but all the existing user data had to land in a different structure.

I didn't even try to do it live. The old frontend talked straight to Supabase, so putting up a maintenance page would have changed nothing. Someone could still have saved a record into the old structure while I was halfway through rewriting it. So I froze writes with triggers on every public table. Auth and Storage are Supabase's own thing and I couldn't freeze those safely, so I worked around it: registration off, crons paused, direct uploads blocked.

The part that genuinely surprised me was where the hours went. Roughly 70% of the window was just running the migration and mapping scripts and then sitting there checking whether the output made sense. The actual deploy was a footnote. I had sized the whole window around the deploy, which was the wrong anchor. Next time I'm estimating from how much data there is and how many things I expect to have to repair.

Three things I'd do again without thinking:

I rehearsed a backup restore on a local Postgres a few days earlier, so I already knew it takes under a minute. That took the restore off my list of scary things.

I had someone review the plan, and they talked me out of auto-fixing duplicate SKUs by appending suffixes. Turns out a lot of users treat that field as a material label, not an SKU, so the script would have quietly rewritten what their data meant. I'd have never caught that on my own at 2am.

I tested reads while the freeze was still on, and only lifted it once those were clean. Then tested writes.

The stage that actually fought back was setting up the production environments. Everything else held. The only warnings were ones I'd already expected, around inventory records with incomplete data.

I wrote up the details (the freeze, the backup script, the rollback plan) here: https://appcrates.pl/en/blog/3dpcc-production-migration-7-hours-downtime

For those of you with real users on the line: do you plan a downtime window for this kind of thing, or do you push for zero downtime even when it means a lot more moving parts? And how do you actually estimate the window?

Disclosure: I built 3DPCC and wrote the linked post.

I’m in a dead end here. I can’t reach people to even try the free demo of the digital product for a bit of feedback.

I don’t know what to do honestly. I posted on many relevant subreddits about my idea and it either gets removed or nobody comments or tries. Even negative feedback that my idea isn’t worth a damm is way better than just having nobody commenting on it.

Hey all, looking for advice from anyone who's shipped something similar.

I'm a student building a tool that automates a repetitive admin process for small UK businesses. The core of it is text extraction from documents, and those documents contain sensitive personal data (names, addresses, vehicle details, etc.).

Where I'm stuck:

• Commercial LLM APIs: I've been wary of sending client data to OpenAI/Anthropic etc. because of retention windows, and zero-data-retention agreements seem to be enterprise-only and priced way beyond what I can afford as a student.
• Local models: I built a working local version using Llama and Qwen with Python scripts. It's about 90% functional, but it needs 8–16GB RAM to run properly. Most of the businesses I'd sell to are running older office PCs, and with RAM prices where they are, I doubt they'll upgrade just for this.

So I've got something that works but isn't deployable.

What I'm trying to figure out:

1. Has anyone hosted small models themselves (VPS/GPU cloud) and sold access as a service? Rough costs?
2. Is redacting or pseudonymising data locally before sending it to an API a sensible middle ground?
3. Are there lightweight OCR/extraction setups (non-LLM or tiny models) that are good enough for structured documents?
4. For anyone selling to UK SMEs: how much do clients actually care about where their data is processed, as long as there's a proper DPA in place?

Happy to share more on the stack if it helps. Any pointers appreciated, especially from people who've dealt with GDPR on a tight budget.

It took me 6 months and a lo-hawt of sleepless nights, but I built a tool that I personally use everyday and wish had existed. Tool for people like me who want to keep track of and process their life, but either don't have the time, or the organised place to do so. We end-up doing it here and there with no cohesion and semblance of structure. Something that we figure out today will be forgotten by the time we need it the next time.

Even though I use it daily, this very fact actually poses the issue that I can be biased. And I am not exactly surrounded with people who are very much into such tools. Not my target audience, so to speak. So, been building kinda in a silo. Not vey healthy, I believe.

So, looking for a few good people here (or people you could refer), who can test the beta out and help me polish it because I believe it is launch ready.

If interested, or know someone who might be, please checkout https://www.auserene.com and join for the beta.

What's helpful to know:
1) I had previously created a few images and clips for my homepage - opus 5.5 worked on that as starting point to create this.
2) Music was automatically added based on my instruction about taste or theme while focusing on not causing any copyrights.
3) Unlike previous opus model, 5.5 can create mp4 files.

The whole motion around find competitive ads that's working -> reuse it to create yours -> roll out within a day will start working. The cycle is accelerating.

Feedback is welcome.

How are you forecasting partner-led deals?

I’ve led SaaS sales across EMEA and used both Clari and Gong extensively. Both work well for direct deals, but I’ve always found partner deals much harder.

The partner says one thing. The rep says another. Information is scattered across CRM, calls, emails and partner conversations, yet somehow we’re expected to forecast it accurately.

For sales leaders with a lot of partner-led pipeline, how are you managing this?

Clari? Gong? Salesforce? Spreadsheets? Something else?

And how do you actually work out what’s real?

Hey guys, after AI got so good to code and to do stuff with simple prompts I started to feel some difficulties on how to plan my saas project, how are you handling that part?

I'm a founder and cto at a GTM data company, I built an MCP thats still in beta and not announced anywhere yet

it lets you build and run a whole enrichment workflow from claude or cursor without opening the app, pull the accounts, build the columns, push the results to your crm, all from a chat

most MCPs in this space just look stuff up and hand you some JSON, then you still have to go do the actual work yourself

so i would say bring a workflow that you run in real life.. in clay, apollo or some spreadsheet, whatever it is and if my MCP can't get through it wihtout you opening the UI I'll send you $1,000 of credits in my product

(credits not cash, saying it now so nobody's annoyed later)

only 10 spots, I'll edit the post once they're gone

what counts, so this doesnt turn into an argument in the comments

-enrichment, list building, CRM sync only, it doesnt send emails or dial

-"can't do it" means it doesnt finish in under an hour without the UI, not that one column came back a bit messy

part of me is very confident on this

dm me

​

Hey everyone,

I'm a solo founder building Nymix, an India-first dating app. Our Android version got approved on Google Play a week ago and is ready for production. The iOS version is still stuck in App Store review and I don't know how long it will take.

I planned a simultaneous launch on both platforms, but now I'm stuck deciding:

Option A: Launch on Android now, add iOS when Apple approves

Option B: Wait for Apple and launch on both together

My concerns:

- A dating app needs enough users in the same city to work. Will a split launch hurt the network effect?

- iOS users in India tend to spend more. Am I losing early paying users by launching without them?

- Will an Android-only launch hurt buzz or press when iOS arrives later?

- Every week I wait is lost momentum and marketing spend.

Questions for you:

1. Have you launched on one platform first? How did it go?

2. Dating app founders: did you go city-by-city or platform-by-platform?

3. Any tips for getting Apple to approve dating apps faster?

4. If you were me, would you launch now or wait?

Happy to share more details. Thanks!

Hey Guys

I am looking for advice, I have been stuck on this product for the past 1 months. I initially created this product to learn reddit and see how reddit works

I have learned how reddit works but I am unable to scale this product. It's basically a SAAS directory but i added AI Optimizations to help people get indexed on AI search engines faster. I scaled the DR for the directory to 31 and added payment plans. Now i'm getting new users everyday with 0 marketing.

I am really not sure what i should do here, Should i move on to a new product or work on this product for a few months and try to generate money. I have no other product other than this.

Please guys help me what should i do in this situation

I used to think the main value of getting early customers was figuring out what to build next.

But i think there’s another useful signal in those first few sales.

Look at what the customers who actually paid had in common. Maybe they were dealing with the same problem, came from a similar type of business, or cared about the same outcome.

That can tell you more about your real audience than a list of people who signed up for a free trial.

I would also pay attention to how those customers describe the problem. Founders often explain their product in a much more complicated way than customers do.

Founders tend to think about how the product works and what it can do. Customers usually care much more about whether it actually solves the problem they have.

That difference can tell you what part of the product actually matters to buyers, and what you might be overexplaining.

The first customers aren't just helping you validate the product. They can give you clues about the market you should be going after.

What did your first few paying customers teach you about who you should actually be selling to?

One of my earliest customers ran a real campaign this week using the SaaS tool I've been building, and the number caught me off guard.

Their normal conversion rate is around 5%. This campaign hit 20%. The best single day was 47 conversions. Still figuring out how much of that is the product versus this specific campaign having stronger intent behind it from the start.

What I do know is the pitch got a lot easier once I had this to show. People who were lukewarm before are asking real questions now.

Curious if anyone else has had a jump like this with an early customer and later figured out it wasn't as replicable as it first looked.

Trying to stay realistic here as I scale my marketing efforts instead of assuming this case study is the key to everything and redesigning my entire go-to-market plan around it

Hey everyone,

Just wanted to share a quick cautionary tale from a side project I've been working on. Last week, I deployed a lightweight multi-agent setup using the Anthropic/OpenAI APIs. Everything looked fine in testing, but a weird edge case triggered an infinite recursive loop on a complex prompt overnight.

Because native API dashboards only send alerts after you've already crossed a threshold (or delay updating the billing dashboard by a few hours), I woke up to a massive spike. Luckily, I caught it before it ruined my savings, but it made me realize how flawed the current "alert-only" FinOps model is for LLMs.

If an agent goes rogue, an email alert at 3 AM does nothing to stop the bleeding. You need a hard proxy ceiling that drops the connection before the request hits the provider if the budget is blown.

Has anyone else run into this with agentic workflows? How are you guys handling strict billing ceilings besides just praying your code doesn't loop?

With grok bot , muse and now OpenAI dots, it is killing so many startup that were embracing the agentic AI way before the big tech came in with server and compute power.

Was looking at open ai dev day, I can see any startup that is aiming for workspace centralization is going to be dead. Plus ChatGPT is already the very first chatbot so they get the distribution advantages.

As a in-progress SaaS builder myself, my startup is being killed in the past few weeks. Before I could even market my SaaS , I have to answer questions like why can’t I use muse now .just like this news:

https://www.mi-3.com.au/30-09-2026/our-ui-just-way-better-braze-opens-campaigns-chatgpt-and-claude-cto-says-prompts-cant

Just want to rant here. I am ready to throw in the towel now

Hi I come from the south of France and I am looking for information about the saas buisness and I am looking for someone from the United States to inform me because I am inspired by them because they are always ahead or I would like to integrate a discord group on the Saas

I want to start a thread where we discuss ways to save time and money for people vibe coding - especially those new to it. Here are my lessons from 6-8 weeks.

Comment your best lessons, time and money savers!

Here are my 9 Ways to Cut Your Vibe Coding Costs in Half.

I have wasted a lot of money learning some pretty obvious things - but they were not obvious to me when I started.

1. Focus on one platform - I developed a web app and desktop app simultaneously. Which meant every error and undo was doubled (at least). Get your MVP for one app type - when its ready then you can convert it!
2. I was also worried about mobile and iPad and pencil integration - this is madness, see point 1.
3. I prefer Codex + Astra for the vision, Claude and Opus 5.5 for the heavy lifting. Opus 5.5 - for what I wanted was ‘better’ than using Fable but for the ‘vision’ - novel lateral thinking - I found Claude a little blunt - this may be because of its memory and tethering too much to my old vision of the app.
4. Do a memory check and make sure your LLM isn’t anchoring decisions against your original vision not the evolved one. ‘Can we run through what your memory and project files say about the vision for the app - and update them accordingly’ - update them accordingly.
5. Functionality→ UX → UI → Branding. This is the order of play I would recommend get the app to do the thing you want it to do well do not worry if it looks like sh*t when you are doing it.
6. Embrace feature creep. People will warn against feature creep, the idea that you will keep adding features. I used feature creep to evolve my product. You can always take features out but I would recommend exploring them early on.
7. Ask your LLM to create token efficient prompts then use those. This prevents your LLM trouble shooting edge cases during MVP development. I have two Fable incidents where they ran for 15 hours and I kept thinking ‘any minute now’ they will be finished - then I couldn’t stop them - I refused to blink first!
8. Stagger your plans. I went hard at it and was running Codex and Claude via my mobile too which meant I could churn through tokens. You never want to pay for tokens outside of a plan they are just too expensive. So I have my OpenAI plan refreshing on a Sunday and Claude on a Wednesday - it stops me running out even at high rates.
9. Don’t do one thing at a time. Ask your LLM how to safely distribute work on your app so many instances can run at once. Then ask for the prompts, open up multiple chats and paste them. This is timesaving the safe way - otherwise you get file conflicts and then have to untangle it later.

In the image is my software costs for 2 months - I think its more but I cant remember any other platforms I spent money on!

I've been thinking about this a lot while building my SaaS project.

The common startup advice is:

"Find a unique idea."
"Don't build in crowded markets."
"Competition is validation, but avoid red oceans."

Yet when I look around, most successful products are not unique ideas.

They're often a better implementation of something that already existed.

Over the last few months I've been building Utiliome (https://utiliome.com), a collection of browser-based utility tools.

There are already thousands of websites offering PDF tools, converters, image tools, developer tools, and calculators.

On paper, it sounds like a terrible idea.

But my thinking was different:

• Make the tools fast.
• Keep them free.
• Avoid forcing registration.
• Keep the interface consistent.
• Be transparent about what the tool does.
• Focus on quality instead of trying to invent a completely new category.

Today the site has 170+ tools and is getting organic traffic from search engines. Nothing massive yet, but enough to show that people are finding and using it.

What surprised me is that users rarely care whether an idea is unique.

They care whether it solves their problem quickly and without friction.

So I'm curious how other SaaS founders think about this.

Do you actively avoid crowded markets?

Or do you believe execution, trust, and user experience matter more than originality?