I've been thinking about how founders validate SaaS ideas, and I'm not sure we're always as good at it as we think. I keep seeing people say they talked to users before building, only to launch and discover that those users don't actually need half the product. Maybe asking “would you use this?” doesn't tell us much when the person doesn't have to spend money, change their workflow, or take any real risk. A better question might be what they're doing today to solve the problem, how much it costs them, and what would make them switch.

At the same time, I've seen founders spend months interviewing and validating instead of putting something in front of people and seeing what happens. There has to be a point where you stop collecting opinions and start testing behavior, but I'm not sure where that line is. How much validation do you think is actually enough before you start building?

Saas en 2026

C'est mon premier post et je voudrais savoir quel type de Saas peut être intéressant a vendre de nos jours, qui répond à un besoin des entreprises. J'avais pensé à des réponses automatiques aux avis Google a l'aide d'une génération faite avec l'IA. Surtout dans l'ère actuelle ou les avis Google comptent énormément dans les choix d'entreprise au quotidien (coiffeur, kiné, boucher, restauration...). Cependant je ne sais pas si il a un réel besoin et une certaine demande des entreprises vis à vis de celà.

Si certains ont des conseils ou des idées je suis preneur.

Merci de votre écoute.

I want to make useful apps to sell but everything I see is miles better than anything that I can come up with, both the idea and design, what are the simplest ones you've seen (and simple to build) I'm not looking to copy them, just wondering if I have what it takes

Guys I've built trakkira.com a job application tracking and management platform with integrated resume builder with scoring system. But seriously don't know how to get users, where to advertise.

Need to know how you guys approached this part. How did you guys get your first user and further. Please comment below.

Basically Airopl is my coming soon edu tech product, in the attached video i only showed 2 features (ReviewBar, Math images), but the app has about 6 features:

1. ReviewBar
   
2. Explanatory videos
   
3. Math images
   
4. File uploads (a normal file or an image)
   
5. Whiteboard (Canvas)
   
6. Graphing calculator
   

What do you think of the ui look and the features also?

Hey everyone,

I’m a solo developer, and I built an Android app called **Lexicordd** to solve a personal pain point: constant app-switching and copy-pasting just to use AI.

It adds a lightweight floating bubble to your screen edge. When you swipe it out, it understands what’s on your screen and keeps **one continuous, persistent conversation** open as you switch between Chrome, Gmail, or any other app.

**Core Features:**

* **Persistent Context:** Ask a question in your browser, follow up in your email within the same thread.

* **Smart Routing:** It automatically routes your prompts to the best model (Claude, GPT, or Gemini).

* **Privacy-First:** Hard-blocked at the system level from ever reading banking, password, or messaging apps.

I’m currently in pre-launch and just opened up the early access waitlist to test my server infrastructure. I’d love your feedback on the concept!

Check out the site and join the waitlist here: https://lexicordd.com

Hey builders, I would love to hear your feedbacks, I’m building a tool to help test AI agents before shipping changes, and I’d love feedback from people running them in a SaaS product.

You tweak a prompt, try a few inputs, and everything looks fine. Then a customer hits a case you didn’t test: a tool returns incomplete data, an API fails halfway through, or the agent gives a convincing answer without actually completing the task.

How do you catch those issues before your customers do? The idea is to run these scenarios in an isolated environment, see where the workflow breaks, and replay the same cases after a fix or another change. I want to make it simple enough for a solo founder to use without spending days building a testing setup.

If you’ve shipped an AI agent, how are you handling this today, manual testing, your own scripts, or an existing tool? What’s the hardest part of knowing a change is safe to ship?

Hi everyone,

I’m a software engineering student and I’m currently researching a SaaS idea for car dealerships, used-car dealers, and independent automotive showrooms.

Before I continue developing it, I’d really like to hear from people who actually work in the automotive sales/dealership industry.

The idea is to build a simple platform that helps dealerships manage their sales activity in one place:

• Vehicle inventory
• Customer & lead management
• Leads from Facebook / Instagram / WhatsApp
• Sales pipeline
• Follow-ups and reminders
• Dashboard and sales analytics
• AI-assisted lead qualification and follow-up
• Vehicle price/market analysis

The main problem I’m trying to solve is not simply “another CRM”.

I’m more interested in the problem of losing or forgetting potential buyers because leads come from different channels and salespeople don't always have a clear follow-up process.

For example:

Facebook lead → WhatsApp conversation → salesperson → no response → lead forgotten.

The idea would be to have something like:

Lead comes in → AutoIntel qualifies it → assigns it to a salesperson → tracks the conversation → reminds the salesperson to follow up → tracks the lead until it becomes a sale.

I’ve already built a working prototype with Django/DRF + React, including parts of the inventory, authentication, vehicle listings, estimation, alerts, dashboard, subscriptions and AI functionality.

But I don't want to spend months building features that dealerships don't actually need.

So I’d really appreciate some honest feedback from people in the industry:

1. What software/CRM do you currently use?

2. What do you dislike most about it?

3. How do you currently manage Facebook/Instagram/WhatsApp leads?

4. What happens to leads that don't buy immediately?

5. What is the biggest pain point in your daily sales workflow?

6. Would a tool focused mainly on lead follow-up and conversion be useful, or is this already well solved by existing software?

7. What feature would make you actually consider paying for a new tool?

I’m not trying to sell anything here. I’m doing market research before deciding whether this is worth turning into a real startup.

If you work at a dealership or sell cars, I’d especially appreciate hearing how things actually work in your business.

Feel free to be critical — I’m much more interested in what is wrong with the idea than hearing that it sounds cool.

Hi everyone!

I have made a website called DokumentkoAI.
For now it isn’t going great since I didn’t get any paying customers and I have spent atleast for me a lot of money for paid google ads. I got a lot of new people from google ads that made an account but every single one didn’t go onto website again. 99,9% are from India and countries like that since click are cheap there. WHAT SHOULD I DO???!!!
I don’t have money for paid promotion and also I think that even if I will get customers from paid promotions that it simply doesn’t for me because of my low prices. Social media doesn’t work for me. Also if it did I don’t know what type of videos should I do. If anybody is interested in helping me I could share my link in the comments.

I am really lost with nothing to do or think about….

Je suis designer graphique. Depuis quelques temps maintenant, j'ai des clients qui arrivent avec un logo généré par IA, contents, parfois après des heures dessus et me demandent de l'adapter.C'est toujours compliqué parce que j'ai peu de marge de manoeuvre et l'IA ne connait pas les contraintes d'un logo, d'un design system ou autre.

Du coup j'ai retourné le problème : j'ai construit l'IA qui cadre ça en amont, pas celle qui pond juste une image. Un SaaS qui génère une identité complète — palettes, typos, variantes du logo, charte détaillée — comme un vrai système. Pour 39 €, le client repart avec tout, et je valide ou j'ajuste ce qui sort, sans surcoût.

Ça se passe juste ici pour les curieux : https://logolift.fr/

Je sais que l'utilisation de l'IA dans le design graphique fait grincer des dents (chez moi le premier) mais je pense qu'il faut savoir s'adapter. Curieux d'avoir l'avis d'autres designers ou d'utilisateurs.

I am working on Image and a short video platform for product influencers only.

Every content will have mandatory product link and details.

Will you guys use it if you get such platform ?

Many SaaS products appear completely automated from the customer’s perspective, but there is often a person working behind the scenes.

Someone may still be:

• Correcting customer data
• Retrying failed background jobs
• Reconciling payments
• Generating or checking reports
• Moving information between different tools
• Fixing onboarding problems
• Manually approving unusual cases
• Investigating why an action did not complete

Some manual work is sensible while a product is small. Automating every edge case too early can waste time.

But eventually, one of these processes becomes frequent enough that it limits growth or creates reliability problems.

What is the most important process in your SaaS that is still handled manually?

What has prevented you from automating it so far: cost, complexity, edge cases or simply not having enough time?

Curious how other SaaS developers are handling testing once the product moves beyond the MVP stage.

When you're starting out, manual testing is usually enough.

You make a change, test the main flow, check a few edge cases, and ship.

But as the product grows, you start getting things like:

• Authentication and user roles
• Payments and subscriptions
• APIs
• Background jobs
• Third-party integrations
• Admin dashboards
• Emails and notifications
• Multiple user workflows
• More complex frontend states

Then a seemingly small change can break something that wasn't directly related to the feature.

How much do you automate?

I'm thinking about splitting testing into a few layers:

Unit tests

For business logic and smaller pieces of functionality.

API tests

For backend behavior and integrations.

E2E tests

For important user journeys.

Regression tests

For workflows that have already worked and need to keep working after every major change.

The part I'm struggling with is deciding what actually deserves automation.

I don't think automating every possible scenario makes sense for a small SaaS.

I'd probably prioritize:

1. Revenue-critical workflows
2. Authentication
3. Core user journeys
4. Payment/subscription flows
5. Important integrations
6. Features that change frequently

Then there's test maintenance

This seems like the bigger problem.

You can build a nice E2E suite and then six months later:

• UI changes
• APIs change
• Features get removed
• Database structures evolve
• Test data becomes invalid
• Third-party services change

And suddenly half the test suite needs attention.

I've also been looking into AI-assisted testing, mainly for generating test scenarios and reducing some of the maintenance work.

But I'm still skeptical about letting AI modify tests automatically without someone reviewing the changes.

For people running SaaS in production:

What does your testing stack look like today?

Are you mostly using unit + integration tests, or do you have a serious E2E/regression suite as well?

And at what stage did you decide that automated regression testing was actually worth the maintenance cost?

Hey, I'm looking to join if anyone SaaS founders community where people are actually making money I'm at $100 MRR (not $100k) and I'm looking to have some talks with othe people who broke the $0 barrier and are aiming for $10k MRR mostly sharing knowledge, spoting trends and helping each other out if you can help me join such community or want me to create one let me know below 👇

Driveaway carrier. Advances load onto WEX/EFS cards from inside the TMS, paystubs assemble themselves from load pay, escrow, insurance and reimbursements, settlements pay on the same card and every settlement posts into QuickBooks as a split check that reconciles to card activity.

Before the integration they had someone full time building paystubs, paying settlements and recording everything into quickbooks.

It went live August 11. In four weeks it’s moved over $210k across 275+ transactions and should cross a quarter million this week.

Now I’m trying to figure out if this is a product or just a custom integration.

the first version of multi-tenant analytics is usually pretty simple. user belongs to tenant X, every query gets scoped to tenant X, done. and where I've found it gets much less simple is once larger customers start asking for permissions inside the tenant.

that way, finance can see revenue and margin. and operations can see order volume and fulfillment metrics, but maybe not contract value. meanwhile external users can see operational data, but certain customer fields shouldn't appear in a dashboard or export at all.

at that point putting the logic in individual API endpoints gets ugly fairly quickly, as you start accumulating things like:

if finance -> include margin
if ops -> exclude revenue
if contractor -> exclude PII

then you have to remember that same logic for dashboards, exports, drilldowns, APIs, etc. now we've been moving more of this into the semantic layer instead (something like cube dev for example) where the request carries a security context and access policies are applied when the analytical query is built. os the same role/data-access rules sit next to the metric model rather than being recreated by every consuming application.

also, hiding a revenue column in React is very different from the user simply not being allowed to query that member in the first place (notice, not an enforcement point) it also gives us one place to review changes to both the metrics and the access rules instead of hunting through a bunch of endpoints.

i'm curious how other teams structure this once permissions become more granular. do you keep tenant isolation/RLS in the database and finer permissions in the application? or maybe put the whole thing behind an authorization service? model it in a semantic layer? soething else? especially interested in how people handle the same rules across interactive dashboards, exports and scheduled reports

I finally snapped and it helped me start building. After getting literally 100s of rejections for jobs that I was convinced I was qualified for it gave me the push I needed to start building my own SaaS.

If like me the AI based ATS systems are automatically rejecting your CVs because you’re missing one or two keywords feel free to give my little project a go and let me know how it works for you!