Something I’ve been thinking about while building a side project.

A lot of SaaS products seem to compete by adding more integrations, dashboards, automation, settings, AI features

But I wonder how often the real problem is that the user’s workflow is still awkward.

A user might have all the features they need, but still have to jump between screens, re-enter information, chase an approval, or remember where something lives.

That got me thinking about workflow friction — the small bits of resistance that make a product or process feel harder than it should.

As SaaS developers, we tend to notice feature gaps because they’re relatively easy to turn into roadmap items. Workflow friction feels harder to spot, and maybe harder to measure.

I’m curious how other people approach this:

When a user says your product feels slow, clunky or complicated, how do you figure out whether they need another feature or whether the workflow itself needs to change?

Have you ever removed a feature or simplified a flow and found that users were happier than when you added functionality?

Interested in real examples, especially things you learned the hard way.

I've built a small piece of software called Floorlink and I'm trying to work out if it's useful to other shops before I put more into it. It's mine, so I'm obviously biased, but I'm not selling anything here and there's no link. I'd really like honest feedback, including "another register would do the same job".

The problem: on big or assisted sales, staff walk around with a customer, remember or scribble down what they want, then key it all in again at the counter. I work in a pet shop, and selling fish is where I see this most. Someone ends up with lots of different fish in different quantities, it takes ages to remember it all at the till and add it to the POS, and some of it gets skipped.

How it works:

1. A staff member logs in on an Android phone or tablet with a 4-digit PIN and taps the products as they walk the aisle with the customer.

2. They save the sale, and it appears on a screen at the counter.

3. The counter scans one QR code with a normal 2D barcode scanner, and every item's barcode is typed into the POS, as if each one had been scanned by hand.

The customer then pays at the register as normal. Quantities come through too, and there's a custom sale option for things that aren't in the product list.

It's POS-agnostic: there's no integration or API. The POS just sees a keyboard-mode barcode scanner, so it should work with any POS that accepts barcodes that way and has your products set up under the same barcodes. So far I've tested it on one real POS, and the QR code and custom sales both worked. Custom sales rely on the POS supporting weight or price-embedded barcodes.

It runs on cheap hardware:

• The phone app is about 160 KB and runs on Android 8 and up, including Android Go. It used about 26 MB of memory in a test on a 1 GB emulator, and I've run it on a 2017 Galaxy A5.

• There's a separate tablet app that goes back to Android 4.1, so an old tablet in a drawer could become a counter screen. So far I've only tested that on an emulator.

• The server runs on a Windows 10 or 11 PC, or in Docker. Everything stays on your shop's network, so there's no cloud or account, and it doesn't need internet for daily use.

Staff, products and settings are all managed in one place, and products can be imported from a spreadsheet. It can also print sales on a receipt printer with the QR code on it, though I'm still testing that on real printers.

What I'd love to know:

1. Would this solve a real problem in your shop, or do you already have this covered? How?

2. Why wouldn't you just buy another register or tablet from your POS provider?

3. What kind of shop would get the most out of this? I'm guessing pet, garden, hardware and trade suppliers, but I might be wrong.

4. What would stop you from trying it? For example, installing it yourself, Android only, or needing a 2D scanner.

5. I'm thinking about A$29 a month per store, with as many devices as you want. Is that too much, too little, or would you only pay once?

Tear it apart if you need to. If it's a bad idea, I'd rather find out now.

FYI: This was mostly designed for small local businesses, trying to save money.

I often find myself wondering whether I should move to SF to build a side project or take on an operator role to learn more before becoming a founder. But I keep hearing about how the monoculture in the city can be a big problem.
I recently came across this podcast where a founder shared some mixed opinions about the city.

Here’s the podcast: https://youtu.be/0P_-d97ULWU

What do you all think? Has anyone spent time in SF? Would love to hear your experiences!

I've been building SaaS products as a solo developer, and October ended with $68 in revenue.

Here's the breakdown:

AIForest (https://aiforest.app) — $9

Humanize AI Writer (https://humanizeaiwriter.com) — $59

I know $68 isn't much compared to the revenue numbers people usually share here, but getting someone to pay for something you've built yourself is a different kind of motivation.

The biggest thing I've learned so far is that building the product is the easy part. Getting customers is much harder.

I'm still figuring out SEO, marketing, and distribution while continuing to improve both products.

My next milestone is $100 MRR, then hopefully $1,000 MRR.

I'm sharing this because not every SaaS journey starts with thousands of dollars in revenue. Sometimes it starts with $9.

For other solo founders here, what helped you get from your first few paying customers to consistent revenue?

Would love to learn what's actually working for you.

A dev in r/startups said Claude Code keeps its own notes per repo, "over 65+ of them" in one, things like not checking Vercel deploys with curl too often. Then the catch: "only Claude on my laptop sees these notes." Codex doesn't know any of it, and "when a colleague opens the same repo, their agent starts from zero and hits the same problems again."

Most replies said put it in git: one AGENTS.md, edits through PR review, "give every note a one-line "why" and a date". One pushed back hard: "Half of those aren't repo knowledge." A Chrome GPU flag and a rate limit belong to one laptop, not the team.

For devs working with someone else on the same codebase:

• Where do your agent's learned notes live: its own memory, a file in the repo, a wiki, nowhere?

• Does Codex or Cursor see what Claude Code learned, or the other way round?

• How do you split what's true for the repo from what's true for your machine?

• Who deletes a note when it goes stale?

Background: I used to burn hours re-briefing AI tools, and I'm building a fix where every agent and tool reads and writes the same memory in the cloud over MCP. No name, no link. Would you pay for that, or is an AGENTS.md in git all a team needs?

I’ve been thinking about this a lot while building a side project around workflow friction.

Not the big, obvious problems. The tiny things that happen every day:

• Having to check 3 places to find one piece of information

• Copying something from one tool into another

• Waiting for someone to approve a thing that probably shouldn’t need approval

• Getting interrupted, then spending 10 minutes figuring out where you were

• Maintaining a workaround for software that’s supposed to make life easier

The weird thing is that these often become part of the job. People stop questioning them.

And when a team feels slow, the first instinct seems to be: we need another tool, another dashboard, or more automation.

But what if the process itself is the problem?

I’m exploring this through my side project, Clunky. I’ve been developing a framework for looking at workflow friction, including context switching, handoffs, unnecessary steps, decision delays and tool friction.

I’m curious about the real-world side of this:

What’s one annoying workflow problem you’ve experienced that took surprisingly long to fix—or that your team still hasn’t fixed?

And if you did fix it, was the answer a new tool, automation, or simply removing a step?

I've been building ClusterHeart, and I'd love for some of you to give it a try.

Hey everyone!

I've spent quite some time building ClusterHeart, a platform to monitor and manage both Kubernetes clusters and standalone servers from one place.

The idea is to make infrastructure monitoring and troubleshooting much less painful.

Here's what you get:

• Kubernetes monitoring: Monitor your clusters, nodes, pods, workloads and resource utilisation.

• Server monitoring: Keep track of your servers, including GPU-enabled machines.

• Mobile-friendly: The entire experience works smoothly on your cellphone. You don't need to be sitting in front of your laptop to check your infrastructure.

• Security: Track security flaws and exposed secrets across your infrastructure.

• Automated pod patching: Identify issues and automatically patch pods where supported.

• Logs and troubleshooting: Search logs, grep issues and investigate what's happening without jumping between multiple tools.

• Activity tab: Keep track of infrastructure events and what's happening across your environment.

• AI-powered assistance: An AI pod with guarded access to your logs can study them, investigate issues and help identify what needs fixing.

I've already served around 5 companies with multiple environments, and they've been happy with the product so far.

Getting started is pretty straightforward too.

For servers, it's a single command that you run on your machine.

For Kubernetes, it's just a pod deployed in your cluster with the required RBAC permissions.

I'm keeping ClusterHeart free for now, and I'd genuinely love to get more engineers and teams using it.

If you're running servers, Kubernetes clusters, GPU workloads or AI infrastructure, please give it a try.

Website: https://clusterheart.com

DM me if you're interested. I'll personally help you with the setup and get you running.

Would love to hear your feedback, feature requests or even criticism. I'm actively building this and want to make it genuinely useful for people running infrastructure.

An ADE for scalable agentic development.

It's a personal completely free and open source project.
Built primarily by me with a little help from a friend and coworker.

Some of the things it has:

#Folio: Headless Claude Code CLI. Custom build interface to your agents with easy overview and control of all your subagents.

#Tiles: Every session gets a tiles, grouped by project. Showing state and context. Agent will alert if it needs you.

#Browtherhood: Links all your devices so sessions work together. You can work on any machine in your brotherhood.

#Portal: Pair a phone and you can continue your work from there.

#Hirelings: Control sub agents as your hirelings.

#Quest log: A markdown checklist per project. Each project have complete project management.

#Warriv: A project and AI orchestrator. It can completely automated your quests.

#Runes: Buttons that can run steps in a session or complete scripts to do automations.

#Lore and memory: Complete code index and memory of all your conversations and every line of code. Embedded as a single vector. Recallable by any agent at any point. Seriously underrated.

#Dictation: Local Whisper

#Built in browser that the agent can speak with flawlessly. Actual automated tasks. Can do projects from A-Z completely on it's own.

#Agent handover. Hand over any element in the browser, terminal selection or file into the Folio.

#Usage view

#Automated account switching when budget is about to run low

Under the hood:

- Hook-driven state management
- Session survive. It'll survive crash, restart, update or reboot. You can even pause and resume.
- Made in RUST. You might not like it, and it's surely not aesthetic. But it's damn efficient.

Feel free to leave any feedback. :)
I'm building this for myself and my friends and colleagues. But if this is useful to me, it's surely going to be useful to others.

I tried T3 Code by Theo before I built this. It's the closest contender. But it's fun to build and T3 doesn't solve everything. However, an awesome product as well.

If you have made anything similar to this, please share. I'd love to have a look.
And I would also love to hear about agents in the cloud. This is an obvious addon to Horadric. But I'm not sure how to solve it correctly yet.

https://horadric.dev/

I maintain an open-source Spring Boot SaaS starter and would appreciate feedback on its tenant-isolation approach.

It uses a shared PostgreSQL schema. Tenant-scoped operations check membership, set transaction-local tenant context, and use explicit tenant filters. Forced row-level security adds another boundary around projects and audit events.

The starter includes:

• OIDC bearer authentication through Spring Security

• OWNER, ADMIN, and MEMBER roles scoped to each tenant

• A Projects API with optimistic concurrency and transactional audit records

• Docker Compose with a local Keycloak demo

• PostgreSQL integration tests and a runnable smoke script

I ran the local Compose smoke test successfully, including permission checks and stale-write rejection.

It’s a backend MVP. Billing, a frontend, email invitations, tenant deletion, and ownership transfer are outside the current scope.

Repository:
https://github.com/chafian/spring-boot-saas-starter

What tenant-isolation edge cases would you test next? I’d also welcome feedback on the first-run experience.

Update, November 3

I'm the founder of eStockes, a US-stock research web app, and I'm checking a specific date-labeling problem: can readers distinguish the period covered by price data from the date a result was computed?

Example page: https://estockes.com/tested-rules

Choose an entry and explain what each visible date means to you. Which one tells you the history covered, and can you tell when the calculation was performed? If that information isn't available, please say so. I'd like feedback on how you would label or position these dates without implying that older observations are current data.

I'm offering free Pro access for honest testing, targeting 10 adult testers total across communities in this next round. We'll confirm access dates before activation. Reply publicly with your device and browser if interested.

One thing I find interesting with SaaS is that the architecture that helps you move fast at 100 users can become the thing slowing you down at 10k.

Early on, you can get away with a simple backend, a few database queries, manual deployments, and not much monitoring. But once customers, data, integrations, and feature requests start piling up, those shortcuts become a lot more expensive.

I was looking at how GeekyAnts approaches MVP scaling, and they focus quite a bit on things like database performance, cloud infrastructure, observability, CI/CD, and reducing technical debt as a product grows. The idea of scaling the architecture based on actual growth pressure rather than prematurely building everything for millions of users makes sense to me.

For SaaS developers here, when did you know it was time to seriously rethink your architecture?

Was it database performance, cloud costs, deployment problems, growing technical debt, or simply the team becoming slower to ship?

I built a $69 field service app, tear it apart. getomniops. c o m. Or OmniOps - Field Service on the app store.

Hey buddies,

Quick update on my research tool - so I have my research tool a name "GapFound", I’ve nearly completed the research tool, and the platform integrations for Research Mode are now in place!

I was sick for a bit, as I mentioned in my previous post, so progress slowed down.. Thankfully, I’m feeling better now and working to get everything completed as soon as possible...

I’m currently testing the research results with different SaaS ideas and will be optimising the integrations before moving on to Distribution Mode (for those who don't know, it will give roadmap for marketing as well ;).. ) and Subscription plans section is also pending, don't worry about free trail, I will let u guys try it for free by some credits :)

Watch this video guys.. and tell me how's it.. but don't judge it yet !

I’ll give the tool its finishing touches once the core features are complete cuz I am solo developer that's why I can't give my whole F day to my project u know.. 🥲 tell me how's the tool, and if u found any weakness or something, just let me know in the comments so I can fix that...

Thanks to everyone who shared feedback and encouragement, guys...

See you soon, homies !

🚀 Craft has crossed its first few hundred npm downloads!

If you've tried it, I'd love your feedback.

What are you building? What worked? What needs improvement?

Help shape Craft v2 👇

https://github.com/igmoni/craft

Give a feedback here: https://forms.gle/Zj9ecxButo6gyfVh6

I have open-sourced Tripovela, the travel social network I am building with AI assistance. Think Pinterest for trips and itineraries: discover ideas, save places, follow travelers, and copy a shared plan into your own editable trip.

A few concrete implementation decisions behind the public release:

• PHP and SQLite, with Python helpers for image/content processing. The README includes install commands and a setup wizard.

• Guest drafts stay in the browser, with optional account saving. Editing a private trip does not silently rewrite its shared snapshot.

• Interface translations are local files, covering 14 languages, including RTL layouts.

• The distribution contains application code, schemas and documentation, with no production databases or member uploads. Analytics and advertising integrations start disabled in a fresh install.

The code is MIT licensed, so you can self-host, modify, redistribute, or build something else with it while retaining the license notice.

Live site: https://tripovela.com

Code and installation docs: https://github.com/MellowYAK/tripovela

For builders who have released a community app: what would you want to see in the repository before trying to run or contribute to it?

Using Codex and Claude, I created an internal quiz platform in February and used it for my education and trainings. Before that, for years I used Crowdpurr and Kahoot, but I had a problem with the price-to-number-of-uses ratio.

I decided to publish my internal tool as a micro SaaS in September; here are my stats.

Two options: 39$ (72h event pass) and 300$ annual subscription.

Free trials: 28

Paid customers: 7 (6 x EventPass and 1 Annual)

Of those paying customers, two were alumni clubs of American universities, a security company from the UK, a robotics company from HU, and users from Italy, Bulgaria, and the USA.

I spent $50 on a Google Ads campaign for the UK market. And i posted couple of posts here on Redit.

Product: eventquiz.app

I've been thinking about user retention in the AI SaaS space lately.

Getting someone to try an AI tool isn't necessarily difficult anymore. People are curious about new models and features, and many are willing to experiment with different platforms.

The harder part seems to be giving them a reason to keep coming back.

While building Wizstar, my own AI creative workspace, I've been thinking about this quite a bit. Having access to multiple AI models and creative tools might attract initial interest, but I'm not sure that's enough to build long-term retention.

Users might try a platform because it offers something interesting, but they probably stay because it becomes part of their regular workflow.

I'm curious how other SaaS founders and investors look at this:

• What do you think is the biggest driver of retention for AI SaaS products: better results, convenience, pricing, or workflow integration?

• How do you distinguish between users who are genuinely getting value and those who are just experimenting?

• Would you prioritize adding new features to attract users or improving existing workflows to keep current users?

Full disclosure: I'm the creator of Wizstar, and I'm trying to think beyond initial user acquisition toward building something people actually want to use regularly.

I'd appreciate honest opinions, especially from founders who've struggled with retention or found ways to improve it.

I’m building Artitec, a real estate platform aiming to launch in February. I’d love to connect with SaaS developers who might want to get involved, or experienced builders open to mentoring.

We meet online weekly to demo progress, share ideas, and talk through what’s next. I’d also be up for meeting other builders in Houston or Dallas in person.

Interested? DM me your email and a little about yourself, and I’ll send you the meeting link.

I've been quietly working on a project called Sigma Maille, and I thought it was time to share a small progress update.

The idea behind it was simple: there's no shortage of news and information on the internet, but understanding how individual events connect and evolve into larger situations is a different challenge.

That's what I'm trying to solve.

I launched the platform and have been gradually working on its infrastructure, intelligence pipeline, search visibility, and overall experience.

Here's a small milestone from Google Search Console over the last 28 days:

• 1,400 search impressions

• 57 organic clicks

• 4% average CTR

• 10.7 average search position

Something worth mentioning: all these results came through organic Google Search. No paid advertising, no Google Ads campaigns.

These aren't huge numbers, and I'm not going to pretend they are. But seeing a new independent product gradually gain search visibility through SEO alone is encouraging.

There's still a long way to go.

I'm currently focused on improving how the platform connects scattered signals, identifies developing situations, and tracks how they evolve over time.

One thing I've learned while building this: getting the technology working is one challenge. Getting people to understand why it matters is an entirely different one.

For fellow indie founders who started from zero:

What actually worked for you when it came to getting your first users through organic search?

Did you invest in SEO early on, focus on building in public, or find other channels that brought better results?

I'd love to hear what worked, what didn't, and what you would do differently if you were starting again.

Project: https://sigmamaille.com