It's 2026, and Micro SaaS is still a massive opportunity!
Yes, use AI. But use it the right way.
PRACTICAL > HYPE ✅ One problem, one promise, one price ✅ Validate with real users before code ✅ Automate the boring, review the critical ✅ Self-serve onboarding + clear docs
AVOID THE NOISE ❌ Feature soup to chase "everyone" ❌ Vanity metrics over paying customers ❌ Hype hacks without distribution ❌ "AI slop" that replaces human judgment
- Distribution BEFORE development. - Design UI that sells the value. - Protect your calendar like equity.
SYSTEMS THAT BUY FREEDOM - Weekly rotation: build → ops → growth → slack - Automations: n8n for chores, Aidbase for support - Pricing: monthly, yearly, pay-once for cashflow
In my 5+ years of building SaaS, the playbook has completely flipped.
Back in 2020, the default was: → Raise money. → Hire 15 people. → Burn through cash chasing growth. → Pray your unit economics work out "eventually."
I watched so many founders go down that path. Bloated teams, endless meetings, and a product that moves slower every quarter because everyone is busy "managing" instead of building.
The 2026 version looks nothing like that.
I run multiple SaaS products with a tiny team. Most of the heavy lifting is handled by AI agents and automation. Revenue from day 1 (no freemium). And growth comes from content, not cold outreach and demo pipelines.
Here is what actually changed:
1. You do not need to raise money to build great software. Revenue-funded from day 1 means you own your margins and make decisions in minutes, not board meetings.
2. AI replaced the need for big teams. I have agents handling support, monitoring, content distribution, and internal ops. A solo founder or a team of 2-3 can now do what used to require 15 people.
3. Content replaced cold outreach. YouTube, email lists, and building in public generates more trust (and more qualified leads) than any SDR team ever could. Organic authority compounds. Sales calls do not.
The old playbook optimized for looking big. The new one optimizes for staying lean and moving fast.
If you are still hiring for roles that AI can handle and burning cash on growth hacks from 2019, you are playing a different game.
Running a SaaS business has so many moving parts, cause you're not in direct day-to-day contact with all of your users (e.g. like you would in an agency or as a consultant). So it's really easy to lose the bigger picture.
Now the agent tells me that churn went up last week - and it already traced it to a 1-hour outage with Meta that got users super annoyed.
Or it flags that support volume spiked 30% and connects it to a broken API from our last deployment.
I've never had a better "helicopter" view of my business.
Revenue is up. Customer satisfaction is up. And I spend way less time figuring things out and instead I focus on simply taking action.
If you're still wasting money with PostHog and Sentry and playing detective all day, you're still living 2022.
Here's another quick way to make your OpenClaw agents forget less.
Internally, OpenClaw keeps a few files for itself: - MEMORY .md (for long-term memory) - /memory/[date] .md (for day-to-day memory)
And finally, the sessions files (jsonl).
How it's SUPPOSED to work: The sessions files are used directly with ongoing chats. So OpenClaw will have context from the last few messages you did. The issue is, these sessions files get truncated as they grow, so it won't remember what you talked about a few days ago.
This is where the MEMORY .md and the /memory/[date] .md files become useful. OpenClaw will move important information to these files to store it as "long-term" memory.
The biggest issue I've found: OpenClaw does a TERRIBLE job at deciding what to store in long-term memory. So it always ends up forgetting important things unless I explicitly tell it to store them in memory.
Here's how I fixed it: I asked my agent to write a script that runs on an hourly CRON job. The script has one single function:
Go through the messy jsonl sessions files, clean them up (remove tools calls and other metadata), and write them to clean md files in a folder called "previous_conversations".
Then add a section to your AGENTS .md file instructing the agent to search through previous conversations when necessary.
⭐ Pro tip: If you have a RAG installed (highly recommended), have the CRON store the conversation chunks to the database as well, this will make it even faster and easier for the agent to search through.
After doing this, I ditched the standard /memory/[date] .md format altogether. Now I just have this + MEMORY .md for bigger, more highlighted information.
OpenClaw <> Notion. It's a phenomenal user experience!
📝 Wiki & notes. My OpenClaw team has direct access to my entire wiki & knowledge base (both personal and for my company).
It's obviously helpful for OpenClaw to have access to information, but the real hack is allowing it to groom it, maintain it, and keep it up to date.
I use OpenClaw 90% through voice, and whenever we discover something outdated, I just tell it to update it. I can do this on the fly, from my mobile, wherever I am.
Preventing my internal wiki from going stale used to be a big task, but is now super smooth and easy.
✅ Projects. My OpenClaw team uses Notion's project boards to create, delegate, and collaborate with each other, and with my human team.
I see some people creating their own "Mission Control" dashboards, and I have no idea why? Just use Notion for this, it's perfect.
💬 Editorial. This experience is just wonderful. I collaborate with my OpenClaw agent on writing great YouTube scripts, and we'll be in the same Notion doc together.
I can see his updates live as they happen, and he can see mine.
I can leave comments on specific blocks, and he can retrieve them and address them.
Just like a real-world collaboration.
What makes OpenClaw truly amazing is how you interface with it: Telegram (chat) and voice.
But you still not some UI for things, and Notion makes up 90% of what you'd need.
So if you're not using OpenClaw <> Notion already, give it a try.
What happens when founders ask AI: "Show me which humans on my payroll you can replace."
This is coming. And it won't even look evil on a dashboard.
Imagine this setup: → Every role is tracked in painful detail. → AI agents already handle 60–80% of the repetitive work. → The system sees salary, performance, error rates, CSAT, MRR impact.
Now the founder asks: "Show me the humans where your workload overlap is >70% and you outperform them. Rank them by cost."
The AI returns a list. Not opinions. Just math.
For many founders, this will be irresistible. Many boards will *demand* it.
But in practice, you just asked an AI to help you decide who to fire.
The people at the top of that list won't be "bad" employees.
They'll simply be: → Doing repeatable tasks. → Inside clean, measurable workflows. → With no real ownership beyond "tickets closed".
If your work can be fully expressed as a dashboard, at some point a model will outperform you on that dashboard.
If you're still an employee in your "safe and stable" job - I'd think long and hard about this.
Either become the 1/100 employee that AI can't replace. Or create your own job where you run the show.
Most founders don't realize it until it's way too late.
At $2K MRR, it feels harmless: → "We'll just use their managed vector DB." → "We'll just let them own auth + billing." → "We'll just proxy all AI calls through their API."
Fast-forward 18 months: - Your infra bill is brutal. - You can't negotiate. - Migrating is more expensive than staying trapped.
If you're building SaaS or AI products in 2026, you need to build with 3 core fundamentals in place:
1️⃣ BYO key as a default Let customers plug in their own OpenAI/Anthropic/etc. key.
→ They own spend. → You own product, not tokens. → They keep full control.
2️⃣ Self-hostable core Your moat is the product + UX/AX, not "you can only run this on our servers". Offer a self-host tier and price it so there's something to win for your users.
3️⃣ Replaceable building blocks Use tools you can rip out: → Postgres + pgvector over black-box AI DBs. → n8n over closed automation platforms. → Standard S3-compatible storage over proprietary blobs.
People fear AI will "replace" them. I think the real threat is infra that quietly owns them.
Own your product!
Or whoever owns it will eat your margins, limit your roadmap, and eventually put your business down.
Simon Høiberg
It's 2026, and Micro SaaS is still a massive opportunity!
Yes, use AI.
But use it the right way.
PRACTICAL > HYPE
✅ One problem, one promise, one price
✅ Validate with real users before code
✅ Automate the boring, review the critical
✅ Self-serve onboarding + clear docs
AVOID THE NOISE
❌ Feature soup to chase "everyone"
❌ Vanity metrics over paying customers
❌ Hype hacks without distribution
❌ "AI slop" that replaces human judgment
- Distribution BEFORE development.
- Design UI that sells the value.
- Protect your calendar like equity.
3-STEP MICRO SAAS LOOP
1️⃣ PROVE: Landing + email waitlist + LTD smoke test
2️⃣ BUILD: Tiny MVP with AI-assisted dev, human QA
3️⃣ SCALE: Onboarding polish, trust signals, content engine
SYSTEMS THAT BUY FREEDOM
- Weekly rotation: build → ops → growth → slack
- Automations: n8n for chores, Aidbase for support
- Pricing: monthly, yearly, pay-once for cashflow
1 day ago | [YT] | 152
View 0 replies
Simon Høiberg
In my 5+ years of building SaaS, the playbook has completely flipped.
Back in 2020, the default was:
→ Raise money.
→ Hire 15 people.
→ Burn through cash chasing growth.
→ Pray your unit economics work out "eventually."
I watched so many founders go down that path. Bloated teams, endless meetings, and a product that moves slower every quarter because everyone is busy "managing" instead of building.
The 2026 version looks nothing like that.
I run multiple SaaS products with a tiny team. Most of the heavy lifting is handled by AI agents and automation. Revenue from day 1 (no freemium). And growth comes from content, not cold outreach and demo pipelines.
Here is what actually changed:
1. You do not need to raise money to build great software.
Revenue-funded from day 1 means you own your margins and make decisions in minutes, not board meetings.
2. AI replaced the need for big teams.
I have agents handling support, monitoring, content distribution, and internal ops. A solo founder or a team of 2-3 can now do what used to require 15 people.
3. Content replaced cold outreach.
YouTube, email lists, and building in public generates more trust (and more qualified leads) than any SDR team ever could. Organic authority compounds. Sales calls do not.
The old playbook optimized for looking big.
The new one optimizes for staying lean and moving fast.
If you are still hiring for roles that AI can handle and burning cash on growth hacks from 2019, you are playing a different game.
3 days ago | [YT] | 168
View 2 replies
Simon Høiberg
AI models work a lot like evolution right now.
Some survive everything. Claude has been my go-to for coding for over a year - nothing has seriously challenged it.
Others cycle through fast. A new image model drops, dominates for 3 weeks, then gets replaced by the next one.
Survival of the fittest, but on a weekly schedule.
These are the ones currently running daily in my workflows 👇
5 days ago | [YT] | 130
View 0 replies
Simon Høiberg
In my 4 years of running SaaS, I've wasted so much time on dashboards...
Sentry for errors.
Stripe for churn.
PostHog for analytics.
Grafana for infra.
Bunch of dashboards. Bunch of logins. Zero connection between them.
The data is all there. But no one is putting the pieces together.
So I built an agent that does exactly that.
→ Inputs
Stripe webhooks. Uptime pings. n8n workflows. Server logs. Aidbase API.
→ Outputs
Telegram alerts. Daily digest. GitHub issues. Downtime escalation. Weekly report.
This has been a huge unlock for me!
Running a SaaS business has so many moving parts, cause you're not in direct day-to-day contact with all of your users (e.g. like you would in an agency or as a consultant). So it's really easy to lose the bigger picture.
Now the agent tells me that churn went up last week - and it already traced it to a 1-hour outage with Meta that got users super annoyed.
Or it flags that support volume spiked 30% and connects it to a broken API from our last deployment.
I've never had a better "helicopter" view of my business.
Revenue is up. Customer satisfaction is up. And I spend way less time figuring things out and instead I focus on simply taking action.
If you're still wasting money with PostHog and Sentry and playing detective all day, you're still living 2022.
1 week ago | [YT] | 184
View 5 replies
Simon Høiberg
Everyone loves to say their OpenClaw "works while they sleep".
But traditional automation did that too. It's not really that groundbreaking.
I think the real shift is *how* the work happens.
Old-school automation is a straight line:
Input → steps → output.
If-this-then-that. Left to right.
Agentic automation is different.
It's much closer to a real organization.
Think of OpenClaw as founder ops HQ:
→ Communication
Requests from Telegram, Slack, voice notes, inbox, support.
→ Knowledge
SOPs, notes, past conversations, databases.
→ Execution
Browser actions, internal tools, admin, agents.
→ Automation
Workflows, schedules, triggers, handoffs.
→ Distribution
Email, socials, alerts, content.
All connected to one orchestrator in the middle.
OpenClaw listens, decides who should act, what context to use, and what needs to happen next.
This is what makes it feel more dynamic, like a real "organism" and not just a mechanical system.
In these last 5 years, this is truly the closest we've gotten to a real "team" of AI agents.
1 week ago | [YT] | 206
View 0 replies
Simon Høiberg
You can absolutely run a 7-figure SaaS solo.
But not with "more hustle". You do it with the right stack.
Here's mine 👇
→ Infra (self-hosted)
Postgres + pgvector.
Docker + NodeJS.
Kubernetes + bare metal on Hetzner.
→ Build (AI-assisted dev)
Codex / GitHub for development.
OpenClaw + n8n for reliable agents.
CI/CD + tests + manual QA.
→ Marketing (always-on distribution)
Email list as the core asset.
X + YouTube for attention.
Meta ads to scale what already works.
That's the whole game: lean infra, AI-assisted build, and a marketing engine that runs even when you don't.
2 weeks ago | [YT] | 167
View 5 replies
Simon Høiberg
Here's another quick way to make your OpenClaw agents forget less.
Internally, OpenClaw keeps a few files for itself:
- MEMORY .md (for long-term memory)
- /memory/[date] .md (for day-to-day memory)
And finally, the sessions files (jsonl).
How it's SUPPOSED to work:
The sessions files are used directly with ongoing chats. So OpenClaw will have context from the last few messages you did. The issue is, these sessions files get truncated as they grow, so it won't remember what you talked about a few days ago.
This is where the MEMORY .md and the /memory/[date] .md files become useful. OpenClaw will move important information to these files to store it as "long-term" memory.
The biggest issue I've found:
OpenClaw does a TERRIBLE job at deciding what to store in long-term memory. So it always ends up forgetting important things unless I explicitly tell it to store them in memory.
Here's how I fixed it:
I asked my agent to write a script that runs on an hourly CRON job. The script has one single function:
Go through the messy jsonl sessions files, clean them up (remove tools calls and other metadata), and write them to clean md files in a folder called "previous_conversations".
Then add a section to your AGENTS .md file instructing the agent to search through previous conversations when necessary.
⭐ Pro tip: If you have a RAG installed (highly recommended), have the CRON store the conversation chunks to the database as well, this will make it even faster and easier for the agent to search through.
After doing this, I ditched the standard /memory/[date] .md format altogether. Now I just have this + MEMORY .md for bigger, more highlighted information.
Try it!
3 weeks ago | [YT] | 159
View 2 replies
Simon Høiberg
OpenClaw <> Notion.
It's a phenomenal user experience!
📝 Wiki & notes.
My OpenClaw team has direct access to my entire wiki & knowledge base (both personal and for my company).
It's obviously helpful for OpenClaw to have access to information, but the real hack is allowing it to groom it, maintain it, and keep it up to date.
I use OpenClaw 90% through voice, and whenever we discover something outdated, I just tell it to update it. I can do this on the fly, from my mobile, wherever I am.
Preventing my internal wiki from going stale used to be a big task, but is now super smooth and easy.
✅ Projects.
My OpenClaw team uses Notion's project boards to create, delegate, and collaborate with each other, and with my human team.
I see some people creating their own "Mission Control" dashboards, and I have no idea why? Just use Notion for this, it's perfect.
💬 Editorial.
This experience is just wonderful.
I collaborate with my OpenClaw agent on writing great YouTube scripts, and we'll be in the same Notion doc together.
I can see his updates live as they happen, and he can see mine.
I can leave comments on specific blocks, and he can retrieve them and address them.
Just like a real-world collaboration.
What makes OpenClaw truly amazing is how you interface with it: Telegram (chat) and voice.
But you still not some UI for things, and Notion makes up 90% of what you'd need.
So if you're not using OpenClaw <> Notion already, give it a try.
3 weeks ago | [YT] | 160
View 4 replies
Simon Høiberg
What happens when founders ask AI:
"Show me which humans on my payroll you can replace."
This is coming.
And it won't even look evil on a dashboard.
Imagine this setup:
→ Every role is tracked in painful detail.
→ AI agents already handle 60–80% of the repetitive work.
→ The system sees salary, performance, error rates, CSAT, MRR impact.
Now the founder asks:
"Show me the humans where your workload overlap is >70% and you outperform them.
Rank them by cost."
The AI returns a list.
Not opinions. Just math.
For many founders, this will be irresistible.
Many boards will *demand* it.
But in practice, you just asked an AI to help you decide who to fire.
The people at the top of that list won't be "bad" employees.
They'll simply be:
→ Doing repeatable tasks.
→ Inside clean, measurable workflows.
→ With no real ownership beyond "tickets closed".
If your work can be fully expressed as a dashboard, at some point a model will outperform you on that dashboard.
If you're still an employee in your "safe and stable" job - I'd think long and hard about this.
Either become the 1/100 employee that AI can't replace.
Or create your own job where you run the show.
3 weeks ago | [YT] | 94
View 7 replies
Simon Høiberg
Vendor lock-in is the new technical debt.
Most founders don't realize it until it's way too late.
At $2K MRR, it feels harmless:
→ "We'll just use their managed vector DB."
→ "We'll just let them own auth + billing."
→ "We'll just proxy all AI calls through their API."
Fast-forward 18 months:
- Your infra bill is brutal.
- You can't negotiate.
- Migrating is more expensive than staying trapped.
If you're building SaaS or AI products in 2026, you need to build with 3 core fundamentals in place:
1️⃣ BYO key as a default
Let customers plug in their own OpenAI/Anthropic/etc. key.
→ They own spend.
→ You own product, not tokens.
→ They keep full control.
2️⃣ Self-hostable core
Your moat is the product + UX/AX, not "you can only run this on our servers". Offer a self-host tier and price it so there's something to win for your users.
3️⃣ Replaceable building blocks
Use tools you can rip out:
→ Postgres + pgvector over black-box AI DBs.
→ n8n over closed automation platforms.
→ Standard S3-compatible storage over proprietary blobs.
People fear AI will "replace" them.
I think the real threat is infra that quietly owns them.
Own your product!
Or whoever owns it will eat your margins, limit your roadmap, and eventually put your business down.
4 weeks ago | [YT] | 141
View 2 replies
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