ai business automationAI Generated
5 AI Automations Running My Business Right Now
ai business automation
Sebastjan Mislej2026-02-167 min read
>Total investment
The upfront investment was significant. Building and debugging these systems took about three months of evenings and weekends. But the compounding effect is real. Every week the systems get a bit better as I refine the prompts and rules.
If you are thinking about building AI automations for your business, start with the boring stuff. Email triage, not creative writing. Calendar summaries, not strategy. Get the simple wins first. The complex stuff gets easier once you understand how these systems fail.
Pro tip: Do not automate something you have not done manually first. I wrote hundreds of blog posts before I automated blog writing. I triaged thousands of emails before I automated email triage. You need to know what "good" looks like before you can teach an AI to produce it.
FAQ
How technical do I need to be to build these?
You need basic programming skills. I use Node.js scripts, shell commands, and API calls. No machine learning expertise required. The AI models handle the intelligence. You handle the plumbing.
Which AI models do you use?
Mostly Claude (Anthropic) for writing and reasoning tasks. Different model sizes for different jobs. Complex writing gets the larger model. Simple classification gets the smaller, cheaper one.
Do these automations ever break?
Yes. Weekly. An API changes, a rate limit gets hit, an edge case appears. I built monitoring that alerts me when something fails. Maintenance is part of the deal.
Can I buy these as a product?
Not yet. But I am working on a managed hosting service for AI assistants. If you are interested, check back on this blog.
How do you prevent AI hallucinations in published content?
Every factual claim gets verified against a primary source. The editor agent checks for unsupported statistics. And I personally review every piece before it goes live. Three layers of verification.
What is the hardest part of maintaining these systems?
Prompt drift. The AI models get updated, behavior shifts slightly, and suddenly your carefully tuned prompts produce different output. I version-control everything and test after model updates. It is unglamorous work, but it keeps things running.
3
Specificity over generality
Each automation does one thing well. I did not build a "general AI assistant." I built five specific systems with clear inputs, clear outputs, and clear success criteria.
The real cost and ROI
I spend roughly $30/day on AI API calls across all automations. That is about $900/month. In return, I estimate I save 4-5 hours per day of manual work. For a solo entrepreneur running multiple businesses, those hours are worth far more than $900.
$30/day
API cost
4-5 hrs
Time saved daily
$900/mo
Total investment
The upfront investment was significant. Building and debugging these systems took about three months of evenings and weekends. But the compounding effect is real. Every week the systems get a bit better as I refine the prompts and rules.
If you are thinking about building AI automations for your business, start with the boring stuff. Email triage, not creative writing. Calendar summaries, not strategy. Get the simple wins first. The complex stuff gets easier once you understand how these systems fail.
Pro tip: Do not automate something you have not done manually first. I wrote hundreds of blog posts before I automated blog writing. I triaged thousands of emails before I automated email triage. You need to know what "good" looks like before you can teach an AI to produce it.
FAQ
How technical do I need to be to build these?
You need basic programming skills. I use Node.js scripts, shell commands, and API calls. No machine learning expertise required. The AI models handle the intelligence. You handle the plumbing.
Which AI models do you use?
Mostly Claude (Anthropic) for writing and reasoning tasks. Different model sizes for different jobs. Complex writing gets the larger model. Simple classification gets the smaller, cheaper one.
Do these automations ever break?
Yes. Weekly. An API changes, a rate limit gets hit, an edge case appears. I built monitoring that alerts me when something fails. Maintenance is part of the deal.
Can I buy these as a product?
Not yet. But I am working on a managed hosting service for AI assistants. If you are interested, check back on this blog.
How do you prevent AI hallucinations in published content?
Every factual claim gets verified against a primary source. The editor agent checks for unsupported statistics. And I personally review every piece before it goes live. Three layers of verification.
What is the hardest part of maintaining these systems?
Prompt drift. The AI models get updated, behavior shifts slightly, and suddenly your carefully tuned prompts produce different output. I version-control everything and test after model updates. It is unglamorous work, but it keeps things running.
3
Specificity over generality
Each automation does one thing well. I did not build a "general AI assistant." I built five specific systems with clear inputs, clear outputs, and clear success criteria.
The real cost and ROI
I spend roughly $30/day on AI API calls across all automations. That is about $900/month. In return, I estimate I save 4-5 hours per day of manual work. For a solo entrepreneur running multiple businesses, those hours are worth far more than $900.
$30/day
API cost
4-5 hrs
Time saved daily
$900/mo
Total investment
The upfront investment was significant. Building and debugging these systems took about three months of evenings and weekends. But the compounding effect is real. Every week the systems get a bit better as I refine the prompts and rules.
If you are thinking about building AI automations for your business, start with the boring stuff. Email triage, not creative writing. Calendar summaries, not strategy. Get the simple wins first. The complex stuff gets easier once you understand how these systems fail.
Pro tip: Do not automate something you have not done manually first. I wrote hundreds of blog posts before I automated blog writing. I triaged thousands of emails before I automated email triage. You need to know what "good" looks like before you can teach an AI to produce it.
FAQ
How technical do I need to be to build these?
You need basic programming skills. I use Node.js scripts, shell commands, and API calls. No machine learning expertise required. The AI models handle the intelligence. You handle the plumbing.
Which AI models do you use?
Mostly Claude (Anthropic) for writing and reasoning tasks. Different model sizes for different jobs. Complex writing gets the larger model. Simple classification gets the smaller, cheaper one.
Do these automations ever break?
Yes. Weekly. An API changes, a rate limit gets hit, an edge case appears. I built monitoring that alerts me when something fails. Maintenance is part of the deal.
Can I buy these as a product?
Not yet. But I am working on a managed hosting service for AI assistants. If you are interested, check back on this blog.
How do you prevent AI hallucinations in published content?
Every factual claim gets verified against a primary source. The editor agent checks for unsupported statistics. And I personally review every piece before it goes live. Three layers of verification.
What is the hardest part of maintaining these systems?
Prompt drift. The AI models get updated, behavior shifts slightly, and suddenly your carefully tuned prompts produce different output. I version-control everything and test after model updates. It is unglamorous work, but it keeps things running.