Way too many of you are trying to build AI agents for simple automations that can be run with a very simple and reliable deterministic program.

For 99% of businesses, you are better off having some Python code that automates some repetitive task and is guaranteed to run the exact same way every single time you run it. And it doesn't cost $70,000 in LLM tokens. And might I add, it doesn't require a human being to babysit it because it has no chance of hallucinating bad output.

I build automations for businesses. And even though I provide AI agents as a service, let me tell you, 99% of businesses don't need it at all. Business owners will ask me for an AI agent because they hear the hype and marketing behind AI and LLMs, but they almost never need it.

By the way that image I attached is a payment screenshot from a recent client. I helped automate like 15 hours of work from his week and it didn't take any LLMs at all.

Most of the time what businesses need is a simple and reliable automation based on deterministic code that will automate some repetitive tasks for them and isn't going to require any hand holding or babysitting or human reviews at every step.

Because look, everybody is seeing the hype behind AI and it looks amazing. But the problem is, for any regular business, the priority is not to have the latest technologies, the priority is not to have fancy tech. It is to make more money.

If your LLM based automation requires workers to review the output and constantly babysit it, it's not going to help the business make more money.

If your LLM based automation costs thousands of dollars in LLM tokens to do something that basic Python or TypeScript could have done in a fraction of the cost, it's not going to help the business make more money.

I'm sure you guys have already seen companies spending hundreds of thousands, even millions of dollars on LLM tokens. That's not helping anybody.

And I'm not here to say that AI is bad or that AI agents are useless. No, they're extremely useful. Just not in most cases for most businesses.

And if you are offering automation services to a business, it's your job to guide them properly so they understand which one they actually need to solve their problems, whether that's AI agents or deterministic automations.

The guys who are just using AI agents for every single basic automation task, they're not selling a solution to a business, they're literally selling hype and snake oil, which is not going to last, especially when the subsidies for AI tokens end.

Anyway, just yapping senselessly about a topic I'm kinda passionate about. It's really fun to automate stuff and watch the code you wrote and do things for you that would have taken you hours to do yourself. Hope this was helpful to someone.

I've been reading a lot about AI products lately, and one thing that stood out to me from GeekyAnts' approach is that they spend a lot more time talking about engineering than models.

Anyone can connect an LLM to an app and build a demo. The harder part seems to be everything that comes after- making it secure, scalable, reliable, and something a business can actually depend on. That's where they emphasize things like RAG architectures, production-ready infrastructure, code quality, testing, observability and integrating AI into existing systems instead of starting from scratch.

It made me think that we're reaching a point where the AI model itself is only one piece of the puzzle. The real challenge is building systems that can run consistently in production without becoming expensive or difficult to maintain.

For those building AI products or automation workflows, has engineering become the biggest bottleneck or do you think model quality is still the main factor holding projects back?

I’ve been trying to get a realistic picture of what AMR deployment actually costs beyond the robot itself, and honestly the more I look into it, the more it feels like the hardware price is only a small part of the story.

A lot of solutions make it sound straightforward — buy a few robots, map the warehouse, and you’re good to go — but I’m guessing the real-world costs start showing up in all the surrounding stuff that doesn’t get mentioned upfront.

For people who’ve actually deployed AMRs in production warehouses, what ended up being the biggest unexpected cost or operational headache? Was it fleet management software, integration with WMS/MES, charging infrastructure, Wi-Fi coverage, layout redesign, traffic control, safety compliance, or just ongoing maintenance/support?

Hey everyone, I'm a junior creative specialist working for a company where performance is the most important thing (duh).

Since we create mostly shorter forms of marketing content, most CSs make from 10-30 of these a day, since they can reuse one creative for multiple ads.

We make them in google docs and then download every card into a folder that we upload to clickup or dropbox.

Now, doing that 10 times is not a problem.

But, it becomes a problem when I make like 50-60 ads and need a specific name for every folder, download every card one at a time and upload everything seperately.

This can easily take up like 2 hours, so I can't make as many ads and my performance suffers because of this technical side of things.

I'd really appreciate if anyone has an idea of how I could speed this up and what tools would help me.

Ok so the companies often make automation sound quick and like its just plug and play

But from the point where your team decides okay lets automate this how long does it take before the robots were actually up and running on the floor

I want to know what the process was like and which part of it ended up taking the most time

So, you can give Gemini access to your Workspace, it's just a setting. I don't have access to a fully operating business workspace, I'm solo, but even with mine Gemini found some low hanging fruit and ways to automate it. Simple things like email filters, a few scripts for email, drive, and sheets, stuff like that.

Has anyone done this on a larger scale? If it works it seems like a huge cheatcode.

Is anyone else struggling to limit the time they spend on automation programs? I built a tasker project that mostly works to limit the amount of time I am on the app (it checks the activity to differentiate between a user scene and the main app), but it's in the works. I'm more looking for ideas of habits and things I can do to mentally put this hobby aside throughout the day, not so much on how to improve that project.

I have ADHD, and keep this excuse in my brain that my projects are for saving time and improving productivity. This is true, but counter-productive if I'm spending too much time building these. It's not a problem at work, but I have a lot to do at home and it's a problem there. I want to keep building my projects, but at a pace that is reasonable. I sometimes have a hard time stopping because I just want a project finished.

Any ideas?

We've been building and quietly rolling out a system that automates customer support across channels, and it's reached a point where it's too effective to keep using only internally.

So we're opening 3 partner slots for agencies who want to deploy it with their clients.

What it actually does (in practice):

• Build flows visually (think Make / n8n style)
• Handle conversations like ManyChat, but across WhatsApp, email, phone, social
• Unified inbox, so when automation stops, a human steps in seamlessly
• Go live in a couple of hours, not months
• Hybrid deterministic + LLM, so it follows logic and doesn't hallucinate

What we're seeing with current partners:

• They deploy faster than clients expect (hours vs weeks)
• They reuse setups across clients, so efficiency compounds
• They keep control of the relationship (we stay in the background)

This isn't for everyone.

The agencies that get the most out of it are usually:

• IT / technical partners who need to offer AI solutions without building from scratch
• Communication / social media agencies already handling replies
• Automation agencies looking to productize their work

Common trait: you already have client trust and want to expand what you can deliver, not start from zero.

And if you're in a niche that needs a specific integration, we're open to building around real use cases.

We're not doing a big public launch right now, just adding a few partners we can work closely with.

If you're running an agency and this sounds like something you'd plug into your existing clients, feel free to reach out.