r/automation

I went through dozens of healthcare AI discussions, and the pattern isn’t what most people expect.

It’s not about “what AI can do.”

It’s about where it breaks in real clinical workflows.

Most of the demand looks obvious on the surface:

- patient communication

- appointment scheduling

- documentation / notes

- triage and intake

Nothing new.

What’s interesting is why these are still problems.

In most cases, it’s not an AI limitation.

It’s everything around it:

- fragmented communication channels

- EHR constraints (Epic / Cerner)

- inconsistent patient data

- compliance overhead (HIPAA, audit logs, etc.)

- multiple people touching the same workflow

On paper, these look like perfect automation use cases.

In reality, they sit across systems that don’t talk well together.

That’s where most AI projects stall.

Not at the model level —

but at the workflow and infrastructure layer.Feels like the real opportunity isn’t adding AI

it’s making it actually work inside how healthcare operates day-to-day.

Curious how others here see it

where have you seen AI actually break in real clinical settings?

A lot of early startups try to automate everything because it feels efficient.

But automating the wrong thing too early can create more work than it removes.

The hard part is usually not connecting tools. It’s knowing which bottleneck is painful enough, repeatable enough, and stable enough to automate.

For me, the best early automations are small and controlled: they remove one annoying manual step without hiding the parts the founder still needs to understand.

If you’re building a startup, what’s the first workflow you would automate?

we are hitting a wall right now where our team is running like 30 to 40 demos every single week and it feels impossible to scale because every new deal still depends on someone hopping on a call, its starting to feel like a huge time suck and im not sure how other teams get out of this without hurting conversion, we have looked at a few tools but its hard to tell what actually replaces demos vs just adds another layer on top, also struggling to figure out how to justify pricing when usage could fluctuate a lot, for anyone who has solved this what actually worked and did it reduce the number of live demos you had to run?

Recently I’ve been looking into automation, but at the beginning I honestly didn’t really know what people would actually be willing to pay for. So over the past few months, I scraped more than 10,000 Reddit comments and posts related to automation, mainly around these tools and categories: no-code integration tools (Make, Zapier, n8n, etc.), assistant-style products (Fathom, Fireflies, Airtap), and common AI tools like Claude. I wanted to figure out one thing: what automation scenarios do users really care about, and what are they actually willing to pay for? From what I found, the most commonly mentioned workplace scenarios were:

• email and customer support
• meeting notes
• sales lead management
• work document handling
• content creation
• personal scheduling assistants

In everyday life, the most wanted automation scenarios were more like:

• refund and savings tracking
• helping parents schedule or book medication
• finding a restaurant and making a reservation
• weekly grocery shopping
• job search and job applications

I also kept seeing some very specific pain points when I reviewed the data again and again:

• “There’s too much spam on LinkedIn, I want a tool to filter potential leads.”
• “The 24-hour window limit and template review process in WhatsApp Business are a nightmare.”
• “I have a lot of customer data, but I don’t have time to organize it manually.”
• “Updating CRM after meetings is my biggest time sink.”
• “I want to automatically turn YouTube videos into blog posts, tweets, and summaries.”
• “80% of our content time goes into formatting and adapting for different platforms.”

I’m not sure whether all of this is useful to you, but honestly, I feel like I’ve found some direction now. I actually want to focus more on the automation scenarios people most want in daily life. If it were you, which automation scenario would you be most interested in? Hope this is helpful.

We have outgrown basic forms and now need something with proper conditional logic, dynamic fields and workflow automation behind submissions.

Many can collect information but not many handle complex intake flows well once different responses need different actions.

What are you using for:

• lead qualification
• client onboarding
• internal requests
• support workflows

Hi I have been doing automation for quite some time need some guidance about the pricing strategies. If you have delivered live automations for several client hmu please need some help regarding the pricing strategy

Been thinking about this after a conversation with someone who just switched back to spreadsheets after six months of trying to automate their workflow with various AI tools. Not because the tools were bad because the gap between what was promised and what they actually got was demoralizing. There's a pattern I keep noticing: the demo is perfect, the use case is real, and then you spend two weeks integrating only to find that the 'autonomous' part requires a human checking every third output. Not a deal-breaker, but not what was sold. The tools that have stuck for me are ones that were honest about their constraints upfront. One example: I've been using Accio Work as a general business AI assistant to handle everything from operations to data workflows. It doesn't pretend to replace human judgment on complex edge cases; instead, it just flags them. That transparency made it easier to trust the outputs it does handle autonomously across my daily business tasks. The ones that burned me: tools that claimed to 'handle customer communication end to end' but couldn't parse a non standard return request without producing a reply that made no sense. Or niche sourcing tools that showed perfect results in demo data but struggled the moment you gave them real SKUs from a technical category. Curious what patterns others have seen. Is the over-promising a marketing problem, a product problem, or just a mismatch between what enterprise teams need vs what solo operators need?

Coming from GPT-5.5 Codex.

I've been making an app for roughly 25 hours now with AI, trying to vibe code everything. This obviously has its ups and downs, but so far it's a steady trajectory. As the project gets more complex, it often feels like the polishing stage is just further increasing in size, but I still feel like regardless I could finish this app without coding once myself - which for AI is super impressive, and is making me believe that the future of open source free apps is looking better and better.

I haven't tried Opus 4.7 yet, as I wanted to see what I could do with the base model. Claude told me Sonnet 4.6 was good enough for my code base, so I trusted in it. While it did quite a lot for the 1h 58m 42s session I got out of it, the execution was lacklustre.

It would implement what I said, but aesthetically it wouldn't look great. Even screwing up the alignment/evenness or forgetting basic UI elements I strictly told it to include. When reviewing what it worked on and trying to fix mistakes, it took upwards of 7 attempts to get what I wanted, and sometimes it would progressively make the problem worse.

Sonnet 4.6 might be good for the very bare bones getting a feature to exist, but getting it to look great, perform good, animate well, and integrate alongside other UI elements - it simply cannot do this well enough for me to recommend it whatsoever. Even with the nearly double amount of usage I got out of it compared to GPT-5.5, the consistency and polish of GPT5.5 was a lot better overall, getting the same tasks done in 2 prompts with greater presentation vs. 7+ prompts or being unable to fulfil my task with Sonnet 4.6.

Now this isn't to say GPT5.5 is without issues, as I've had to direct it a lot more than I'd like. It can't really do enough thinking for itself and will usually miss very obvious things I'd want, but with enough prompts and time it can get to where I want my app to be, while I can't say Sonnet 4.6 was good enough to get my project in a state I'd want to release to the public.

Stats:

I used 10% of my total 'All Models' weekly usage for Claude within 1h 58m 42s.

I used 16% of my weekly Codex usage (not all usage) for ChatGPT in a total of 1h 7m, but each execution of a task was done better and to a more finished state, and was needed to go over Sonnet 4.6's work for a more finished product overall.

Going to try Opus 4.7 with ClaudeCode next to see how it compares. Just wanted to let you know that Pro plan is not good enough for vibe coded development using Sonnet 4.6. My app is quite basic all things considered, so expect worse results making games.

Most agent demos I see end in a text answer, but a lot of my work ends in a deck. I’ve been testing a workflow where the agent starts with some context, figures out what still needs to be searched or researched, pulls the useful parts together, and then turns the result into a PowerPoint file.

The interesting part is not really AI makes slides, it’s whether the agent can decide what information is missing, what to ignore, and how to structure the output so it doesn’t feel like generic AI filler.

Still needs review, obviously. But it feels more useful than just getting a long summary back. Anyone building something similar?

Took me about four months. Mostly breaking things at 2am. Duct-taping different tools together, wondering if I was just making my life harder for no reason.

The goal was simple. I wanted our three-person agency to stop spending half the week on repetitive content tasks so we could actually focus on client strategy. Started with the writing side because that was eating the most hours. Tried a few generation tools, hated most of them, eventually found one that produced drafts decent enough to edit rather than rewrite from scratch. That alone saved us maybe six hours a week.

Then I got greedy and went after the whole pipeline. Website updates, chatbot responses, social scheduling. Each piece took a week of tinkering to get right. Some integrations worked on the first try. Others made me question my career choices.

The weird part is nobody on my team even noticed the transition happening. They just gradually had fewer boring tasks on their plate. One of them asked last month why Tuesdays feel so empty now.

Still breaks sometimes. But it breaks less.

I looking for a highly practical, systems-minded GoHighLevel specialist to help us streamline internal operations, client onboarding, lead follow-up, reporting, invoicing workflows, and other repetitive admin processes.

We want someone who can think in workflows, build clean automations, and improve how the business runs day-to-day with as little manual effort as possible. This role is ideal for someone who has real hands-on experience building automations inside GoHighLevel for agencies or service businesses.

What You’ll Be Doing:

You will help us design, build, and improve GoHighLevel automations across the business, including:

• Lead follow-up sequences.
• Client onboarding workflows.
• Automated reminders and task routing.
• Internal notifications for key events.
• Pipeline stage automations.
• Reporting and performance updates.
• Quote, invoice, and payment reminder workflows.
• Contract and onboarding document delivery.
• Missed call, no-show, and re-engagement automations.
• General admin process cleanup and systemization.

We want someone who:

• Has strong experience using GoHighLevel in a real business setting.
• Understands workflows, triggers, actions, conditions, pipeline stages, tags, forms, calendars, and automation logic.
• Can build clean, reliable systems without constant supervision.
• Can think practically about business operations, not just “set up a workflow.”
• Can improve existing processes and suggest better ways to structure them.
• Is detail-oriented and able to document what they build clearly.

Ideal Experience

• Prior experience working with agencies, lead generation businesses, or service-based businesses.
• Experience building automated lead nurture and client onboarding systems.
• Experience with reporting workflows and operational automations.
• Familiarity with document delivery, invoice flows, or payment reminders inside GoHighLevel.
• Ability to troubleshoot and refine workflows when something breaks or underperforms.
Nice to Have
• Experience creating SOPs and process documentation.
• Experience improving CRM structure and pipeline organisation.
• Experience working with offshore or remote teams.
• Strong understanding of conversion-focused follow-up systems.

Apply by sending your work, location, and availability. TIA!

I automate stuff for small teams. Thats my whole job.

But lately something been bugging me. Every workflow I build, every dataset I clean, every prompt chain I optimize, it all feeds into platforms that dont pay me or my clients a cent for the training data we generate. We're literally improving the tools that could replace us tomorrow morning. Not crypto, not stocks, this is where the actual wealth transfer is happening and most people in this sub are on the wrong side of it without even realizing.

I sat in a coffee shop last tuesday watching a founder demo his "AI-powered" product to investors. The whole thing ran on models trained by thousands of people who will never see a dollar from it. Dude raised his series A that afternoon.

The part that gets me is we all know this. Everyone in automation sees it happening in real time. We keep building anyway because the alternative is falling behind even faster.

Weird spot to be in honestly.

Prospecting → enrichment → CRM → sequence. No tab switching.

I expected the CRM sync to break, field mapping across tools is usually where everything falls apart. It handled it automatically. Didn't need to touch a CSV once.

What are others using MCP for in their day-to-day?

Came across a post where someone connected their bank to Claude through MCP and the agent was handling their invoicing and expenses automatically. Didnt dive too deep into it but the concept of having an AI agent manage your business finances caught my attention.

Im big on automating everything in my business but havent touched the financial side yet. Anyone here doing something like this or know what setup they were using. Would love to hear real experiences not just theory

I recently read about a Shopify founder who had an absolutely unhinged setup recently. They connected Midjourney to a print-on-demand pipeline so trending memes from Twitter/X automatically became t-shirt mockups within minutes. The system scraped viral posts, generated parody shirt concepts, created mockups, and pushed products directly to the store before most brands even noticed the meme existed. The crazy part is they said most of the sales came from being early, not from having amazing designs. Basically weaponized internet speed.

So curious from the experts here, what’s the most unhinged AI automation you've seen that somehow works?

Started automating workflows for a small team last quarter. The AI part was surprisingly easy to set up.

Then the invoices hit. I was running a few document processing flows and some customer email triage stuff, nothing crazy, maybe a dozen active automations. Looked at the bill after about three weeks and just sat there for a minute. I had budgeted for the tooling costs, the integrations, the time spent building it all out. Never once thought about what the actual token usage would look like at scale. The per-call cost seems tiny until you realize how many calls even a simple workflow makes in a day.

So I started asking around. Talked to a couple people running similar setups, one guy at a meetup last tuesday who manages automations for a mid-size logistics company. Nobody has a real strategy for this. Everyone is just kind of winging it, swapping models, caching where they can, hoping the prices drop.

The wild part is how fast it went from "this is saving us so much time" to "wait, is this actually cheaper than just hiring someone."

Curious what others here are doing about it.

Most open source AI assistants either don't support scheduled task execution at all, or they require cron setup and shell scripting to make it work. Curious if anything in this space can handle scheduled automation for someone who doesn't write code.

The biggest lie people tell about AI automation:

"Set it and forget it."

I Built so many automations for small businesses.

The ones that actually stuck required checkin.

Content updates. Small fixes when something broke.

AI doesn't run itself. It runs on the quality of what you feed it.

Update your docs, it gets smarter.

Ignore it, it gets stale.

The businesses winning with AI aren't the ones who automated everything overnight.

They're the ones who picked one problem, built one simple solution, and actually maintained it.

That's it.

👇 What's the biggest misconception you've seen about AI automation?

Hey folks,

Trying to understand how is automation different from what agent does? Basically what’s the layer and demarcation between AI, agent and automation ? If an agent proactively sends me a daily digest - is that automation ?

And where else is the opportunity for AI to come in the automation lifecycle and enhance it? Also, should it help just automation makers of today or serve larger segment of automation consumers too?