r/AiAutomations

▲ 14 r/AiAutomations+1 crossposts

linkedin automation

I need to automate 40 accounts for professors (with proper authorization). The goal is 6-7 unique total made up of: posts about new articles they wrote and about conferences they attended. I need to recreate their authentic offline networks online based on publicly available data such as their cvs and lists of their co-authors, people they have appeared together with on panels etc…… Then I need while somehow having captured their authentic voice, write several comments per week, give several like per week, maybe a reshare a couple of times, literally bare minimum for each account, but turning a person who previously had no presence into a person with regular but not high volume. Each account needs its own static ip, and a way of reliably logging back in. Each account needs its own monitor to determine in advance what it will respond to and engage with. Each of the 40 needs to act on its own in terms of time of day that it posts, and honestly everything else that the particular account does.

thoughts?

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u/DistributionSoggy678 — 5 days ago
▲ 21 r/AiAutomations+7 crossposts

👋 Hey Everyone,

Two weeks back I built a support inbox router for my friend Mike's small company – Gmail trigger, AI classifies each email into Billing / Technical / Sales / Other, scores priority, drops a clean summary into the matching Slack channel. Sarah on his finance team was tired of getting CC'd on bug reports, so the routing actually had to work.

After my last stress test post (the one where I broke our extraction with degraded invoices), a bunch of people asked the obvious follow-up: yeah but how do you stress test a classification workflow? Different problem. There's no "ground truth amount" to compare against – the model is making a judgment call.

So I sat down and wrote 50 deliberately awful emails. The kind of stuff that would actually land in Mike's support inbox on a bad week. Here's what I learned.

If you want to follow along or fork this, the template is published on n8n: https://n8n.io/workflows/15366-route-and-prioritize-support-emails-to-slack-channels-with-easybits/

The categories I tested

I grouped them into five buckets, each designed to attack a different assumption the workflow makes:

1. Mixed-language emails – German body, English technical term ("authentication error", "timeout", "404"). Tests whether the language detection holds up when it shouldn't.

2. Tone vs. urgency mismatches – polite rage ("just wanted to flag the export has been broken for three days, no rush! 🙂"), and the inverse: aggressive-sounding emails about trivial issues. Tests whether priority leans too hard on sentiment.

3. Category overlap (requested from community) – billing questions that are actually bugs ("my invoice shows €0 but I was charged €49"), sales leads disguised as technical questions ("does your platform support SAML SSO? we're 200 people evaluating tools"), cancellation emails that are really retention conversations.

4. Adversarial structure – all-caps emails, emails with no subject line, emails that are 90% forwarded thread and 10% actual question, emojis-as-punctuation, single-sentence vague pings ("hey can you help?").

5. The not-actually-support stuff – vendor pitches dressed up as support requests, recruiter spam, customers replying "thanks!" to closed tickets, automated bounce notifications.

What broke (and how)

Three patterns showed up across the failures, and they're more interesting than the individual misses:

Failure pattern 1: Politeness as a priority sedative

The sentiment-based priority scoring weighted tone heavily. Someone writing "no rush, totally understand" about a three-day outage scored Normal. Someone yelling in all caps about a typo on a pricing page scored Urgent. The model was reading the customer's mood, not the situation's severity.

The fix wasn't a smarter prompt. It was admitting that some signals shouldn't go through the model at all. Words like "broken," "down," "can't login," "charged twice," "still waiting" now force Urgent regardless of how nicely they're phrased.

Failure pattern 2: Single-token language confusion

A German email with one English error message ("Hallo, ich bekomme einen 'authentication error' beim Login...") got routed to Sales. One token of English in a 60-word German email was enough to throw the classifier sideways. Made no sense logically, made total sense if you think about how these models actually work.

The fix here was prompt-level – explicit instruction that the language of the email is determined by the dominant language, not isolated technical terms. Not perfect, but cut the misroutes substantially in re-tests.

Failure pattern 3: Category confidence vs. category correctness

This was the most interesting one. The model was confidently wrong on overlap cases – billing-questions-that-are-bugs, sales-disguised-as-support. High confidence score, wrong category. Confidence was measuring "do I know what category this fits" not "does this email fit cleanly into one category."

This is the case where threshold-based fallback alone doesn't save you, because the model isn't uncertain – it's certain about the wrong answer. The honest fix was to stop treating Billing/Technical/Sales as exclusive – letting the model flag a secondary category for overlap cases, with the secondary channel getting a quiet FYI cross-post.

I haven't pushed this updated prompt to the repo yet. Drop a comment if you want it – happy to share.

What I'd tell anyone building something similar

Three takeaways, none of them about better prompts:

  • Stress test the category boundaries, not just the categories. Easy emails are easy. The interesting failures live where two categories overlap, and that's where you should spend your test time.
  • Don't trust confidence scores to catch confidently-wrong outputs. A high score means the model is sure, not that it's right. Build for the case where it's sure and wrong, not just unsure.
  • Some things shouldn't go through the model. Hard rules layered on top of AI classification aren't a hack – they're how you make the system trustworthy. The phrase "I want to cancel" should never need an LLM to flag for human attention.

The "Other" channel – the catch-all for low confidence – turned into the most valuable channel in the whole setup. It's where every interesting edge case lands, and where Mike actually learns something about his customers.

If you want to try it

Happy to dig into the test cases, the prompt structure, or why I think category overlap is the underrated problem in support automation. And again – comment if you want the updated overlap prompt when it's ready.

Best,
Felix

u/easybits_ai — 6 days ago
▲ 2 r/AiAutomations+1 crossposts

Need some help building an AI Automation system for inbound and outbound real estate leads

I use a system called X Leads and Poperty Leads which both don’t have an API to work with. All my inbound and outbound leads live in those 2 CRMs.

I’ve tried integrating with Apify but failed miserably due to not knowing how to implement nonstandard and custom integration requirements.

I’m trying to find a way to pull data from the CRM and notes (Property Value, Repairs, Comparables) and shoot a text message to the home owner with the offer and based on sentiment (interested or not)

Give me a signal notification to call them myself if they are interested. The cooler part would be a Voice integration that takes my voice and clones it with ElevenLabs and then handles phone call end 2 end but I think we are far off from that.

Some leads have gone cold at 30-60 days and I can’t find the time to call them up so an automated SMS follow up trigger would be super helpful.

Want to keep it simple and clean. No API CRM to SMS with Twilio. Maybe VAPI or Bland for Voice calling. Willing to hire someone who has done something similar or exactly the same.

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u/Obvious_Lime — 7 days ago
▲ 2 r/AiAutomations+1 crossposts

Building an AI-for-education product and struggling to find senior AI engineers to guide or work with me. Where do you actually find them?

I'm building an AI-powered learning platform for school students (classes 6-12). I have about 2 years of hands-on experience integrating LLMs into the product, but to take it to the next level I need input from people who've built agents, RAG pipelines, and large-scale AI systems in production.

Over the last 1-2 months I've reached out to 50-60 senior AI engineers on LinkedIn. A few replied and a couple said they'd help, but nothing stuck and most went quiet. I'm not blaming anyone. I know senior folks are busy and a cold message from a stranger is a hard sell.

So I'd love some guidance on:

  1. Where do experienced AI engineers actually hang out or pick up projects (communities, Discords, forums, platforms)?
  2. Is it better to start with a paid contractor/consultant, a part-time advisor, or go straight for a co-founder-type person?
  3. How do you approach senior people so they take it seriously? What makes you reply to a cold message?
  4. Has anyone been on either side of this (founder finding a senior AI person, or the engineer being approached)? What worked?

I'm happy to pay for time on a trial or consulting basis, and open to equity conversations for the right person. Any advice or pointers are appreciated, thanks!

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u/Alert-Sprinkles-2213 — 5 days ago
▲ 433 r/AiAutomations+1 crossposts

I made $75K selling AI automations to clients. Here's what I'd change if I started over.

I wasn't planning to build an AI automation business. I was freelancing, doing GTM work for SaaS founders, and one of them asked if I could "set up some AI thing" to handle their lead follow-ups. They were losing prospects because their two-person sales team couldn't reply fast enough.

I quoted $2,500. Built it over a weekend using Zapier and GPT. Took their average first-response time from 14 hours to under 3 minutes. The client told a friend. The friend called me.

Before I get into the lessons, quick note: if you want your own automations built, I take on a couple of new clients a month. There's a link in my bio to book a call.

That was roughly a year ago. I've done $75K in revenue since then, mostly from small and mid-size businesses that knew AI could help them but had no idea where to start. I want to share what actually happened, because most "I made X with AI" posts skip the parts where it got ugly.

My first five clients all came from referrals. I didn't have a website, a portfolio, or a pricing page. Just a WhatsApp message that said something like "the guy who fixed our lead flow." I charged between $1,500 and $3,000 per project. Felt like a lot at the time.

It wasn't. I was building custom workflows, integrating three or four tools, handling revisions, jumping on calls, and basically being on retainer for free because I hadn't scoped the engagement properly. One project I quoted at $2,000 ate six weeks of back and forth. That client is the reason I now send a scope document before I touch anything.

The first real lesson hit around client number seven. A dentist's office wanted me to automate appointment reminders and no-show follow-ups. Straightforward. But then they asked me to also build a chatbot for their website, connect it to their booking system, and "maybe do something with reviews." The project went from a clean $3,000 build to a mess I was still patching two months later.

I stopped saying yes to everything after that.

Pricing is where most people in this space leave cash on the table. I know because I did it for months.

My early projects were flat-fee. $2,500 to build, hand over, done. The problem is that a lead-routing automation I built in 12 hours was worth the same to me as one I built in 40. The client paying $2,500 for the 12-hour build was getting a steal. The one paying $2,500 for the 40-hour build was getting my full attention and I was getting minimum wage.

What fixed it: I started charging a build fee plus a monthly retainer. Build fee covers the setup, usually $3,000 to $7,000 depending on complexity. Retainer covers monitoring, tweaks, and the fact that these systems break quietly. APIs update. Rate limits change. A form field gets renamed and suddenly nothing flows. $500 to $1,500 a month, depending on how many automations the client runs. That retainer revenue is what turned project work into a business with actual recurring income.

Right now about 60% of my revenue comes from retainers. The other 40% is new builds. The retainer clients barely contact me most months, but they pay because the one time something breaks at 2am and leads stop flowing, I'm the person who fixes it before they wake up. That peace of mind is worth more to them than the dollar amount on the invoice.

The $75K breaks down roughly like this: around 18 clients total, average project size just under $4,200, and eight of those clients are on monthly retainers. Three of the retainer clients have been with me for over eight months. Two of them have referred me to other businesses, which brought in another $11K I didn't have to sell for.

Some things I'd tell anyone starting this now.

Don't sell AI. Sell the outcome. Not once has a client asked me what model I'm using or whether I'm running n8n or Make or Zapier. They want to know how fast their leads get a reply, how many hours their team saves per week, and whether their follow-up rate goes up. If I pitched "I'll build you a GPT-powered multi-step automation workflow," their eyes would glaze over. "Your leads will get a personalized reply within 90 seconds, 24 hours a day" is what closes.

Pick boring businesses. My best clients aren't tech companies. They're dental offices, HVAC companies, real estate teams, insurance brokers. Businesses drowning in manual follow-ups and appointment scheduling with zero internal tech talent. They don't comparison shop. They don't ask for a technical proposal with an architecture diagram. They just want the problem gone.

Scope everything in writing before you start. I said this already but it matters enough to repeat. The project that nearly burned me out could have been avoided with a one-page document listing exactly what I'd build, what I wouldn't build, and what counts as a revision versus a new project. I use a dead simple template now. Hasn't failed me yet.

Don't build from scratch when a platform handles 80% of it. My early instinct was to code everything custom because it felt more "real." Waste of time. Most client problems are solved with Zapier or Make connected to their CRM, plus a GPT layer for the parts that need language. Save custom builds for the rare client whose problem actually demands it. The other 90% want it done Tuesday, not done perfectly.

Charge for maintenance. This is where the business gets stable. A one-time build makes you a freelancer. A build plus retainer makes you a partner they budget for every month. Once a client is on retainer, the switching cost is high enough that they stay. Not because you're trapping them, but because replacing the person who knows where all the wires connect is more painful than the monthly fee.

I'm not pretending $75K is life-changing money. Spread across a year, after tool costs and taxes, it's a solid income but not a windfall. What changed things for me is that the pipeline is warmer now than when I started, retainer revenue covers my base expenses before I sell anything new, and the last three clients came inbound without me spending a dollar on marketing.

If you're selling AI automations or thinking about starting, I'm curious what's working for you. Especially around pricing. I still feel like I'm figuring that part out.

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u/Warm-Reaction-456 — 10 days ago
▲ 5 r/AiAutomations+1 crossposts

Looking for Remote AI Training Jobs Like Outlier (Aether Tasks, Coding, AI Evaluation)

​

Hi everyone!

I'm looking for legitimate remote AI training opportunities similar to Outlier AI, especially projects involving AI response evaluation, data annotation, and tasks like Aether.

I'm also interested in simple HTML, CSS, and JavaScript tasks, such as reviewing AI-generated code, testing outputs, or fixing basic coding issues.

I'm looking for opportunities that:

Pay for completed tasks or hours worked.

Accept applicants from different countries, including Algeria.

Don't require an upfront payment to access work.

Allow me to work using my own account and identity.

If you've worked on similar platforms or know of companies currently hiring, I'd really appreciate your recommendations and experiences.

Thanks!

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u/User-Usual-7243 — 6 days ago

I’m 23yr running a call centre doing $85k a month, mostly automated using Ai.

Hi everyone, I thought I would do another ama since the first one I did got a lot of questions.

Since my first post around 6 months ago, I’ve managed to automate 90% of my day to day job, and the business has grown massively because of it entirely using Ai.

Since it’s been a few months, the platform I made using Ai costs $3 per day on average to run, and it has systemised everything. Better lists, better calls, better outcomes.

My system is 127,000+ lines of unique code that I made with Claude, ChatGPT, and Lovabledev. I have no background whatsoever in coding, and have managed to pull this off officially with real statistics to back that claim. I’ve spent roughly $8,000+ in credits in the last 4 months in build costs, a one off now it’s finished.

Last 3 weeks, I’ve tried work as little as possible to see what brakes first, and I’m now writing this post in Dubai on the palm, for a celebration holiday. The business has actually grown for the first time ever without me.

We are projected to hit $100k revenue next month with 8 full time staff in Leeds, UK.

We don’t spend a penny on marketing, and generate all new business directly from cold calling.

AMA!

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u/TheRealVenonymous — 11 days ago
▲ 6 r/AiAutomations+1 crossposts

want to connect with ppl in ai automation

i will be honest here i want someone who is good at ai automation im thinking to start a agency for that i want someone who is at ai automation i will split the project revenue with them . anyone intrested dm me

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u/Mental-Chipmunk-4398 — 9 days ago
▲ 4 r/AiAutomations+1 crossposts

Need advice on AI automation

Hello everyone, it’s been three months since I stopped AI automation. I initially started with Make and now I’d like to resume using N8n. My problem has always been finding a niche that’s still viable and offers a problem to solve with my automations. For example, whenever I have a clue about a niche I discover a SaaS already solves the problem. I’m looking for people with experience in the automation business who could advise or guide me. I’ve been stuck for a week now and I’m really motivated! Thanks 🙏🏼

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u/ku4tro_stone — 9 days ago
▲ 7 r/AiAutomations+1 crossposts

I build the automations but I'm bad at finding clients. Looking for someone who's the opposite

Hello everyone,
I build automations: n8n, Make, Zapier, and AI agents on the OpenAI and Claude APIs. I'm good at the building and bad at sales, which so far means solid workflows and no clients.

So I'm looking for someone who's the opposite. Maybe you're good at finding and closing small business clients but don't build. Maybe you run an agency and need someone reliable for the builds. Maybe you already have clients asking for automation and nobody to hand it to.

What I bring: I build it, test it, document it and look after it afterwards. I'm in Romania, 7 hours ahead of New York, so work gets done while US clients sleep.

Open to a revenue share or a split per project, whatever is fair once we talk. If this sounds like you, comment or DM me and tell me how you find clients now.

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u/Traditional-Wind4843 — 12 days ago
▲ 1 r/AiAutomations+1 crossposts

One Sentence In -> A Working Business Out

If you need a custom built website, company email, and full go to market stack to go from an idea to a live business in one hour, I have a solution for you...

you can use the free AI business builder tool by Leapd, describe your idea in plain English, and watch how it turns it to a live business.

I built this after watching my friend wasting 3 months and over $10k and grinding 24/7 to be able to test a basic idea which he had to shut down afterwards.

A traditional way for building nd testing a business idea was to do these:

1- find an agency and pay them $10k -> after 3-6 month have an mvp

2- fina another agency to run email campaigns or marketing -> pay them $2k -$5k per month

3- after 8 month see if any customer would pay for it - would anyone care!!!

With leapd the flow is simple:

1- start free, describe your idea -> get deep market research, custom built websites, and a company email in 10 minutes

2- set up email campaigns, meta ads, linkedIn outreach, and GEO/SEO in 5 minutes

3- see how customer respond to your business, improve, scale what works -> grow!

all done from idea to putting your business in front of customers in less than one hour.

Leapd free business builder is very useful if you are looking to go from an idea to a live business and start testing different marketing channels on autopilot and in few hours.

start here: https://www.leapd.ai/tools/free-business-builder

If you don't know what to build and looking for proven business ideas with revenue, deep analysis and more -> leapd recently launched built radar, a database of 5,000+ trending business with revenue, can you build it verdict, moat analysis and more. Find what you like and build it with Leapd:

https://buildradar.leapd.ai

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u/leapd-ai — 10 days ago
▲ 2 r/AiAutomations+1 crossposts

Starting a solo AI automation agency with reusable templates — best stack + client account setup?

I’m planning to start a one-person AI automation agency and want to avoid rebuilding everything from scratch for every client.

My idea is to create reusable automation templates for common business problems, then customise them depending on the industry/client.
Examples:

Lead response + follow-up
Missed-call recovery
Review/reputation automation
Appointment booking/reminders
Quote follow-up
Customer reactivation
Payment/invoice follow-up
Customer support automation

The goal is for maybe 70–80% of the system to stay reusable, with the remaining 20–30% customised around their CRM, calendar, messaging, business rules, accounting software, etc.

I’d then charge a standard setup + monthly
management fee, while deeper integrations/custom workflows would be a premium add-on/project.
A few questions for people actually running AI automation agencies:

What stack would you recommend?
HighLevel, Make, n8n, Zapier, or a combination?
Would you use HighLevel for CRM/SMS/calendars and Make for more complex automation?

Where should client automations live?
My agency account, separate client sub-accounts/workspaces, or the client’s own software accounts?

Who normally pays software/usage costs?
Things like HighLevel, Make, Twilio, OpenAI, phone numbers, SMS and voice usage.
Do you bundle this into your monthly price or have clients pay separately?

Do you collect setup/software costs upfront?
I don’t want to fund a client’s infrastructure before they’ve paid.

How reusable are templates in reality?
Can the same lead-response system genuinely work across roofing, dental, legal, automotive, etc., with only configuration changes?

How do you handle customisation and scope creep?
Higher setup fee, project fee, hourly, or premium monthly package?

Which automations are businesses actually willing to pay for repeatedly?
How much ongoing support do these systems need once deployed?
I’m still at the validation/building stage, so I’m especially interested in advice from solo agency owners on software stack, account ownership, pricing, and keeping delivery scalable.
Would appreciate any lessons from people who have actually done this.

I appreciate your feedback in advance 😀

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u/Personal-Business802 — 13 days ago