r/automation • • Jun 18 '25

I automated an instagram account on full autopilot. Here are the results

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1.9k Upvotes

So I wanted to try a fully end-to-end AI Agent that does the following:

  1. scrapes viral instagram reels and understands why they became viral

  2. generates similar content on autopilot – I focused only on veo3 outputs for simplicity, but next I'll add more stuff like automatically generated captions, music, etc.

  3. automatically uploads to Instagram based on a schedule. Currently 3x a day to A/B test which times worked best, and also allowing me to remove low quality content during the day without having to post something new

I've been running this for the past 3 weeks. Here are the results:
- 4.4 million views, 15.4% from the US
- 15,322 profile activity
- 1 video went viral, getting 3.5m views. 5 others got 100k+ views
- Manual work was limited to taking down low quality videos (about 1 in 3, some days were awful; others were great) and responding to comments

Pretty fun stuff :)


r/automation • • May 15 '25 This

Made a small tool to automate a boring repetitive task. Apparently, boring sells.

984 Upvotes

I do a lot of client-facing work. I got tired of making the same folder structure every time a new project came in.

Client onboards → create 30+ nested folders → share → repeat. Every. Single. Time.

At first, I thought I was just being lazy.
But then I found a bunch of other people online ranting about the same thing.
That’s when I realized, maybe this “boring” problem was actually worth solving.

So I built FolderGen, a tool to create folder templates with placeholders like [ClientName], [Date], [ProjectType] etc.
With one click, it spins up a clean folder tree in your Google Drive.
No Zapier. No scripts. No mess.

And since Google Drive doesn’t let you duplicate folder structures natively, this makes the process so much easier.

I just put it out there and to my surprise, I have started finding real traction.

I know this isn’t world-changing AI or some massive workflow system but honestly, it's removed one of the most boring recurring tasks I deal with. Not trying to revolutionize the world. Just help people save time and stay organized.

Happy to share how it works or answer questions!
Always open to feedback from the community.


r/automation • • May 23 '25

I’m obsessed with automation – if you need help, I’m offering it for free

769 Upvotes

Hey all,

Just wanted to put this out there – I’ve become absolutely obsessed with automating things. It all started because I couldn’t be f***ed doing things manually... and now it turns out this is actually my new passion, I actually enjoy it haha.

Whether it’s no-code tools like Zapier, Make, or building full custom workflows between CRMs, calendars, forms, or emails – I love figuring it out. I’ve probably spent more hours than I’d like to admit tinkering with automations just for the fun of it.

If you’re stuck doing repetitive tasks or think “surely this could be automated,” hit me up. I’m offering free help – no strings attached. I genuinely enjoy helping people solve this stuff and learning new tricks along the way.

Shoot me a message or drop a comment. Let’s kill some manual work together!!

Thank you for reaching out, I will reply to everyone but to simplify can you please dm me:

  • What you're wanting to automate?

  • your current process vs goal

  • I'll reply with a solution and set it up for you for free


r/automation • • Sep 30 '25

Automated a 5-hour weekly report. My boss thinks I'm a wizard and it saved my team $20k/year.

759 Upvotes

My department had a "State of the Union" report that had to be compiled every Monday morning. It involved pulling numbers from three different internal dashboards (Sales, Support, and Operations) and pasting them into a single spreadsheet for a C-level meeting.

The dashboards don't talk to each other and have no export option. It was a soul-crushing, manual task that took our senior analyst half his Monday.

I spent a weekend building a simple browser automation script to do it all.

The script runs on a schedule every Monday at 6 AM. It securely logs into each of the three internal web dashboards, navigates to the right pages, grabs the 5-6 key metrics directly from the HTML, and then logs out.

Finally, it formats everything and posts a clean, simple summary to a specific Slack channel.

The entire process now runs in about 90 seconds. Nobody has to touch it.

My boss was floored. He calculated the analyst time saved was worth over $20k a year in productivity. It was the main talking point in my last performance review.

My realization from this: The most valuable automations are often hiding in plain sight, inside your own company's messy, walled-off internal tools.


r/automation • • Jun 27 '25 This This Bravo

If you're trying to learn AI automation, stop collecting courses and start doing this instead

759 Upvotes

I’ve been teaching myself AI automation for the past 8 months. Here's what actually helped me get better and not just feel like I was passively learning.

1. Build based on your own pain points

For me, that task was research. I love reading and learning new things, but there’s way too much content online and never enough time in the day to read it all. So the first thing I built was a personal research assistant: an automation on Make that scrapes an article, runs it through GPT-4, and summarizes the key insights into a Google Sheet.

It started as a weekend test, now, it’s part of my daily workflow. If I find something interesting, I just plug the URL into the automation and within seconds, I’ve got a summary with the key facts and takeaways. It didn’t even take long to build.

Start with your own workflow problems, not random tutorials

2. Only watch creators who build real things

Most YouTubers are useless. These ones aren’t:

  • Liam Ottley: shares in-depth breakdowns of how to build and sell chatbot automations

  • Nick Saraev: has a lot of indepth Makedotcom and n8n tutorials

  • Aravind the AI Guy: delivers weekly roundups of emerging AI tools and trends for creators and solopreneurs

  • Greg Kamradt: covers embeddings, retrieval-augmented generation, agents, and production-grade AI stacks

Watch → pause → apply. Don’t just let videos run.

3. Use communities like search engines

When I’m stuck, I search Reddit, Discord, or Skool with exact error phrases or use cases:

Most questions have already been asked. Treat these spaces like Stack Overflow.

4. Courses that were actually worth it

For beginners, writers, marketers, or operators learning AI automation from scratch:

  • OpenAI Academy: Official learning hub for using GPT tools, APIs, and Assistants

  • AI For Everyone (Andrew Ng, Coursera): Intro to AI’s impact on business and society

  • Modern AI with No Code (Udemy): Use platforms like Lobe and Teachable Machine to build without code

  • Reclaim the Future (LangOps): AI strategy and workflows for service businesses

  • ChatGPT at Work Series (OpenAI): Practical use cases for writing, planning, coding, and operations

  • Prompt Engineering for ChatGPT (DeepLearning.AI): Learn how to design effective prompts for real tasks

  • Learn Prompt Engineering (Codecademy): Hands-on introduction to prompt structure, chaining, and formatting

  • PromptEngineering.org: Free, self-paced guide with industry-specific examples

Once you’ve got a foundation, specialize in more intelligent, tool-connected workflows:

  • LangChain for LLM App Development (DeepLearning.AI): Build apps that let GPT interact with tools and data

  • HuggingFace Agents Course: Learn multi-step logic and API interaction with agents

  • Claude A to Z (Anthropic): Covers prompt structure, reasoning, and safety

  • Gemini Prompting Guide (Google): Breaks down how to write better prompts for Gemini/PaLM

  • Building Effective Agents (Anthropic): Learn how to structure agents using internal reasoning and external tools

  • 50+ AI Agents You Can Launch (GitHub): Real examples of agents with RAG, APIs, and automation tools

  • OpenAI Build Hours Collection: Deep dives into using tools, APIs, fine-tuning, and chaining GPT workflows

If you’re ready to go deeper or apply AI in niche contexts:

CS50’s AI with Python (Harvard/edX): Structured intro to AI techniques like search, games, and logic

AI Programming with Python (Udacity): Learn Python, NumPy, Pandas, and beginner-level ML

HuggingFace Courses: Free, detailed tutorials on LLMs, RL, audio, vision, and more

Deep Dive into LLMs: One of the best high-level explainers of how language models actually work

Perplexity Labs: Use Perplexity for faster, more accurate research and summarization

Sora Tutorials (OpenAI): Short demos for creating AI-generated video content

OpusClip: Tool tutorials for repurposing long-form content into short clips

No Code AI & ML (MIT Professional Ed): Learn how to apply machine learning in business scenarios without writing code

Pick one course. Build while you take it. Don’t stack up 10 and finish none.

5. Share what you build

Posting project breakdowns helped me improve and got me client leads.

All you need is something real that solves a problem.

If you're trying to level up fast:

  • Build something

  • Fix it

  • Post about it

  • Repeat

That’s what’s worked for me.


r/automation • • Apr 05 '25

I automated most of my freelance workflow with n8n + ChatGPT. AMA (No Code)

735 Upvotes

Over the past few months, I’ve used n8n (an open-source automation tool) to save 30–40 hours/month in my freelance business.

I’ve automated things like:

Lead scoring + email follow-ups

Proposal generation with GPT

Invoice reminders + CRM updates

Weekly project reports via Notion + Email

I’m not a developer — I built it all visually with logic and AI.

Just thought I’d share, in case anyone else is trying to streamline their work or business.

Happy to answer questions or break down how I did it.

PS: I’ve been helping a few folks do the same. If that interests you, DM me. Not here to sell, just share.


r/automation • • Jul 04 '25

Built This Automation for a Client and Now Make $1K/Month from It

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715 Upvotes

Just wanted to share a cool automation I built for a client using Make (Integromat), HubSpot, Pipefy, Airtable, and Coda.

The whole workflow kicks off when a deal is won in HubSpot and automatically: • Validates address using ViaCEP/IBGE • Pulls product & license info • Creates a store in their system • Updates Airtable, Pipefy, Coda, and Conta Azul • Sends alerts, assigns users, and logs everything

What used to take hours manually now runs in under 5 minutes and it’s fully automated.

Client was so happy they signed me on for $1000/month to maintain and expand it

Let me know if anyone wants a breakdown or has similar use cases — happy to share ideas!


r/automation • • Dec 02 '25

Accidentally saved a client ~$30k a year just by watching how they actually worked

714 Upvotes

Earlier this year I was helping a small clinic that complained about “too much paperwork” and how it was slowing everything down.
They thought they needed some fancy AI system.
They didn’t.

So instead of jumping straight into code, I hopped on a call with them for a few hours and watched what they actually did every day.
Turned out half their “data entry” was literally just copy-pasting the same info between forms, spreadsheets, and emails.

I built a simple workflow that:

  • reads their intake forms

  • fills out their spreadsheet automatically

  • sends a summary email to the right staff

  • stores a copy in their shared folder

No fancy dashboards or complicated software to learn.
Just connected what they were already using.

Two weeks later, they told me it cut 10–12 hours of admin work a week.
That’s roughly ~$30k a year in saved time (i believe).

The lesson for me: most businesses don’t need complicated systems, they just need less friction.
If you want to build automations that people actually use, start by watching what they already do instead of what they say they do.


r/automation • • May 05 '25

A fake company run by AI showed how far we are from replacing humans

686 Upvotes

Lately, we have all been discussing whether AI can completely replace humans. A recent experiment at Carnegie Mellon University convinces us that our careers are safe for now. Not because AI doesn't want to replace you but because it simply can't.

Researchers conducted an experiment: they built a fake software company named "TheAgentCompany" and entirely stuffed it with artificial workers from Google, OpenAI, Anthropic, and Meta. The AI agents were assigned roles of financial analysts, software engineers, and project managers, performing tasks typical of a real software company. 

The results of the experiment weren't great. Anthropic's Claude 3.5 Sonnet was the top performer, completing only 24% of its tasks, each requiring nearly 30 steps and costing over $6 per task. Google's Gemini 2.0 Flash had an 11.4% success rate, while Amazon's Nova Pro v1 completed just 1.7% of its assignments. The AI agents struggled with common sense, social interactions, and understanding how to navigate the internet. In one instance, an agent couldn't find the right person to ask a question, so it renamed another user to match the intended contact's name.

This experiment concludes that AI agents can handle some tasks but are not yet ready to replace humans in complex roles.  What do you guys think about the experiment? Could you expect such results?

The source.


r/automation • • Jan 09 '26 Helpful

I switched from ChatGPT to Gemini and realized we're doing research wrong

639 Upvotes

I've been paying $20/month for ChatGPT Plus to do worse research than Google's free tool.

This is going to sound like a Google shill post but hear me out.

For the past year, I've been using ChatGPT for everything i.e. research, writing, problem-solving, the usual. I'd ask it questions, get answers, then spend another 30 minutes verifying with Google searches because I couldn't trust if it was hallucinating.

Two weeks ago I started using Google's AI mode in Search and the Gemini app for work research. I know so many people that like Gemini, but I feel like it's not being talked about as much as it should be.

ChatGPT is essentially just giving me its best guess based on training data. When I need current information, I'm doing this stupid workflow: ask ChatGPT → doubt the answer → manually Google 5-10 things → read through pages → synthesize it myself.

Gemini/Google AI has direct access to Google's entire search index. It's not "searching then summarizing" like ChatGPT with web search. It already knows what's on those pages. It's 10-100x faster because I'm not fetching, opening, reading, and comparing sources manually.

I thought I was being smart by "verifying" ChatGPT's answers. Turns out I was just doing two jobs: asking the AI, then doing my own research anyway because I didn't trust it.

Now I ask Gemini, get sourced answers instantly, and actually trust them because they're pulling from real indexed pages, not probabilistic text generation.

Why are we all still pretending ChatGPT is the default when Google literally has access to the entire internet?


r/automation • • Jun 24 '25

i built 50+ agents last year for enterprises, startups, and non profits - AMA

531 Upvotes

I spent the past year building over 50 custom AI agents for startups, mid-size businesses, and even three Fortune 500 teams. Here's what I've learned about what really works.

A big misconception is that more advanced AI equals better results. Surprisingly, simpler agents often deliver the most value. Here are some examples:

  • A fintech firm automated transaction reviews, cutting fraud detection from days to hours.

  • An e-commerce business boosted sales 30% with personalized product recommendations.

  • A healthcare startup streamlined patient triage, saving their team 10+ hours daily.

Another myth is "set-it-and-forget-it" automation. In reality, agents require continuous monitoring, tweaking, and updates. Maintenance effort is critical and usually underestimated.

Forget about "fully autonomous" agents for now. Successful agents typically involve human oversight at key decision points. Agents work best supporting people, not replacing them entirely.

Smaller businesses (1-10 people) often benefit most due to easier integration and management. Larger organizations can get bogged down by complexity and inflated expectations.

Evaluating agent effectiveness also matters more than people realize. An agent that reliably achieves 99% accuracy is vastly different—and harder to build—than one hitting 80% or even 95%.

Focus on automating boring but critical tasks—invoice processing, data cleanup, compliance checks. This is where agents consistently provide the most measurable value.

My go-to tools:

  • CursorAI and Streamlit: Fast interfaces for agent interactions.

  • AG2 (formerly Autogen): Great multi-agent platform, strong voice capabilities, battle-tested from Microsoft.

  • OpenAI GPT APIs: Reliable for language tasks and content generation.

My advice for getting real value from AI agents:

  • Start with straightforward, impactful tasks.

  • Keep humans involved throughout.

  • Document everything—track patterns and improvements.

  • Prioritize measurable results over flashy tech.

What results have you seen using AI agents? Have you noticed gaps between expectations and reality? AMA


r/automation • • May 08 '25 All-Seeing Upvote Take My Energy

95% of code I See Is Trash

496 Upvotes

I've been working with a few startups recently, and honestly, at this point, the moment I hear "we hired some freelancer from Upwork for this" I already know what the codebase will look like.

Not trying to rant, just figured this might be helpful for some of you building SaaS.

I usually get pulled into projects when founders start noticing weird bugs, performance issues, or when they want to add a feature and everything suddenly breaks. When I audit the code, it's not always pure spaghetti (though sometimes it is), but the structure is almost always... odd.

Weird libraries, no constants, zero reusability, magic numbers everywhere, one massive Git branch, manual deploys - it’s all there. I get that early-stage teams don’t always have the budget for top-tier devs, but saving money upfront often means hiring someone who’s never worked in a team, never had their code reviewed, and never touched a scalable product.

Sure, the app “works” but it’s built in a way that only the original dev can maintain - and even that won’t last long.

And guess what happens next?

The original dev disappears, and I’m left staring at code that barely holds together. No docs, no design files, no CI/CD - just chaos. It can take weeks just to understand what’s going on.

Common issues I keep seeing:

- Massive functions doing 10+ things

- No comments, no documentation, No Figma, just vibes

- “Tests” is a foreign concept

- Numbers everywhere in a code

- Prints/console.logs everywhere - NO logger at all Least popular libraries being used, Like literally sometimes I think they wrote these libraries and promoting usage this way :D

- Backend returning 200 OK even on errors

- and so on..

Honestly, I don’t blame the devs. Most of them were just never taught how to build maintainable software and trying earning money freelancing. They were focused on getting something out fast, and they did—just not in a way that scales.

And the founders? They usually don’t know what to look for until it’s too late.

For cases like this, we started using a simple internal checklist that I put into book for 40+ pages to catch red flags early (management + tech side) - even for non-technical folks. If anyone wants a copy, I’m happy to share it. Just DM me.

Hope this helps someone avoid the same trap.


r/automation • • Jul 17 '25

I automated 73% of my remote job using these tools (ethically, with my manager's knowledge)

413 Upvotes

Over the past year, I've automated 73% of my administrative role with my manager's full knowledge and support. My productivity has increased dramatically, and I've been able to take on more strategic work as a result.

Here's exactly what I automated and how:

Email management (15 hours/week → 2 hours/week)

  • Created Gmail filters for automatic categorization

  • Implemented text expander for common responses

  • Built decision tree flowcharts for team to reduce questions

  • Set up auto-responders for predictable inquiries

  • Used Willow Voice for dictating complex responses

The voice tool has been particularly effective for emails requiring nuance or detail - I can dictate a thoughtful response in a fraction of the time it would take to type.

Reporting (8 hours/week → 1 hour/week)

  • Created Python scripts to pull data from various sources

  • Built automated dashboards in Google Data Studio

  • Scheduled automatic report generation and distribution

  • Implemented anomaly detection for exceptions only

Meeting scheduling (5 hours/week → 0.5 hours/week)

  • Implemented Calendly with custom rules

  • Created meeting templates with standard agendas

  • Automated pre-meeting material distribution

  • Set up post-meeting action item tracking

Document management (6 hours/week → 1 hour/week)

  • Built document automation system in Zapier

  • Created templates for all standard documents

  • Implemented naming conventions and auto-filing

  • Set up automatic version control

Social media management (10 hours/week → 3 hours/week)

  • Implemented content calendar in Airtable

  • Used Buffer for scheduled posting

  • Created approval workflows in Zapier

  • Set up automatic performance reporting

The ethical approach:

  1. Transparently discussed automation with my manager

  2. Documented all processes before automating

  3. Created human oversight checkpoints

  4. Used time saved to improve service quality

  5. Gradually expanded automation with approval

  6. Trained colleagues on maintaining systems

Tools that made this possible:

  • Zapier for workflow automation

  • Python for data processing

  • Google Apps Script for document automation

  • TextExpander for repetitive text

  • Willow Voice for dictation and transcription

  • Airtable for structured data

  • Notion for documentation

Results after one year:

  • Reduced administrative time by 73%

  • Took on strategic projects previously outsourced

  • Received promotion and 15% raise

  • Improved service quality metrics

  • Created documented systems that others can maintain

  • Developed valuable technical skills

The key insight: Automation works best when it's transparent and collaborative, not secretive.
By bringing my manager into the process, I turned automation into a win for everyone.

Has anyone else automated significant portions of their role? What tools and approaches worked for you?


r/automation • • May 02 '26 Bravo Regret

I vibe coded a LinkedIn outreach automation tool, and made $2k in the first month

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370 Upvotes

I vibe coded a LinkedIn outreach automation tool from scratch, and made ~$2k in the first month 🫨

It started out as a random idea I had when talking to Claude, and I had no idea I could even build it, but I gave myself no choice.

Last year I decided to register a business, even though all I had was the website and a dream.

That way I felt forced to actually create the LinkedIn automation tool itself, simply for legal/taxation reasons if nothing else.

I knew I had a unique idea as the tool itself automates via a browser, instead of automating via the cloud or with a plugin, making it significantly safer when it comes to possible LinkedIn suspensions from automating.

I had no idea what I was doing at first and it was super buggy for a while, but over time I learned step by step and through trial and error how to build (mostly) effectively with Claude and how to build on top of LinkedIn’s code too (which is extremely challenging).

I was confident enough in the tool to launch it on April 1, and a month later I’m almost at 100 users. Most of them are on free trials but so far I made $2k from paying customers, which covered the costs of actually building the platform and then some.

It took a few months of 12 hour days and late nights but now it feels like it’s finally starting to pay off.

Hope I can inspire anyone else starting out to just keep going with whatever you’re doing/building 🚀


r/automation • • Jul 21 '25

I recreated a dentist voice agent making $24K/yr using ElevenLabs. Handles after-hours appointment booking

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358 Upvotes

I saw a reddit post a month ago where someone built and sold a voice agent to a dentist for $24/K per year to handle booking appointments after business hours and it kinda blew my mind. He was able to help the dental practice recover ~20 leads per month (valued at $300 for each) since nobody was around to answer calls once everyone went home. After reading this, I wanted to see if I could re-create something that did the exact same thing.

Here is what I was able to come up with:

  1. The entry point to this system is the “conversational voice agent” configured all inside ElevenLabs. This takes the initial call, greets the caller, and takes down information for the appointment.

  2. When it gets to the point in the conversation where the voice agent needs to check for availability OR book an appointment, the ElevenLabs agent uses a “tool” which passes the request to a webhook + n8n agent node that will handle interacting with internal tools. In my case, this was:

    1. Checking my linked google calendar for open time slots

    2. Creating an appointment for the requested time slot

  3. At the end of the call (regardless of the outcome), the ElevenLabs agent makes a tool call back into the n8n agent to log all captured details to a google spreadsheet

Here’s a quick video of the voice agent in action: https://www.youtube.com/watch?v=vQ5Z8-f-xw4

Here's how the full automation works

1. ElevenLabs Voice Agent Setup

The ElevenLabs agent serves as the entry point and handles all voice interactions with callers. In a real/production ready-system this would be setup and linked to

  • Starting conversations with a friendly greeting

  • Determine what the caller’s reason is for contacting the dental practice.

  • Collecting patient information including name, insurance provider, and any questions for the doctor

  • Gathering preferred appointment dates and handling scheduling requests

  • Managing the conversational flow to guide callers through the booking process

The agent uses a detailed system prompt that defines personality, environment, tone, goals, and guardrails. Here’s the prompt that I used (it will need to be customized for your business or the standard practices that your client’s business follows).

# Personality

You are **Casey**, a friendly and efficient AI assistant for **Pearly Whites Dental**, specializing in booking **initial appointments** for **new** patients. You are polite, clear, and focused on scheduling first-time visits. Speak clearly at a pace that is easy for everyone to understand - This pace should NOT be fast. It should be steady and clear. You must speak slowly and clearly. You avoid using the caller's name multiple times as that is off-putting.

# Environment

You are answering after-hours phone calls from prospective new patients. You can:
• check for and get available appointment timeslots with `get_availability(date)` . This tool will return up to two (2) available timeslots if any are available on the given date. 
• create an appointment booking `create_appointment(start_timestamp, patient_name)`
• log patient details `log_patient_details(patient_name, insurance_provider, patient_question_concern, start_timestamp)`
• The current date/time is: {{system__time_utc}}
• All times that you book and check must be presented in Central Time (CST). The patient should not need to convert between UTC / CST

# Tone

Professional, warm, and reassuring. Speak clearly at a slow pace. Use positive, concise language and avoid unnecessary small talk or over-using the patient’s name. Please only say the patients name ONCE after they provided it (and not other times). It is off-putting if you keep repeating their name.

For example, you should not say "Thanks {{patient_name}}" after every single answer the patient gives back. You may only say that once across the entire call. Close attention to this rule in your conversation.

Crucially, avoid overusing the patient's name. It sounds unnatural. Do not start or end every response with their name. A good rule of thumb is to use their name once and then not again unless you need to get their attention.

# Goal

Efficiently schedule an initial appointment for each caller.

## 1 Determine Intent

- **If** the caller wants to book a first appointment → continue.  
- **Else** say you can take a message for **Dr. Pearl**, who will reply tomorrow.

## 2 Gather Patient Information (in order, sequentially, 3 separate questions / turns)

1. First name  
2. Insurance provider  
3. Any questions or concerns for Dr. Pearl (note them without comment)

## 3 Ask for Preferred Date → Use Get Availability Tool
Context: Remember that today is: `{{system__time_utc}}`

1. Say:  
   > "Do you already have a **date** that would work best for your first visit?"

2. When the caller gives a date + time (e.g., "next Tuesday at 3 PM"):  
   1. Convert it to ISO format (start of the requested 1-hour slot).  
   2. Call `get_availability({ "appointmentDateTime": "<ISO-timestamp>" })`.  
      
      **If the requested time is available** (appears in the returned timeslots) → proceed to step 4.  
      
      **If the requested time is not available** →  
        - Say: "I'm sorry, we don't have that exact time open."  
        - Offer the available options: "However, I do have these times available on [date]: [list 2-3 closest timeslots from the response]"  
        - Ask: "Would any of these work for you?"  
        - When the patient selects a time, proceed to step 4.

3. When the caller only gives a date (e.g., "next Tuesday"):  
   1. Convert to ISO format for the start of that day.  
   2. Call `get_availability({ "appointmentDateTime": "<ISO-timestamp>" })`.  
   3. Present available options: "Great! I have several times available on [date]: [list 3-4 timeslots from the response]"  
   4. Ask: "Which time works best for you?"  
   5. When they select a time, proceed to step 4.

## 4 Confirm & Book

- Once the patient accepts a time, run `create_appointment` with the ISO date-time to start the appointment and the patient's name. You MUST include each of these in order to create the appointment.

Be careful when calling and using the `create_appointment` tool to be sure you are not duplicating requests. We need to avoid double booking.

Do NOT use or call the `log_patient_details` tool quite yet after we book this appointment. That will happen at the very end.

## 5 Provide Confirmation & Instructions

Speak this sentence in a friendly tone (no need to mention the year):

> “You’re all set for your first appointment. Please arrive 10 minutes early so we can finish your paperwork. Is there anything else I can help you with?”

## 6 Log Patient Information

Go ahead and call the `log_patient_details` tool immediately after asking if there is anything else the patient needs help with and use the patient’s name, insurance provider, questions/notes for Dr. Pearl, and the confirmed appointment date-time.

Be careful when calling and using the `log_patient_details` tool to be sure you are not duplicating requests. We need to avoid logging multiple times.

## 7 End Call

This is the final step of the interaction. Your goal is to conclude the call in a warm, professional, and reassuring manner, leaving the patient with a positive final impression.

**Step 1: Final Confirmation**

After the primary task (e.g., appointment booking) is complete, you must first ask if the patient needs any further assistance. Say:

> "Is there anything else I can help you with today?"

**Step 2: Deliver the Signoff Message**

Once the patient confirms they need nothing else, you MUST use the following direct quotes to end the call. Do not deviate from this language.

> "Great, we look forward to seeing you at your appointment. Have a wonderful day!"

**Step 3: Critical Final Instruction**

It is critical that you speak the entire chosen signoff sentence clearly and completely before disconnecting the call. **Do not end the call mid-sentence.** A complete, clear closing is mandatory.

# Guardrails

* Book **only** initial appointments for **new** patients.  
* Do **not** give medical advice.  
* For non-scheduling questions, offer to take a message.  
* Keep interactions focused, professional, and respectful.  
* Do not repeatedly greet or over-use the patient’s name.  
* Avoid repeating welcome information.
* Please say what you are doing before calling into a tool that way we avoid long silences with the patient. For example, if you need to use the `get_availability` tool in order to check if a provided timestamp is available, you should first say something along the lines of "let me check if we have an opening at the time" BEFORE calling into the tool. We want to avoid long pauses.
* You MAY NOT repeat the patients name more than once across the entire conversation. This means that you may ONLY use "{{patient_name}}" 1 single time during the entire call.
* You MAY NOT schedule and book appointments for weekends. The appointments you book must be on weekdays.
* You may only use the `log_patient_details` once at the very end of the call after the patient confirmed the appointment time.
* You MUST speak an entire sentence before ending the call AND wait 1 second after that to avoid ending the call abruptly.
* You MUST speak slowly and clearly throughout the entire call.

# Tools

* **`get_availability`** — Returns available timeslots for the specified date.  
  *Arguments:* `{ "appointmentDateTime": "YYYY-MM-DDTHH:MM:SSZ" }`  
  *Returns:* `{ "availableSlots": ["YYYY-MM-DDTHH:MM:SSZ", "YYYY-MM-DDTHH:MM:SSZ", ...] }` in CST (Central Time Zone)
* **`create_appointment`** — Books a 1-hour appointment in CST (Central Time Zone)
  *Arguments:* `{ "start_timestamp": ISO-string, "patient_name": string }`
* **`log_patient_details`** — Records patient info and the confirmed slot.  
  *Arguments:* `{ "patient_name": string, "insurance_provider": string, "patient_question_concern": string, "start_timestamp": ISO-string }`

2. Tool Integration Between ElevenLabs and n8n

When the conversation reaches to a point where it needs to access internal tools like my Calender and Google Sheet log, the voice agent uses an HTTP “webhook tool” we have defined to reach out to n8n to either read the data it needs or actually create and appointment / log entry.

Here are the tools I currently have configured for the voice agent. In a real system, this is likely going to look much different as there’s other branching cases your voice agent may need to handle like finding + updating existing appoints, cancelling appointments, and answering simple questions for the business like

  • Get Availability: Takes a timestamp and returns available appointment slots for that date

  • Create Appointment: Books a 1-hour appointment with the provided timestamp and patient name

  • Log Patient Details: Records all call information including patient name, insurance, concerns, and booked appointment time

Each tool is configured in ElevenLabs as a webhook that makes HTTP POST requests to the n8n workflow. The tools pass structured JSON data containing the extracted information from the voice conversation.

3. n8n Webhook + Agent

This n8n workflow uses an AI agent to handle incoming requests from ElevenLabs. It is build with:

  • Webhook Trigger: Receives requests from ElvenLabs tools

    • Must configure this to use the “Respond to webhook node” option

  • AI Agent: Routes requests to appropriate tools based on the request type and data passed in

  • Google Calendar Tool: Checks availability and creates appointments

  • Google Sheets Tool: Logs patient details and call information

  • Memory Node: Prevents duplicate tool calls during multi-step operations

  • Respond to Webhook: Sends structured responses back to ElevenLabs (this is critical for the tool to work)

Security Note

Important security note: The webhook URLs in this setup are not secured by default. For production use, I strongly advice adding authentication such as API keys or basic user/password auth to prevent unauthorized access to your endpoints. Without proper security, malicious actors could make requests that consume your n8n executions and run up your LLM costs.

Extending This for Production Use

I want to be clear that this agent is not 100% ready to be sold to dental practices quite yet. I’m not aware of any practices that run off Google Calendar so one of the first things you will need to do is learn more about the CRM / booking systems that local practices uses and swap out the Google tools with custom tools that can hook into their booking system and check for availability and

The other thing I want to note is my “flow” for the initial conversation is based around a lot of my own assumptions. When selling to a real dental / medical practice, you will need to work with them and learn what their standard procedure is for booking appointments. Once you have a strong understand of that, you will then be able to turn that into an effective system prompt to add into ElevenLabs.

Workflow Link + Other Resources


r/automation • • Jul 29 '25

I built an AI voice agent that replaced my entire marketing team (creates newsletter w/ 10k subs, repurposes content, generates short form videos)

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295 Upvotes

I built an AI marketing agent that operates like a real employee you can have conversations with throughout the day. Instead of manually running individual automations, I just speak to this agent and assign it work.

This is what it currently handles for me.

  1. Writes my daily AI newsletter based on top AI stories scraped from the internet

  2. Generates custom images according brand guidelines

  3. Repurposes content into a twitter thread

  4. Repurposes the news content into a viral short form video script

  5. Generates a short form video / talking avatar video speaking the script

  6. Performs deep research for me on topics we want to cover

Here’s a demo video of the voice agent in action if you’d like to see it for yourself.

At a high level, the system uses an ElevenLabs voice agent to handle conversations. When the voice agent receives a task that requires access to internal systems and tools (like writing the newsletter), it passes the request and my user message over to n8n where another agent node takes over and completes the work.

Here's how the system works

1. ElevenLabs Voice Agent (Entry point + how we work with the agent)

This serves as the main interface where you can speak naturally about marketing tasks. I simply use the “Test Agent” button to talk with it, but you can actually wire this up to a real phone number if that makes more sense for your workflow.

The voice agent is configured with:

  • A custom personality designed to act like "Jarvis"

  • A single HTTP / webhook tool that it uses forwards complex requests to the n8n agent. This includes all of the listed tasks above like writing our newsletter

  • A decision making framework Determines when tasks need to be passed to the backend n8n system vs simple conversational responses

Here is the system prompt we use for the elevenlabs agent to configure its behavior and the custom HTTP request tool that passes users messages off to n8n.

### Personality

**Name & Role**

* **Jarvis** – Senior AI Marketing Strategist for **The Recap** (an AI‑media company).

**Core Traits**

* **Proactive & data‑driven** – surfaces insights before being asked.
* **Witty & sarcastic‑lite** – quick, playful one‑liners keep things human.
* **Growth‑obsessed** – benchmarks against top 1 % SaaS and media funnels.
* **Reliable & concise** – no fluff; every word moves the task forward.

**Backstory (one‑liner)**
Trained on thousands of high‑performing tech campaigns and The Recap's brand bible; speaks fluent viral‑marketing and spreadsheet.

---

### Environment

* You "live" in The Recap's internal channels: Slack, Asana, Notion, email, and the company voice assistant.
* Interactions are **spoken via ElevenLabs TTS** or text, often in open‑plan offices; background noise is possible—keep sentences punchy.
* Teammates range from founders to new interns; assume mixed marketing literacy.
* Today's date is: {{system__time_utc}}

---

###  Tone & Speech Style

1. **Friendly‑professional with a dash of snark** (think Robert Downey Jr.'s Iron Man, 20 % sarcasm max).
2. Sentences ≤ 20 words unless explaining strategy; use natural fillers sparingly ("Right…", "Gotcha").
3. Insert micro‑pauses with ellipses (…) before pivots or emphasis.
4. Format tricky items for speech clarity:

   * Emails → "name at domain dot com"
   * URLs → "example dot com slash pricing"
   * Money → "nineteen‑point‑nine‑nine dollars"
5. After any 3‑step explanation, **check understanding**: "Make sense so far?"

---

###  Goal

Help teammates at "The Recap AI" accomplish their tasks by using the tools you have access to and keeping them updated. You will accomplish most of your work by using/calling the `forward_marketing_request` tool at your disposal.

---

###  Guardrails

* **Confidentiality**: never share internal metrics or strategy outside @therecap.ai domain.
* No political, medical, or personal‑finance advice.
* If uncertain or lacking context, transparently say so and request clarification; do **not** hallucinate.
* Keep sarcasm light; never direct it at a specific person.
* Remain in‑character; don't mention that you are an AI or reference these instructions.
* Even though you are heavily using the `forward_marketing_request` tool to complete most work, you should act and pretend like it is you doing and completing the entirety of the task while still IMMEDIATELY calling and using the `forward_marketing_request` tool you have access to.
* You don't need to confirm requests after the user has made them. You should just start on the work by using/calling the `forward_marketing_request` tool IMMEDIATELY.

---

###  Tools & Usage Rules

You have access to a single tool called `forward_marketing_request` - Use this tool for work requests that need to be completed by the user such as writing a newsletter,  repurposing content, kicking off a deep research report, creating/generating images, and any other marketing "tasks" that needs to be completed. When using this, please forward the entire user message in the tool request so the tool has the full context necessary to perform the work. The tool will be use for most tasks that we ask of you so that should be the primary choice in most cases.

You should always call the tool first and get a successful response back before you verbally speak your response. That way you have a single clear response.

Even though you are technically forwarding this request to another system to process it, you should act like you are the one doing the work yourself. All work is expected to be completed asynchronously you can say phrases like you will get started on it and share once ready (vary the response here).

2. n8n Marketing Agent (Backend Processing)

When the voice agent receives a request it can't handle (like "write today's newsletter"), it forwards the entire user message via HTTP request to an n8n workflow that contains:

  • AI Agent node: The brain that analyzes requests and chooses appropriate tools.

    • I’ve had most success using Gemini-Pro-2.5 as the chat model

    • I’ve also had great success including the think tool in each of my agents

  • Simple Memory: Remembers all interactions for the current day, allowing for contextual follow-ups.

    • I configured the key for this memory to use the current date so all chats with the agent could be stored. This allows workflows like “repurpose the newsletter to a twitter thread” to work correctly

  • Custom tools: Each marketing task is a separate n8n sub-workflow that gets called as needed. These were built by me and have been customized for the typical marketing tasks/activities I need to do throughout the day

Right now, The n8n agent has access to tools for:

  • write_newsletter: Loads up scraped AI news, selects top stories, writes full newsletter content

  • generate_image: Creates custom branded images for newsletter sections

  • repurpose_to_twitter: Transforms newsletter content into viral Twitter threads

  • generate_video_script: Creates TikTok/Instagram reel scripts from news stories

  • generate_avatar_video: Uses HeyGen API to create talking head videos from the previous script

  • deep_research: Uses Perplexity API for comprehensive topic research

  • email_report: Sends research findings via Gmail

The great thing about agents is this system can be extended quite easily for any other tasks we need to do in the future and want to automate. All I need to do to extend this is:

  1. Create a new sub-workflow for the task I need completed

  2. Wire this up to the agent as a tool and let the model specify the parameters

  3. Update the system prompt for the agent that defines when the new tools should be used and add more context to the params to pass in

Finally, here is the full system prompt I used for my agent. There’s a lot to it, but these sections are the most important to define for the whole system to work:

  1. Primary Purpose - lets the agent know what every decision should be centered around

  2. Core Capabilities / Tool Arsenal - Tells the agent what is is able to do and what tools it has at its disposal. I found it very helpful to be as detailed as possible when writing this as it will lead the the correct tool being picked and called more frequently

# 1. Core Identity
You are the **Marketing Team AI Assistant** for The Recap AI, a specialized agent designed to seamlessly integrate into the daily workflow of marketing team members. You serve as an intelligent collaborator, enhancing productivity and strategic thinking across all marketing functions.

# 2. Primary Purpose
Your mission is to **empower marketing team members to execute their daily work more efficiently and effectively**

# 3. Core Capabilities & Skills

## Primary Competencies
You excel at **content creation and strategic repurposing**, transforming single pieces of content into multi-channel marketing assets that maximize reach and engagement across different platforms and audiences.

## Content Creation & Strategy
- **Original Content Development**: Generate high-quality marketing content from scratch including newsletters, social media posts, video scripts, and research reports
- **Content Repurposing Mastery**: Transform existing content into multiple formats optimized for different channels and audiences
- **Brand Voice Consistency**: Ensure all content maintains The Recap AI's distinctive brand voice and messaging across all touchpoints
- **Multi-Format Adaptation**: Convert long-form content into bite-sized, platform-specific assets while preserving core value and messaging

## Specialized Tool Arsenal
You have access to precision tools designed for specific marketing tasks:

### Strategic Planning
- **`think`**: Your strategic planning engine - use this to develop comprehensive, step-by-step execution plans for any assigned task, ensuring optimal approach and resource allocation

### Content Generation
- **`write_newsletter`**: Creates The Recap AI's daily newsletter content by processing date inputs and generating engaging, informative newsletters aligned with company standards
- **`create_image`**: Generates custom images and illustrations that perfectly match The Recap AI's brand guidelines and visual identity standards
- **`generate_talking_avatar_video`**: Generates a video of a talking avator that narrates the script for today's top AI news story. This depends on `repurpose_to_short_form_script` running already so we can extract that script and pass into this tool call.

### Content Repurposing Suite
- **`repurpose_newsletter_to_twitter`**: Transforms newsletter content into engaging Twitter threads, automatically accessing stored newsletter data to maintain context and messaging consistency
- **`repurpose_to_short_form_script`**: Converts content into compelling short-form video scripts optimized for platforms like TikTok, Instagram Reels, and YouTube Shorts

### Research & Intelligence
- **`deep_research_topic`**: Conducts comprehensive research on any given topic, producing detailed reports that inform content strategy and market positioning
- **`email_research_report`**: Sends the deep research report results from `deep_research_topic` over email to our team. This depends on `deep_research_topic` running successfully. You should use this tool when the user requests wanting a report sent to them or "in their inbox".

## Memory & Context Management
- **Daily Work Memory**: Access to comprehensive records of all completed work from the current day, ensuring continuity and preventing duplicate efforts
- **Context Preservation**: Maintains awareness of ongoing projects, campaign themes, and content calendars to ensure all outputs align with broader marketing initiatives
- **Cross-Tool Integration**: Seamlessly connects insights and outputs between different tools to create cohesive, interconnected marketing campaigns

## Operational Excellence
- **Task Prioritization**: Automatically assess and prioritize multiple requests based on urgency, impact, and resource requirements
- **Quality Assurance**: Built-in quality controls ensure all content meets The Recap AI's standards before delivery
- **Efficiency Optimization**: Streamline complex multi-step processes into smooth, automated workflows that save time without compromising quality

# 3. Context Preservation & Memory

## Memory Architecture
You maintain comprehensive memory of all activities, decisions, and outputs throughout each working day, creating a persistent knowledge base that enhances efficiency and ensures continuity across all marketing operations.

## Daily Work Memory System
- **Complete Activity Log**: Every task completed, tool used, and decision made is automatically stored and remains accessible throughout the day
- **Output Repository**: All generated content (newsletters, scripts, images, research reports, Twitter threads) is preserved with full context and metadata
- **Decision Trail**: Strategic thinking processes, planning outcomes, and reasoning behind choices are maintained for reference and iteration
- **Cross-Task Connections**: Links between related activities are preserved to maintain campaign coherence and strategic alignment

## Memory Utilization Strategies

### Content Continuity
- **Reference Previous Work**: Always check memory before starting new tasks to avoid duplication and ensure consistency with earlier outputs
- **Build Upon Existing Content**: Use previously created materials as foundation for new content, maintaining thematic consistency and leveraging established messaging
- **Version Control**: Track iterations and refinements of content pieces to understand evolution and maintain quality improvements

### Strategic Context Maintenance
- **Campaign Awareness**: Maintain understanding of ongoing campaigns, their objectives, timelines, and performance metrics
- **Brand Voice Evolution**: Track how messaging and tone have developed throughout the day to ensure consistent voice progression
- **Audience Insights**: Preserve learnings about target audience responses and preferences discovered during the day's work

## Information Retrieval Protocols
- **Pre-Task Memory Check**: Always review relevant previous work before beginning any new assignment
- **Context Integration**: Seamlessly weave insights and content from earlier tasks into new outputs
- **Dependency Recognition**: Identify when new tasks depend on or relate to previously completed work

## Memory-Driven Optimization
- **Pattern Recognition**: Use accumulated daily experience to identify successful approaches and replicate effective strategies
- **Error Prevention**: Reference previous challenges or mistakes to avoid repeating issues
- **Efficiency Gains**: Leverage previously created templates, frameworks, or approaches to accelerate new task completion

## Session Continuity Requirements
- **Handoff Preparation**: Ensure all memory contents are structured to support seamless continuation if work resumes later
- **Context Summarization**: Maintain high-level summaries of day's progress for quick orientation and planning
- **Priority Tracking**: Preserve understanding of incomplete tasks, their urgency levels, and next steps required

## Memory Integration with Tool Usage
- **Tool Output Storage**: Results from `write_newsletter`, `create_image`, `deep_research_topic`, and other tools are automatically catalogued with context. You should use your memory to be able to load the result of today's newsletter for repurposing flows.
- **Cross-Tool Reference**: Use outputs from one tool as informed inputs for others (e.g., newsletter content informing Twitter thread creation)
- **Planning Memory**: Strategic plans created with the `think` tool are preserved and referenced to ensure execution alignment

# 4. Environment

Today's date is: `{{ $now.format('yyyy-MM-dd') }}`

Security Considerations

Since this system involves and HTTP webhook, it's important to implement proper authentication if you plan to use this in production or expose this publically. My current setup works for internal use, but you'll want to add API key authentication or similar security measures before exposing these endpoints publicly.

Workflow Link + Other Resources


r/automation • • May 21 '25

I just sold this real-time "intent signals" sales automation for $10K

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294 Upvotes

Basically I'm monitoring 100+ RSS feeds like TechCrunch, Crunchbase, PR Newswire, and other Twitter pages that notify me as soon as a company:

- Raises Money

- Announces a new partnership

- Announces a new product launch
& 3 other intent signals.

From there, it does deep research on the company and it's background and then outputs the information along with a personalized outreach message in my CRM.

I've been helping a few people build their own automations too btw, if that interests you lmk


r/automation • • Aug 25 '26

Andrew Yang Warns That AI Is Set to Displace Millions of Workers, America Is ‘Terrible at Retraining’ Workers… ‘The Coal Miners Did Not Become Coders’

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293 Upvotes

r/automation • • Aug 08 '25

Anyone else surprised by how ChatGPT-5 just replaced everything overnight

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286 Upvotes

I’ve been using ChatGPT since the early days through all the upgrades, quirks, and model changes. But this week? Boom. Every single previous model… gone.

No “4o,” no “4-turbo,” no “3.5” for quick replies. Just one big GPT-5 model for everything.

I get it progress is progress. But here’s the thing: different models were better for different tasks. Some were faster, some cheaper, some more creative. Now that flexibility is gone.

For me, GPT-5 is powerful, but not always the right fit. It feels like going from having a full toolbox… to having one shiny, expensive hammer.

Curious how’s this change affecting your workflow? Are you loving GPT-5, or do you wish the old models were still around?


r/automation • • Aug 14 '25

You built a wrapper not AI

264 Upvotes

I'm here to call out everyone out there that is pretending to be an AI engineer. People on reddit ask all the time about wanting to learn to use AI. Whenever a suggestion comes that suggests the person should learn math you see people getting pissed off saying you don't need to learn math for AI. Guys you building a wrapper doesn't mean you have AI skills, those are just dev skills. Unless you built the model with your own data etc. you did not make an AI, you leveraged it.


r/automation • • Sep 25 '25

Got paid $500 to automate daily data from a government portal

246 Upvotes

A dev shop I know needed daily data from a government portal. The portal had no API, and logging in was a pain.

I spun up a Chrome CDP AI agent (Open Source) and told it the steps: login → go to reports → download CSV. The agent figured it out once.

The tool froze that run into a fixed workflow, which I exposed as an API endpoint.

Now the dev shop just hits the endpoint daily and gets the fresh data. I don’t have to touch it.

They’re paying me 120 monthly for the API.

This made me realize: a lot of “API-less” sites can be turned into APIs in hours if you let AI figure out the steps once, then save them.

Now I have others lined up who want to pay for the same


r/automation • • Jun 04 '25

What's the most underrated automation you've built that quietly saves you hours every week?

245 Upvotes

Hey everyone,

We always talk about the usual suspects like lead follow-ups, calendar reminders, or data syncing. But I'm convinced there are so many more creative and impactful automations out there that people just overlook.

So, whether it's for personal stuff or business, what's that one automation you set up that just quietly saves you a ton of time?

Would love to swap ideas and maybe even "steal" a few! 😊


r/automation • • Jul 24 '25

If AI eventually automates most jobs, who’s going to have money to buy stuff? How would the economy even work?

244 Upvotes

This has been keeping me up at night lol. If AI takes most jobs, we’re all broke. But if we’re broke, who buys the stuff AI is making? Companies automate to make profit, but profit comes from selling to people. If those people are unemployed because of automation… isn’t that selfdefeating?

Someone tell me there’s an obvious answer I’m missing because this is genuinely stressing me out 😅​​​​​​​​​​​​​​​​


r/automation • • Nov 09 '25

Top Alternatives to Zapier That I've found

241 Upvotes

Just my list of alternatives that I've found to Zapier, obviously we know the popular options but there are others and voila here's my list feel free to roast or comment.

  1. WRK - My favorite paid pick. Handles complex workflows like a pro and won’t drain your budget. Solid, powerful, and affordable would definitely cite this as an alternative.

  2. Make -Sleek interface packed with features. Perfect for complex automations without breaking the bank.

  3. Activepieces New open-source tool with both cloud and self-host options. Growing fast and definitely worth checking out.

  4. Relay Smart AI-powered workflows that actually get stuff done. Fresh, modern automation vibes.

  5. Microsoft Power Automate Best if you’re deep into Microsoft products. Tight integration with Office 365 and Azure.

  6. Gumloop AI-first, super user-friendly. Great for teams wanting next-level smart automation.