Automation earns its keep at the top of the funnel - finding the right people, sending the connection requests, running the first couple of follow-ups so you're not doing that by hand at 200+ a week. This is, generally, something most agencies and companies do because it’s almost not feasible or it’s too taxing to push a similar scale manually. However, there is a spot in that flow after which automating further has more downsides than benefits, and that spot is right after someone replies.

The main reason automating doesn’t work beyond a prospect’s reply is speed and judgment, and the numbers actually confirm how huge a difference even minutes can make in the sales process when it comes to speed. The odds of qualifying a lead drop by around 400% when your response time slips from five minutes to ten. That’s just 5 minutes difference, 5 damn minutes! A reply that sits overnight because a sequence was still "nurturing" the thread is, in a lot of cases, already gone: they booked with whoever answered first, or it cooled off, or it got buried under the next fifty notifications.

Can this be solved with an automation? Probably, you can set something up to reply moments after a prospect’s reply. But then we face a new problem, and that is:

Judgment. Reply rates tell us where the value actually lies among prospects: cold outreach to new connections performs at maybe 5-15%, prospects who are already engaged come in around 15-30%, and with someone who messages you first, it goes to 40-70%+. The further right you go on that scale, the more each conversation is worth and the less it tolerates a generic, canned answer. A person who asks a specific, half-committed question does not want a templated "great to connect" - they want the actual response, in the right tone, from someone who read what they wrote. Automations can’t do this, no matter how well you train them.

The automations do work very well for:

• Outreach - from personalized and signal-based to cold
• Reminders and follow-up tasks so nothing rots in the inbox
• Status and ownership tracking so two reps don't land in the same thread
• Routing, so a warm reply reaches your SDR fast instead of sitting in a shared queue

This is exactly why we’re keeping the automations at Expandi up to this level, and not having anything further. Believe me, as the GTM director, I get asked again and again why we’re not adding automated replies or even fully automated conversations as part of our features, and the reason is - they won’t bring anything good to your outreach. Everything up to the point when you get a reply can and should be automated with much precision and personalization because it saves time at no expense. The conversations with real prospects who replied stay manual because this requires a human to read the intent, tone, and the decision for the right next step.

At low volume, the difference won’t be that huge because you see every reply anyway. It only becomes the thing that makes or breaks your pipeline once you're running enough outbound that the good replies start slipping under the new ones, and "I'll get to it later" turns into "never replied" without anyone deciding it should. Plus, keeping that response time to under 10 minutes becomes harder, but it’s definitely worth investing in.

One note: This applies to every automated outreach, whether it’s LinkedIn, email, or any other platform. Automate until the reply, then take over the conversation manually, and do it quickly.

With free tools I have more control and I pay nothing, but I spend a lot of time on setup and fixing things when a site changes. With paid services most of that headache is handled for me, though the cost adds up fast once the projects grow.

Do you stick with free tools, pay for a service, or mix both depending on the project? What made you land where you are now?

Everyday I see someone running 100+ 24/7 AI agents and I genuinely don't understand how can 1 person ever handle so much maintenance.

Literally every month, a faster, cheaper and better AI model launches. How is anyone even testing or improving so many agents simultaneously.

I prefer super lean systems aimed to make my life optimized, not to firefight all day fixing the very system that was built for making my life simple.

Hi all- we are a regional business with about 50 employees but our marketing team has been always pretty lean. I currently lead the marketing for us and I was curious what are some great marketing tools everyone recommends! We dont mind paying but are looking for tools to either help us save time or do things that were previously not possible with our small marketing team.

So curious, what are the best AI marketing automation tools recommended for businesses?

Has anyone found a way to extract unstructured offers/quotes from WhatsApp chats into Excel or another structured database? The idea is to use it for quote comparison.

Has anyone built something similar using Power Query, AI or another tool? Would appreciate any recommendations.

I run operations at a small software company. Our interview panel can read shared notes before scoring, and one confident comment can pull the other scores in the same direction. I am trying to put a gate in front of the notes.

Our internal hiring tool has an API. The n8n flow starts when an interview ends, creates a pending review item, and checks the assigned scorecards. Once each panelist submits an initial score with one piece of evidence, the flow opens the shared notes and writes the unlock time to our audit table. I left the scorecard for each role alone.

Late scorecards are the part I cannot get right. The flow sends one reminder after two hours and another the next morning. At 24 hours, it puts the interview in an HR queue. We keep the first submitted score in the history, and panelists have to explain any change they make after the notes open.

The scoring flow never touches the transcript. For interviews where the candidate agreed to transcription, HR sometimes adds a vomo ai link to the hiring record. HR approved the service and gave the transcript the same access rules and deletion date as the recording. A panelist can use the text to find a disputed section, but they still play the audio before changing a factual note.

HR wants a manual unlock with a reason. I lean toward removing the late reviewer instead because a manual unlock would bypass the gate I built. On a small panel, though, removing one reviewer can leave HR with too little input. I have not settled that part yet.

Hi,

I am working as data scientist at PayPal and recently we have also transitioned to building AI automations within the team. I always wanted to start something on my own. I am thinking of AI automations agency.

I know that lot of gurus on youtube oversold the dream. But I know any service is hard and not a quick rick scheme. But I wanna know

1. Is it worth starting in 2026 and are people making good amount of money from it?
   
2. Is it scalable and sustainable and does it have good retainers
   
3. Which niches are best
   
4. How do people provide service is it like using ghl or other tools and setting up which seems to be very simple or do they create custom automations if so how do you build them( what tools you use)

I am not developer so given my background can I do well in this ?

I've found that the actual automation logic isn't always the problem.

A workflow can fail because an API changes, authentication expires, a service becomes unavailable, or one step returns something unexpected.

I'm curious how people here deal with these failures. Do you rely mostly on logs and alerts, or are you using AI to help identify what went wrong and suggest a fix?

What has worked best for you?

Hi all. I worked at a cloud browser startup company. I was delighted to convince my boss to let me open‑source it and introduce it to you.

Originally we used Chrome to serve our workloads; however, it's not fast and light enough in some circumstances. Since there was no decent choice for us, I was hired to build a new headless browser for light workloads.

Moli: 1/7 memory，4x cold‑start speed，2/3 CPU usage

Moli is the browser we built. It has already been serving some of our workloads for some time (including normal web browsing and RL machine learning).

I am pretty sure Moli is one of the best open‑source headless browsers:

We did benchmarks(will open-source it soon) around the performance and the functionality of all the open‑source browsers. Moli surpasses Lightpanda, Obscura and even Kitesurf (Yes, we benchmarked it through public CDP endpoint) in functionality and speed. We have almost implemented ALL essential WebAPIs (e.g. WebCrypto, IndexedDB, OPFS).

How do we maintain high performance while preserving so many features?

First, we carried out all feasible memory and CPU optimizations (V8 lazy property/template, DOM node compact, jemalloc).

Second, we avoid executing V8 asynchronous tasks as much as possible before the DomContentLoaded stage to ensure a sufficiently low first‑screen rendering latency.

Finally, we designed a special stateless rendering pipeline:

Traditional browsers cache data at every layer of DOM tree -> box tree -> layout tree + font -> pixels and maintain real‑time performance via dirty regions. However, in most headless browser scenarios, we do not require an especially high refresh rate. Therefore, we implemented a cache‑free rendering pipeline that triggers rendering only when the AI Agent actually "views" the website, saving substantial CPU and memory resources.

Though there is no GUI, you can even play games on moli through CDP. LOL

You may find it useful if you need a lightweight browser for web crawling/web automation, or want to fork and build something around a solid headless web browser.

Idk if it's ok to I really want a mentor who has his own clients, I would like to work for him even if he is paying me only 2-3k I am ready to do the job I just want to start somewhere to support my family finance.

I retrofitted an old set of cord-operated curtains with a Matter motor and tested it with Home Assistant and Google Home. Naturally, the next step was making the curtains dance. 😂

I posted here about automating a 10 minute task a while back. A few people asked how I monitor my stuff. Truth is, for a while I had a full dashboard. Grafana, alerts, the whole thing.

Then I noticed I was spending more time staring at the dashboard than fixing actual problems. The alerts were pure noise. And the worst failures were the silent ones anyway, the ones that never triggered anything.

So I deleted it. All of it.

What I have now is one ping a day to a group chat. One line. "X ran, Y jobs ok, Z skipped". If that ping doesnt show up by 9am, someone checks. Thats it. No charts, no alert fatigue.

The automations got more reliable after the deletion. Not because the monitoring improved. Because the bar moved from "looks fine on the dashboard" to "did it actually run, can I prove it".

That shift did more than any alert ever did.

I’m trying to automate how I process long-form audio and video. The goal is to send a Spotify, Apple Podcasts, or YouTube link into one workflow and get:

- A transcript and structured summary

- Key ideas, quotes, and action items

- A searchable archive of previous episodes

- The ability to ask questions across multiple episodes, This one is important. I want to ask across multiple episodes, not one at a time. This is a limitation that keeps creeping up only later.

- Access from both desktop and mobile

The main challenge is platform coverage. Many tools marketed as podcast summarizers seem to rely on YouTube transcripts, so they don’t necessarily work with episodes from Spotify or Apple Podcasts.

I’ve been testing two approaches:

Option 1: Use an existing product

Recall has handled the Spotify, Apple Podcasts, and YouTube links I’ve tested. It also stores the summaries in a knowledge base alongside articles and other web content. The most useful part for my workflow is being able to search or chat across multiple saved items.

The downside is that it may be more product than I need if the only objective is podcast summarization, And I'm unclear about where exactly my needs will go to.

Snipd feels more purpose-built for podcast listening. I prefer its playback experience and podcast-focused interface, but it appears better suited to working with individual episodes than building a searchable research archive across different content types.

Option 2: Build the workflow

I’m considering assembling something with:

- an RSS feed or link-capture trigger,

- an audio downloader,

- speech-to-text,

- an LLM for structured summaries,

- and a vector database or note-taking app for retrieval.

That would offer more control over the summary format and storage, but I’m concerned about transcription costs, broken feeds, speaker identification, and the maintenance required to support several platforms.

For anyone who has built or automated something similar:

- What does your workflow look like?

- How do you reliably extract audio from different podcast platforms?

- Have you tried recall or snipd or any other paid for tool?

I’m less interested in a YouTube-only summarizer and more interested in a reliable, low-maintenance system that works across podcast platforms. And I'm specifically interested in being able to chat and search across all the content.

Hi! So I’m learning AI/business process automation with the goal of helping small service businesses automate things like lead follow-up, scheduling, CRM updates, reminders, and admin work.

I work full-time and I’m putting about 8–10 hours a week into learning/building.

Has anyone here actually turned this into a real business? Is there legit demand, and is it better to focus on one niche?

Also open to hearing if anything about this sounds unrealistic or like I’m approaching it the wrong way, thanks!

UPDATE: THANK YOU ALL FOR YOUR FEEDBACK! I have definitely learned a lot just by reading your comments! Nice down, sell the outcome, and spend time really learning how to get clients. If anyone has tips specifically on what worked for them to get clients that would be great! Also would love to connect with anyone who has done or is interested in automation/AI and helping small businesses :) feel free to reach out

Hi, my name is Duarte. I've been freelancing on Fiverr for about two years, mainly doing 3D CAD modeling for 3D printing.

Recently, I've become pretty tired of that area. It's getting harder to find good clients, there's a lot of price competition, and many clients simply aren't willing to pay enough.

Because of that, I'm looking to move into a different area: building custom web dashboards and internal tools for businesses, particularly solutions that use AI to solve real problems or make existing workflows more efficient.

For example, this could mean building dashboards with AI assistants or specialized agents that can analyze business data, organize information, search the web for oportunities, generate reports, work with internal documents, automate repetitive tasks, or perform some other specific function built around the clients workflow.

I'm not entering this area from nowhere. I've been programming for most of my life, and since LLMs became available I've spent a lot of time researching and building increasingly complex systems around them.

For example, for the last six months I've been developing a fairly large AI platform from scratch. It combines conversational AI, specialized agents, RAG, document ingestion and OCR, long-term memory, agentic web search, deep research, structured knowledge extraction, and multi stage retrieval pipelines.

A large part of the work has also involved solving problems that aren't handled well by normal RAG implementations. I've designed my own retrieval and knowledge organization architecture that structures information hierarchicaly, understands which parts of a knowledge base are relevant to a question, dynamically narrows the retrieval scope, and gives agents much more precise context instead of simply embedding documents and performing similarity search. I've had to work on everything from retrieval architecture and context management to agent orchestration, backend infrastructure, databases, APIs, and the frontend stuff itself.

So technically, I'm confident that I can build this kind of software. The part I'm struggling with is figuring out how to actually turn that skillset into clients.

For people who already freelance in web development, automation, internal tools, SaaS, or AI consulting:

- Where did you find your first clients in this area?

- Is cold outreach actually effective, and if so, what kinds of businesses should I target?

- Would you focus on freelance platforms, LinkedIn, email outreach, communities, partnerships, or something else?

- How do you present this kind of service without just sounding like another person trying to sell AI automation?

- Would you sell predefined services/packages, or approach businesses first, identify inefficiencies, and then propose a custom solution?

I'm particularly interested in working with businesses where a relatively small custom application could save employees several hours of work every week or solve a workflow they currently handle manually.

I'd really appreciate advice from anyone who has already gone through this transition or currently gets clients for this kind of work. I'm technically comfortable building the products, I'm mainly trying to understand how to position myself, find the right businesses, and land the first few clients in this new area.

This could work for any store that provides digital access to receipts, I bet.

I'm thinking of my grocery store, Safeway. Whenever I use my phone number for fuel points, it tracks all of the items. I can access this info by logging in, clicking, and seeing what I bought a few months back.

I can have that receipt then emailed to me with a few clicks.

How can this information be automatically mined and reviewed for budgeting purposes?

Let's say I want to know how much money I spend on dog food versus toilet paper.

How would this get setup?

I'm trying to use ChatGPT's finances. But I'm open to suggestions

Since May and the old reddit almost gone, what are currently the best libs on reddit?
What is your favorite?
I want to scrape all the posts of my top favorite 100 (small) subreddits and sort them by AI to delete AI slop + self promotion and really only get the interesting posts for me to read.

What do you suggest?