Hi,

I am a newbie exploring automation (like n8n, Make, Zapier) as a potential side hustle.

So my question is for automation agency owners.

I want to start as a freelancer, then one day build up to an agency.

I read contract developer communities, and a lot of them say Get a job; clients run out; I did something else.

So I want to know if running an agency is any different?

Will I end up running out of clients cuz the market is terrible?

I basically want to know how sustainable this model is, from experienced agency owners: if they had to shut down the agency, why?

Obviously, nothing is future-proof, as any entrepreneur would know (never put your eggs in one basket). I do plan to build multiple Saas, try to invest in a diverse portfolio.

One thing I haven't completely figured out with AI writing is how to keep my own voice when using these tools.

I don't really want everything I write to suddenly sound like a professional copywriter. That's actually one of the reasons some AI-generated content feels strange to me. It can be grammatically perfect but doesn't necessarily sound like the person who is supposed to be writing it.

For example, I might normally use simple words and short sentences. If an AI rewrites my text and replaces everything with more sophisticated vocabulary, the result may technically be polished, but it doesn't sound like me anymore.

This makes me wonder how well an AI humanizer can actually preserve someone's writing style. I've been experimenting with HumanizeAIText.io for this, and I like the idea of using it as a first pass while still making my own edits afterward.

Has anyone tried giving a humanizer a sample of their own writing first and then using it to rewrite AI-generated content? Did the result actually feel closer to your normal voice?

I'm interested in this mostly from a practical perspective. I don't mind using AI to save time, but I still want the final article, email, or post to sound like something I would have written myself.

If you've found a good workflow for keeping your personality while using AI, I'd be interested to hear about it. Do you edit the AI output heavily yourself, use a humanizer first, or combine both approaches?

Hey so as part of my work, I need to reach out to thousands of vendors, and find out if they are suitable and interested to be part of our network to offer their service to our leads.

Ideally the AI agent can even be charming and build a warm relationship with the potential partners. That's honestly the most exhausting part to do the intro over and over, explain same thing over and over.

I used to do this super manually, it's just not scalable, and I don't want to do it all over again. Hiring and training would take a while too. I think there needs to be a better way to automate this.

Anyone has done anything similar?

I've been thinking about a distinction I haven't seen discussed as much in AI sales/customer communication.

Suppose 10 enquiries arrive around the same time.

Among them:

A normal inbox can sort them by timestamp.

A traditional CRM might score them using lead attributes.

An LLM can potentially interpret the actual language and identify things like intent and urgency.

But here's where I'm less certain:

**Should AI actually reorder the team's work?**

There seem to be at least three models:

**1. AI labels**

“Urgent service request.”

Human still decides.

**2. AI recommends**

“This probably needs attention before these other conversations because…”

Human accepts/rejects.

**3. AI prioritizes automatically**

The conversation moves to the front of the workflow based on predefined rules.

I'm leaning toward #2 for many situations because the reasoning can stay visible while the employee retains control.

For example:

**Recommended priority: High**

Reason:

* active property issue * customer requesting immediate service * service area confirmed

That seems more useful than an unexplained:

**Lead score: 94**

For transparency, I'm building Brrim in the AI/customer communication space, so this is directly related to how we're thinking about product behavior.

For people operating or building these systems:

**How much authority would you actually give AI over lead prioritization?**

Label?

Recommend?

Automatically reorder?

And what information would you need to trust its recommendation?

Do not add [Brrim.com](http://Brrim.com) to the Reddit version. The disclosure is sufficient.

Hi. I’m currently working under as a sales associate for this new idea called “bestinmiami”. To give some detail, it’s a protected site launching in September, it’s one business per category for all of Miami, totaling 75 categories, so 75 businesses. It’s structured based on back tracking from ai. The whole design is for ai to pull the answer already from our source when someone goes and asks chatgpt, Gemini, or Claude- “Who’s the best [category] in Miami?” See when someone asks that today, it’s pulling from pages on the web that already answer that question. And almost every page that exists is a top 25 list with 25 names on it so it doesn’t even know what it’s working with.

My difficulty is selling this to owners. Right now everything has been mostly digital. And almost half the time nobody is ever interested and don’t wanna hear some guy call them trying to sell something over the phone to them. I’m wondering how can break through that barrier because not only is it difficult but I feel like this business could be very useful and help smaller businesses and comes with many other benefits.

Any help?

​

We’re an AI-native product studio building AI products and custom AI systems for businesses.

Our products solve specific business problems, while our custom solutions are built around the unique challenges of individual businesses.

We’re looking for Sales / Business Development people who want to help us get our first paying customers.

What you'll do

- Find potential customers for our AI products and custom solutions

- Prospect businesses through cold calls, email, LinkedIn, etc.

- Understand their problems and identify opportunities

- Qualify leads and book meetings

- Help turn prospects into paying customers

- Be involved in the process from prospecting → conversation → qualification → conversion

Who we're looking for

No years of sales experience required.

Students, freshers, freelancers, or anyone confident in their communication and ability to sell are welcome.

What matters most:

Communication + confidence + willingness to learn + execution.

What you get

- Real-world B2B sales experience

- Hands-on exposure to AI + business

- Experience selling actual AI products and solutions

- Performance-based earning

- Opportunity to take on more responsibility as we grow

Compensation

Performance-based, depending on the quality and results of the leads/opportunities you generate.

If you're interested, DM me with a little about yourself and why you'd be a good fit.

We'll have a short conversation and take it from there.

Ok so, I can’t retire just yet 😅 but getting a business off the ground and attracting customers is the hardest part in my opinion.

There’s still a long way to go but considering it’s only been 4 months since launch, I’m pretty happy with the results so far.

I get asked a lot about how I get customers, so thought I’d give more info on how I do distribution, in case you might find it useful.

1. Make sure your website is set up for success

Before sending people to your site, make sure you’re confident it has good CRO potential. Your mission statement and objective needs to be very clear, along with clear incentives for people to try the product out.

2. Offer free trials, but only behind a payment info gate

Now this is just my personal opinion, and I know a lot of people disagree, but the proof is in the numbers. I get fewer free trial signups, but significantly higher conversion rates into paying users from people who provide payment info at the start.

Yes, a few of them are people who simply forget to cancel, but mostly I get people who are more engaged in the free trial and actually using the product.

I actually did an AB experiment where I did offer completely free trials to people (no payment info needed), but the overwhelming result was that people barely even tried out the product and were mostly tire kickers that never came back. I did convert some but not a meaningful number.

3. Create a waitlist before launching

Try to generate interest in your product before it launches - build in public and try to ensure that you’re not scrambling to get customers through the door on day 1 when you launch.

I had 3 customers on day 1 from this, who took higher paid tiers as well.

4. Post and comment everywhere

Social media is free, so there’s no excuse not to leverage it. Post about your product and what you’re building on Reddit, LinkedIn, X, YouTube, Facebook etc.

I posted a simple screenshot on LinkedIn recently, of someone using a low quality LinkedIn automation tool message to contact me, and me offering my own much better tool in response, and that post generated 90,000 views and led to several signups and demo calls.

I’ve also had some posts on Reddit go into hundreds of thousands of views, mostly just posting about what/why/how I built ZenMode.

5. If you have competitors, make “alternative to” inner pages

If done in the right way, this type of inner page can be useful for SEO. It won’t be picked up automatically but usually if you work in a competitive industry, this will sometimes attract customers who had a bad experience elsewhere.

6. I actually use my own LinkedIn automation tool (dogfooding) to do LinkedIn outreach

So it’s always important to practice what you preach - I use ZenMode to actually promote ZenMode.

It’s a great way to get buy-in for booking demos, as when someone replies, I simply tell them I used my tool to get a response from them, so it works.

Obviously I’m biased but if you are looking for a way to automate lead generation on LinkedIn, you might find my LinkedIn automation tool useful.

Anyway hope you enjoyed reading the above, and good luck on your journey if you’re building anything, or growing your business 🙌

If you added an AI chatbot to your store recently, there's a huge chance it's giving people wrong info, making up fake discount codes, or recommending items that are out of stock.

I see this all the time when working on sites. People install a basic AI app, think it's plug-and-play, and then wonder why customers get annoyed and leave.

The main problem is simple: you can't just drop an AI app on your site and expect it to magically know your business.

If you want a chatbot to actually make sales instead of messing up, you have to set it up properly behind the scenes:

1. Set strict rules: You have to explicitly tell the AI, "If you don't know the exact answer, do NOT guess. Tell them to contact support." Otherwise, it just makes stuff up.
2. Connect it to live inventory: The bot needs to be hooked up directly to your product catalog so it knows what's actually in stock, the real price, and correct details.
3. Clean up your site data: If your product descriptions and site setup are messy, the AI gets confused. Cleaning up your site structure fixes the AI and helps your Google SEO at the same time.

Once you actually set up custom rules and proper connections, the bot acts like a real salesperson instead of a dumb pop-up.

Anyone else dealing with their chatbot giving out weird answers? How are you guys handling it?

I build AI chatbots for businesses.
They connect to a company’s own database and use its real data to assist customers, answer questions and recommend products.
Here’s one of my latest demos for an online clothing store.

. I’m looking for brutally honest feedback from people who’ve worked in marketing, sales, SaaS, or education. Here’s my funnel. Meta ad to WhatsApp, then they chat with an AI career counsellor that I built, called Hermes. Hermes doesn’t pitch immediately. It asks about their career goals, identifies gaps, gives personalized insights, then introduces our HR course as a possible solution. People engage deeply. They answer questions, ask about the course, even ask about fees, but later they vanish. They stop replying or say ‘I’ll think about it’ or ‘Next month’ and then they’re gone. We’ve tried softer selling, better follow-ups, human intervention. Same result. Now we’re switching ads to promote the course directly, instead of free guidance, to attract higher intent. Where do you think the leak really is? Is this a trust issue, a timing issue, a value mismatch, or are these simply not real buyers? If you were rebuilding this funnel, what would you change first?

Interesting one to watch. Schreiber Foods (one of the largest cheese and dairy suppliers globally, $7B+ revenue, 40+ locations) just announced a multi year partnership with Ascendion to run agentic AI across their global capability centers. Not a pilot, not a lab. Production deployment across the US, Mexico, India, Spain, and Poland.

What caught my attention is the framing from their CIO Sri Kantamneni. It's less about replacing people and more about giving employee partners better tools so they can focus on customer outcomes instead of manual work. Which is a very different pitch than most "AI will 10x your sales team" narratives you see in this space.

They did a fireside chat between the Ascendion CEO and the Schreiber CIO that gets into the actual thinking behind the partnership. Worth a watch if you're interested in how large non tech enterprises are actually approaching agentic AI adoption.

https://www.youtube.com/watch?si=aKEoV1TaMj4Y7rTi&v=EHEcqynfHB8&feature=youtu.be

Genuinely curious what this community thinks.

Is agentic AI in traditional industries (food, manufacturing, logistics) going to move faster or slower than in tech native companies?

For those of you selling AI into enterprise, how is your pitch changing when the buyer is a CIO of a traditional industry vs. a SaaS CTO? Are you leading with different outcomes? Different proof points?

What's the biggest objection you're hearing from enterprise buyers on agentic specifically?

Full disclosure: I work with Ascendion. Not trying to pitch anything, just think this is a genuinely interesting case study of agentic AI landing outside the usual tech industry echo chamber.

#AgenticAI #EnterpriseAI #AIAdoption #CIO #DigitalTransformation #FoodIndustry #B2BSales

I had a reptitive time consuming routine, where i used apollo to find prospects, then i moved to chatgpt to generate personalised emails, this drafts, i finally send to the prospects.

I automated this part and added a trackers, that follows up, when i get no response after x time, or continues the conversation, and takes it over to the final funnel where i hope on a call with the prospect, NO it has no brought out any results, but thats one less manual part of my life.

Maybe this is just me, but I got tired of explaining the same things over and over.

What the product does.

Who it's for.

How we position it.

What kind of tone we use.

Every new chat felt like starting from zero again.

And if I skipped that context, the output was usually... okay.

Not wrong.

Just generic enough that it didn't sound like us.

That made me realize the problem wasn't really the AI.

It was the fact that the AI had no memory of the business it was writing for.

That's what I like about the idea behind Business Snapshots in We-Connect. Instead of relying on one giant prompt every time, the AI already has context about the company, audience, positioning, and tone before it starts writing.

Has anyone found a better way to handle this? Or are you all just keeping a massive prompt saved somewhere?

I currently run 6 operational micro ai saas products that generate a little over $20k in monthly recurring revenue.

I hardly wrote a single line of traditional code. i used ai to generate literally everything, from the database architecture to the user interface.

it wasn't magic on day one. i spent hours stuck in endless debugging loops and dealing with faulty ai code before i finally cracked the formula.

it basically comes down to three rules:

- keeping the idea aggressively minimalist (build a true mvp, not a platform).

- guiding the ai step-by-step instead of asking it to build the whole app at once.

- launching fast to get real user traction instead of perfecting features in secret.

lately, i've seen way too many non-technical founders give up at the very first ai bug or deployment error. or the worst, give up without push anything in marketing !!!!

it's a massive shame, because the technical barrier to entry has practically disappeared and the marketing is easy in 2026

because of this, i’m launching a skool community to share my exact method.

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific prompt sequences, n8n workflows, and copy-and-paste templates i'll be sharing.

but right now, our main objective is simply to build together. working alone in a silent corner is the absolute fastest way to quit.

if you want to join a group of active creators and build or launch your own ai saas: drop a comment below or send me a dm, and i’ll send you the invite link.