u/ExperienceDeep5869

Over the last year, I've spent hundreds of hours building, shipping, breaking things, talking to users, and fixing the same mistakes over and over.

If I had to start again tomorrow, this is what I'd do differently.

• Build for one specific problem, not an entire market. Narrow beats broad almost every time.
• Talk to potential users before writing code. A 20-minute conversation can save weeks of development.
• Your first version should make you slightly embarrassed. Shipping beats polishing.
• Most feature requests are actually symptoms. Figure out the underlying problem before building anything.
• People don't buy AI. They buy saved time, saved money, or better results.
• If users aren't getting value within the first few minutes, your onboarding needs work—not your marketing.
• The fastest way to improve a product is to watch someone use it without helping them.
• Don't assume silence means satisfaction. The happiest users rarely tell you what's broken unless you ask.
• Organic content compounds. One useful Reddit post or LinkedIn post can outperform weeks of cold outreach.
• Build analytics from day one. The numbers usually tell a different story than your intuition.
• Charge sooner than feels comfortable. Paying customers give far better feedback than free users.
• Don't automate a broken workflow. Fix the process first, then automate it.
• Most founders overestimate how much people care about features and underestimate how much they care about simplicity.
• Support isn't a cost in the early days—it's product research.
• Consistency beats intensity. Shipping small improvements every week is better than disappearing for three months to build the "perfect" feature.

The biggest surprise for me wasn't how hard building the product was.

It was realizing that building is only half the job. Understanding users, communicating clearly, and earning trust are what actually determine whether people stick around.

Out of curiosity, what's one lesson you learned the hard way while building a product, startup, or business?

P.S. Since people usually ask, the product I've been building is Leadbox—an AI sales agent that's trained on your business to qualify leads, handle objections, and book meetings. Most of the lessons above came from building it and talking to the people who use it every day.

The people I know who are doing genuinely impressive work rarely post about it.

Meanwhile, my feed is full of "I almost gave up..." stories, AI-generated motivational posts, humblebrags, and the same career advice repeated in different words.

I'm not even saying people shouldn't build a personal brand. It clearly creates opportunities.

But sometimes it feels like visibility has become its own form of credibility.

I've caught myself assuming someone is an expert simply because they post consistently, only to realize later that someone much more experienced has barely touched LinkedIn in months.

It makes me wonder how much we're rewarding people for communicating success versus actually creating it.

Maybe that's just how every social platform evolves.

Or maybe I'm spending too much time in my feed.

Has anyone else noticed this shift, or am I just seeing a very weird corner of LinkedIn?

A few months ago I was digging through our CRM trying to figure out why so many seemingly qualified inbound leads never turned into real conversations.

The surprising part wasn't the quality of the leads.

It was the timing.

People were filling out forms late at night, during lunch breaks, or on weekends. By the time someone from the team responded, many had already scheduled a demo elsewhere, solved the problem another way, or simply lost momentum.

It made me realize we've treated inbound as if every lead patiently waits in a queue.

Most don't.

When someone reaches out, they're usually in the middle of researching several options at once. The first meaningful interaction often shapes the rest of the buying process, whether it's with you or someone else.

That's why I'm starting to think the biggest impact of AI in sales isn't replacing SDRs.

It's replacing the empty gap between a prospect raising their hand and hearing back from someone.

We've been experimenting with an AI sales agent that can answer common questions, qualify leads based on our criteria, handle straightforward objections, and book meetings whenever someone reaches out. It doesn't replace the conversations that require judgment or relationship-building, but it keeps interested prospects from hitting a dead end while the team is offline.

I'm not convinced every company needs this approach, and there are definitely situations where a human-first response is better.

I just think we're entering a period where "we'll get back to you tomorrow" is becoming less acceptable than we realize.

Curious whether others are seeing the same thing.

Are you finding that lead quality is the problem—or that response time is becoming the real competitive advantage?

Been watching this space pretty closely over the last few months, and one thing keeps standing out.

A lot of small businesses want AI helping with sales, but most of them don't actually want to hire developers or spend weeks connecting APIs and building custom workflows.

They just want something that can qualify leads, answer common questions, and book meetings without adding another full-time employee.

That shift feels a lot like what happened with websites years ago.

Businesses didn't suddenly want HTML.

They wanted a website.

Now they don't necessarily want "AI."

They want better sales outcomes.

I think there's a pretty interesting opportunity for freelancers here.

The playbook seems surprisingly straightforward:

• Find businesses that already receive inbound leads.
• Identify repetitive sales conversations.
• Build a simple AI sales agent around that workflow.
• Charge a setup fee plus ongoing management.
• Repeat with the next client.

The interesting part is that you don't have to build everything from scratch anymore.

There are already tools for different parts of the workflow.

Apollo for prospecting.

Clay for enrichment.

Instantly for outreach.

HubSpot for CRM.

Platforms like LeadBox make it much easier to build and deploy AI sales agents without spending weeks on the technical side.

The real value isn't the AI itself.

It's understanding the client's sales process well enough to automate the parts that actually slow them down.

I wouldn't be surprised if "AI sales agent freelancer" becomes one of the more common service businesses over the next couple of years, similar to how Shopify developers and no-code consultants grew as those markets matured.

Curious if anyone here is already offering AI sales agent services.

Are clients asking for AI specifically, or are they simply looking for a better way to generate qualified leads and book more meetings?

Been watching this space pretty closely over the last few months, and one thing keeps standing out.

A lot of small businesses want AI helping with sales, but most of them don't actually want to hire developers or spend weeks connecting APIs and building custom workflows.

They just want something that can qualify leads, answer common questions, and book meetings without adding another full-time employee.

That shift feels a lot like what happened with websites years ago.

Businesses didn't suddenly want HTML.

They wanted a website.

Now they don't necessarily want "AI."

They want better sales outcomes.

I think there's a pretty interesting opportunity for freelancers here.

The playbook seems surprisingly straightforward:

• Find businesses that already receive inbound leads.
• Identify repetitive sales conversations.
• Build a simple AI sales agent around that workflow.
• Charge a setup fee plus ongoing management.
• Repeat with the next client.

The interesting part is that you don't have to build everything from scratch anymore.

There are already tools for different parts of the workflow.

Apollo for prospecting.

Clay for enrichment.

Instantly for outreach.

HubSpot for CRM.

Platforms like LeadBox make it much easier to build and deploy AI sales agents without spending weeks on the technical side.

The real value isn't the AI itself.

It's understanding the client's sales process well enough to automate the parts that actually slow them down.

I wouldn't be surprised if "AI sales agent freelancer" becomes one of the more common service businesses over the next couple of years, similar to how Shopify developers and no-code consultants grew as those markets matured.

Curious if anyone here is already offering AI sales agent services.

Are clients asking for AI specifically, or are they simply looking for a better way to generate qualified leads and book more meetings?

Over the last few months, I've been talking to founders, agencies, and service businesses while building Leadbox, a platform for creating AI sales agents.

I expected most conversations to be about models.

GPT vs Claude.

Prompt engineering.

Agent workflows.

None of that came up nearly as much as I expected.

Instead, almost every business asked some variation of the same questions:

• How will this bring me better leads?
• How many meetings can it realistically book?
• Can my team review what it's doing?
• How do I know the outreach actually makes sense?
• What happens when it gets something wrong?

That completely changed the way I think about AI products.

As builders, it's easy to obsess over making the AI smarter.

Businesses usually care about something much simpler.

Can it save my team time?

Can I trust it?

Can I understand why it made a recommendation?

I've spent a lot of time looking at tools across the sales space—Apollo, Clay, Instantly, Lemlist, HubSpot, and others.

They all solve different parts of the sales workflow really well.

The biggest lesson for me wasn't that one tool has the "best AI."

It was that businesses don't buy AI.

They buy predictable outcomes.

If your workflow helps them consistently find better prospects, personalize outreach, and book more qualified meetings, they don't spend much time asking which model is running behind the scenes.

Ironically, the more I stopped leading with "AI" and started talking about sales outcomes, the better the conversations became.

I'm curious whether other founders or consultants building AI products have noticed the same thing.

Have your customers cared more about the technology itself, or about the business result it produces?

I've been talking to founders, agencies, and small business owners over the past few months while building an AI sales agent.

I assumed the conversation would mostly be about AI models.

It wasn't.

Almost nobody asked which model we used.

Nobody cared whether it was GPT, Claude, Gemini, or something else.

Every conversation eventually came back to the same question:

"Will this actually help us get more qualified leads and booked meetings?"

That completely changed how I think about building.

At first, I kept focusing on adding "AI features."

Longer prompts.

Better personalization.

More automation.

Smarter reasoning.

The product kept getting more impressive technically.

But every demo ended with practical questions instead.

• Can I control who gets contacted?
• How do I know the leads are actually relevant?
• Can my team review things before messages go out?
• How much time does this actually save?
• What happens if the AI gets something wrong?

Those questions had almost nothing to do with AI.

They were about trust and business outcomes.

That pushed me to simplify a lot.

Instead of trying to automate every single decision, we started focusing on making the workflow transparent.

The AI can research companies, qualify leads, and draft outreach, but the business still understands what's happening instead of feeling like a black box.

Ironically, some of the biggest improvements didn't come from adding more AI.

They came from improving the workflow around it.

Clearer lead qualification.

Better review steps.

Simpler dashboards.

Cleaner explanations.

I've also spent time looking at how other products solve similar problems.

Tools like Apollo, Clay, Instantly, Lemlist, and others all do certain parts of the workflow really well.

Building Closer AI made me realize there isn't one "magic AI feature" that wins.

It's usually the combination of good data, a reliable workflow, and software people actually trust enough to use every day.

The AI is just one piece of that system.

The more founders I talk to, the more I think we're entering a phase where businesses care less about who has the smartest AI and more about who solves a real business problem with the least amount of friction.

Maybe that's obvious to everyone else.

It definitely wasn't obvious to me when I started building.

Curious what everyone else has experienced.

If you've built or adopted AI tools in your business, what mattered more in the end—the intelligence of the AI itself, or how well it fit into your existing workflow?

I've been building Closer AI, an AI sales agent for service businesses.

The idea is simple: instead of hiring another setter, businesses can train an AI on their sales process so it can qualify leads, answer common objections, and book calls 24/7.

I'm happy with where the product is, but now I've hit the problem every founder seems to talk about...

How do you get the first users when nobody knows you exist?

Right now I'm considering:

• Cold outreach to businesses that already run ads
• Offering free pilots in exchange for honest feedback
• Creating content around sales and AI
• Reaching out to agencies that already serve my target customers

What I don't want to do is spend months shouting into the void or burn money on ads before I've validated the positioning.

For those of you who've already crossed this stage:

• Where did your first 5–10 users actually come from?
• Was cold outreach worth it?
• Would you focus on one niche first or stay broad until you get traction?

I'd really appreciate hearing what worked (or didn't) from your own experience.