I spend a lot more time on PH at the moment to see what indepedent makers are spending their time on. I've noticed some patterns and also want to share a little bit about my journey at South Park Commons. Most startup stories begin at zero when there s already a team, an idea, maybe even a prototype. But at South Park Commons (SPC), the philosophy is different: people gather in the -1 to 0 stage. That liminal space where you don t yet know what you re building or even if you should build at all. It s a place for exploration, experimentation, and being brutally honest about what s working and what s not.

A hallmark of SPC is how often industry leaders drop by to share what they ve learned in the wild. Recently, I was in a small chat with Tyler Payne former Google and LinkedIn AI lead, startup builder, who has spent the last decade helping teams actually ship real-world ML systems. We're always talking about what's being launched at SPC.

We put off refactoring for way too long last year because we were so focused on launching new features every single week.

Eventually the codebase got so fragile that fixing one simple bug broke three other things in the app. Taking a few uninterrupted days to clean the foundation completely changed our speed going forward.

It really is the best investment you can make even though it hurts to look at an empty changelog at the end of the week. How do you decide when the tech debt is finally too heavy to ignore?

There are so many new AI agent platforms ( @Wordware @Lindy @CrewAI @zapier and so on) that I'm finding myself curious how everyone is using them.

What AI agents are you using in production? What do they do? Are they working and reliable? What would make them better? Are they replacing roles? Augmenting existing ones?

A credit balance turns every click into a purchase decision. That's the whole problem and it has nothing to do with the price being too high.

In a tool with several studios a video render costs roughly 40x an image. One credit unit spanning both means the user is doing arithmetic before every button, and the arithmetic gets worse as the balance drops. The first render feels free. The third one has a price tag on it. People stop long before the balance hits zero, and that shows up in your dashboard as low usage, never as a complaint about cost.

For the past few months, there has been discussion in Europe about creating a concept like EU Inc. (the 28th regime) a single pan-European legal company structure with:

• 100% online incorporation

• extremely fast setup (target: ~48 hours)

• operation across the entire EU without needing to establish 27 separate companies

• a digital-first corporate lifecycle

So far, within Europe, people most often set up companies in Estonia, mainly due to its low tax burden and fully digital infrastructure, as well as in countries like the Czech Republic, Slovakia, or Hungary.

When we landed our first big client paying $2,000/month, we were ecstatic. They were a massive logistics company, and they had one specific requirement: they needed a completely custom reporting dashboard that synced with their proprietary internal software.

We didn't want to lose the deal. So, my co-founder and I spent six weeks building this custom integration. It was a massive hack duct-taped together with webhooks and custom database queries. But it worked. The client was happy, and we had our first real revenue coming in.

Then the nightmare started.

Because we hardcoded this custom feature into our core app, every time we tried to push a new update, the custom dashboard broke. We spent the next three months firefighting bugs for this one client instead of improving the product for our other 150 users. Our overall churn rate ticked up by 5% because our standard features were falling behind, and the codebase became a mess to maintain.

Everyone s been talking about AI Agents over the past year.

But the real leverage doesn t come from the agent itself. It comes from the context you provide:

New models land almost every week. Today it was ByteDance s Doubao 1.5 Pro Vision. Meanwhile, things like more affordable compute through the IndiaAI Mission could matter more for small teams over time.

For those of you shipping AI products: how do you decide what s worth evaluating and what to ignore? Do you have a process, or is it mostly gut feel?

Something I changed my mind about while building a finance app for freelancers.

Say someone made $2,000 last month and $0 this month. The math says -100%. A big red number.

It's correct and it's still misleading. For a freelancer, an empty month often just means a payment is late. So in my app, when a month is at zero, that comparison doesn't show at all. Same with small samples: if there isn't enough history to say something, the screen says that instead of guessing.

The rule I ended up with:

When a user asks for a new button or a custom dashboard, it's super tempting to just build it and make them happy. But half the time what they re asking for is just a band aid over a much bigger issue they re having with your app. If you just keep adding every requested feature your product becomes a bloated mess.

On the flip side if you question everything they say you risk sounding like you aren't listening to them. How do you decide when to just build what they asked for versus spending time investigating what's actually broken in their workflow?