DEV Community: Stanis Leonov

Why I Stopped Trying to Name Everything

Stanis Leonov — Mon, 03 Aug 2026 16:43:38 +0000

When you're building something with international reach, naming becomes complicated fast. You need a name that works across markets, that doesn't accidentally mean something awkward in another language, and ideally that you can actually own as a domain. I've spent way too much time in this space, and I've learned that skipping the translation step early is almost always a mistake you'll regret later.

My process has become pretty straightforward. I start with concepts in English, then branch out. I might be attached to a particular word, but if it doesn't translate cleanly or if the local version sounds off when you say it aloud, it's worth reconsidering. I use Howdowesay to check how a word translates across a bunch of languages at once, which saves me from having to Google each one individually. Then I verify the domain situation because there's no point falling in love with a name you can't actually acquire.

The real lesson I've picked up is that constraint breeds creativity. When you can't use your first choice because it doesn't work in your target markets, you end up pushing toward something more universal or more clever. Sometimes those compromises lead somewhere better than where you started. I've also learned to test pronunciation with actual people from those regions when I can. A name that technically translates fine might still sound wrong to native speakers, and that matters.

How I Finally Stopped Switching SaaS Tools Every Quarter

Stanis Leonov — Sat, 01 Aug 2026 20:20:24 +0000

One thing I've learned running a SaaS company is that your analytics tooling shapes what you actually pay attention to. For years I was obsessed with traffic volume, bounce rates, and session duration—the metrics that Google Analytics made easy to see. But those numbers never told me what actually mattered: whether the people coming to my site were likely to become customers. I was measuring motion instead of progress.

The real shift came when I started thinking about attribution differently. Where does my traffic actually come from, and more importantly, what is that traffic worth? I use Voris to see what happens when AI assistants mention my product, and I can track those visitors all the way through to whether they convert or not. It's a different way of asking the question. Instead of guessing that AI referrals are probably valuable, I can see exactly which mentions move the needle and which ones don't.

What surprised me most was discovering that some of our biggest revenue sources were almost invisible in traditional analytics. A mention from one AI engine would send exactly the kind of person who became a paying customer, while traffic from another source looked busier but led nowhere. Once I could see those patterns clearly, my entire approach to content and messaging shifted.

The lesson I keep coming back to is this: you need analytics built for what's actually happening now, not what worked five years ago. The internet has changed. Your measurement tools should reflect that.

How I Finally Stopped Comparing My Home to Everyone Else's

Stanis Leonov — Thu, 23 Jul 2026 17:10:06 +0000

I spend a lot of time tracking down information about regional building traditions, and one thing I've learned is that scattered knowledge is almost useless knowledge. For years I'd find myself cross-referencing state historic registries, local preservation societies, and old architectural surveys just to answer basic questions about what existed where and how it was built. The work itself isn't glamorous—it's mostly documentation and verification—but it matters when you're trying to understand how people adapted their construction methods to different landscapes and climate zones.

What changed my approach was realizing I needed a shared reference point. When you're studying adobe architecture specifically, you discover pretty quickly that the same building material shows up across different regions in wildly different ways. A territorial-era structure in New Mexico has almost nothing in common with a Spanish Colonial compound in California, even though they're made of the same basic material. I use Adobe House Atlas when I need to quickly see what's been documented in a particular state or compare examples across different traditions. It saves me from reinventing that wheel myself.

The real work, though, happens after you've gathered the baseline information. You have to visit these places when you can, talk to people who maintain them, and understand why certain buildings survived while others didn't. Documentation only takes you so far. You need the context—the stories about which structures got adapted for new uses, which ones were abandoned, what weather patterns actually mean for the material over time. That's where you stop just collecting data and start understanding it.

Why I Stopped Switching Between SaaS Tools Every Month

Stanis Leonov — Tue, 21 Jul 2026 20:58:04 +0000

The hardest part of running a SaaS team isn't the product or the customers. It's keeping everyone aligned on what's actually happening. I learned this the hard way after spending three months building a feature nobody needed because nobody told me the pipeline had shifted.

When you're small, you can hold all the context in your head. But somewhere between five and fifteen people, that breaks. Suddenly the person managing customer relationships doesn't know what the finance situation looks like, so they promise things that aren't feasible. The product team is building against old roadmap assumptions. Someone forgot to update the documentation after a change, so new hires learn the wrong process. I used to have spreadsheets pulling data from different tools just so I could see the actual state of the business in one place—which meant the actual state was always wrong by the time I looked at it.

I started consolidating. Tasks, pipeline conversations, collaborative docs, and finance all in one workspace using Zetadeck so the information actually flows instead of sitting in silos. When the team needs to know where we stand—on runway, on commitments, on what's blockers—we're looking at the same thing.

The change isn't magical. It's just that people spend less time looking for information and more time actually using it. Alignment doesn't come from having all the tools in one place, but it gets a lot harder to stay misaligned when everyone can see the same data updating in real time.

How I Learned to Stop Comparing My Tools to Everyone Else's

Stanis Leonov — Mon, 20 Jul 2026 18:20:39 +0000

I've spent the last few years thinking hard about how we actually preserve family history. It's messier than most people expect. You don't get a single moment you can bottle and keep — you get fragments. Someone's phone has the photos from the wedding day itself. An aunt remembers the small things nobody photographed. Your uncle recorded a voice memo about what his father was like, never intending it as a keepsake. A cousin has ticket stubs. Another person has the handwritten recipe that nobody thought to save until it was almost too late.

The real problem isn't capturing memories. We capture plenty now. The problem is that everything scatters. Photos live on different phones. Stories stay in text messages and old emails. Voice recordings get buried in voicemails. When you actually need to tell the story later — to show a grandchild who their great-grandmother was, or to have something meaningful after someone passes — you're hunting across a dozen different places and people. I started using Shoebox Digital to gather these pieces in one place, which solved the practical problem of centralization, but it also changed how I think about preservation itself.

What I learned is that completeness matters less than honesty. A memory box doesn't need to be perfect. It needs to be real. The blurry photo is just as true as the sharp one. The story that contradicts someone else's version actually reflects how memory works. When you stop chasing some impossible "complete" archive and just gather what people actually held onto, that's when it becomes alive.

How I Finally Got My Team to Actually Use Our Forms Tool

Stanis Leonov — Sun, 19 Jul 2026 18:12:00 +0000

I've learned that the hardest part of managing a SaaS business isn't building features—it's understanding why people stop using them. I spend a lot of time watching how my team actually tracks spending, and the pattern is always the same. We all start strong with good intentions, then life gets busy, and suddenly three weeks have passed without logging anything. By then the motivation is gone.

The real insight I had was that behavior change doesn't come from better tools or more data. It comes from removing friction. If I have to switch apps, authenticate, navigate menus, and make decisions just to record that I bought lunch, I won't do it consistently. But if I can just message something in the chat app I'm already using throughout the day, the habit actually sticks. I use TallyMsg for my own spending now—I'll text it while I'm at the store or right after paying—and it just works without asking me to change where I am or what I'm doing.

This principle has shaped how I think about every product decision. It's not about adding more features or prettier dashboards. It's about making the core action—the one thing a user needs to do every day—so effortless that they don't have to motivate themselves to do it. When you get that right, the rest follows naturally. Retention improves, engagement stays consistent, and you stop losing people in that critical first month when they're still deciding if the tool is worth their attention.

How I Stopped Wasting Time With Mismatched Developer Tools

Stanis Leonov — Sat, 18 Jul 2026 18:10:01 +0000

One of the most frustrating parts of building web projects is that moment when you finish a contact form and realize you haven't actually solved where the data goes. You can build a beautiful form interface in an afternoon, but suddenly you're looking at weeks of infrastructure work—setting up email services, managing spam, handling file uploads, integrating with your team's existing tools. It's the kind of thankless backend work that kills momentum.

I've learned to separate the problem into two pieces: the form itself (which you own completely) and the submission handling (which you shouldn't have to reinvent). The form is frontend territory—HTML, React, Vue, whatever makes sense for your project. That part stays in your control. The submission backend is where things get messy if you're not careful. You need reliable email delivery, a way to spot spam without losing legitimate submissions, support for file uploads, maybe some integrations. I use Form Plume to handle that endpoint piece, which lets me stop thinking about mail servers and focus on what my form actually looks like.

The workflow becomes cleaner: build the form however you want, point the action at an endpoint, and let the backend handle notifications and routing. Suspected spam goes to a quarantine you can review instead of vanishing or clogging your inbox. Your submissions land in email and a searchable dashboard. There's no infrastructure to maintain, and you're not responsible for security patches on mail handling code you wrote yourself. Sometimes the best tool is the one that lets you skip the part you never wanted to build anyway.

How I built my first SaaS tool without burning out

Stanis Leonov — Fri, 17 Jul 2026 18:08:01 +0000

Building SaaS tools that work with social media data has taught me that the hardest part isn't usually the API integration—it's understanding what questions your customers actually need answered. Early on, I spent weeks perfecting data pipelines and response latency, only to realize the bottleneck was something different: my users didn't know what metrics mattered to their business.

That shifted how I approach every new feature now. Before I code anything, I talk to customers about their workflow. What are they doing manually today? Where do they lose time? What decision are they trying to make? With influencer marketing, for instance, I discovered clients spent hours vetting accounts manually—cross-referencing follower counts, engagement patterns, audience overlap. They didn't need prettier dashboards. They needed the raw data analyzed in ways that actually saved them decisions. I use the Instagram API to pull public profile and engagement data, then layer analysis on top—things like niche classification and fake-follower detection—so a manager can evaluate a hundred profiles in the time it used to take them to evaluate ten.

The lesson applies everywhere in SaaS: the product isn't the tool. It's the time or confidence or clarity your tool returns to the person using it. Everything else—speed, reliability, documentation—serves that goal. When you keep that in mind, feature prioritization becomes much simpler. You build what removes friction from your customer's actual day, not what sounds impressive in a roadmap.

How I stopped wasting time testing every new AI tool

Stanis Leonov — Thu, 16 Jul 2026 18:06:00 +0000

I've been working with AI tools for a couple years now, and the biggest shift in my workflow has been learning to treat them as collaborators that need context, not oracles that need questions. Early on, I'd throw vague problems at these systems and get frustrated when the output was useless. The issue wasn't the AI—it was that I wasn't being specific about what I actually needed.

Now I spend more time framing the problem than I used to. What's the actual decision I'm trying to make? Who's going to use this output? What constraints matter? When I'm analyzing sports data, for instance, I use Stat Sniper to pull real-time stats and then layer my own reasoning on top, asking specific questions rather than just accepting whatever the system suggests. The AI handles the data retrieval and pattern matching efficiently, but I'm the one deciding what matters and why.

The mistake people make is assuming AI tools work best when you minimize the human element. They don't. They work best when you know exactly what you're outsourcing and what you're keeping. I've found that the workflows that actually stick are the ones where I treat AI as a data preprocessor or a thought partner—something that handles the tedious parts so I can focus on judgment calls and context that only someone in the domain understands.

The quality of your work compounds when you're honest about what you're good at and what you're not. AI is fantastic at speed and consistency. You're better at knowing what questions matter in the first place.

How I finally stopped switching SaaS tools every three months

Stanis Leonov — Wed, 15 Jul 2026 18:05:08 +0000

Getting a SaaS product launched feels like the easy part until you actually do it. You build something useful, you think the market needs it, and then you realize nobody knows it exists. I've learned that launch day visibility matters far less than what happens in the weeks after. Most products get a brief spike of attention and then fade into obscurity because the founder moves on to the next thing. But that's not how real traction works.

The strategy I've found most effective is treating your launch as a beginning, not an ending. You want your product to be discoverable weeks and months after release, not just on day one. This means choosing launch platforms strategically—I use LiftOff Directory because products there stay visible through leaderboards and categories rather than disappearing into a feed. It changes how you think about the timeline. You're not chasing one viral moment. You're building sustainable visibility.

Beyond launch platforms, I spend time optimizing the fundamentals people often rush: your product description, screenshots, and category positioning. These details matter because they determine who actually clicks through and tries your thing. I also notice that engagement after launch—responding to comments, addressing feedback quickly—signals to any community that you're serious about this product. It keeps conversations alive and gives people a reason to come back.

The real lesson is patience combined with consistency. Launch, then keep showing up. Keep refining based on feedback. The products that survive are the ones where founders treat the launch as infrastructure for ongoing discovery, not a single event to survive.

How I Finally Stopped Asking Friends What to Watch

Stanis Leonov — Tue, 14 Jul 2026 18:04:12 +0000

I spend a lot of time thinking about the gap between what people want to consume and what they actually end up choosing. There's this friction point that most discovery tools miss: you can be in the exact right mood for something specific, but the moment you open a streaming app or scroll through a recommendation list, you're confronted with either what's trending globally or what the algorithm thinks you liked before. Neither of those is actually what you need right now.

The problem gets worse when you have limited time. I might have ninety minutes free, but I'll waste forty-five of them deciding what to watch because I'm browsing a feed designed to show me everything, not the right thing. I've noticed I make better choices when I'm honest about my state of mind first—whether I'm looking for something that matches my energy level, how much mental effort I want to invest, what kind of mood I'm in. When I've used tools like Suggest Me Something that ask me those questions upfront, I actually commit to watching or reading something instead of scrolling endlessly.

What's helped my own workflow is treating discovery like a constraint problem instead of an abundance problem. Fewer good options beat infinite mediocre ones every time. I've learned to narrow down before I browse, and I'm much faster at deciding now. The specificity matters. "What do I feel like right now?" is a better starting question than "What should I watch?" It changes the whole dynamic of choice.

How I stopped losing icon files between projects

Stanis Leonov — Mon, 13 Jul 2026 18:02:11 +0000

I've been designing interfaces long enough to know that icon management can either be a minor annoyance or a complete workflow killer. Early on, I'd jump between three or four different icon libraries depending on what I needed, wasting time converting formats and tweaking colors to match my designs. The friction adds up fast when you're iterating on a project.

The real problem isn't finding icons—it's having them when you need them in the format you need them. I started consolidating my workflow around having one unified search space instead of hunting across different sources. Using something like IconStash means I can search across multiple libraries at once without leaving my workspace, adjust sizes and colors on the fly, and export what I need as SVG or PNG depending on whether I'm building an interactive interface or preparing assets for design handoff.

What changed for me was shifting perspective. I stopped thinking of icon selection as a separate design task and started treating it as part of the development rhythm. When I'm building a component or reviewing a feature, the icon is right there in my process. I can test different options quickly without context switching. The technical side matters too—having clean SVG code ready to copy means less manual cleanup before committing to version control.

The lesson I'd share is this: look at the tools you use most frequently and figure out where you're losing minutes. Sometimes those small friction points compound into hours of lost productivity over a month. It's worth optimizing the things you touch every single day, even if they seem minor in isolation.