Technical experience still makes a difference, especially when the project gets big. But not nearly as much as it used to. And that’s the part I want to talk about, because I think most developers are reading this shift wrong.

You don’t need a developer to start a software company anymore

You probably don’t. Maybe you need a consultant you call every once in a while to fix the specific stuff. And honestly, maybe not even that, considering how many of the products doing well right now are trivial at the infrastructure level.

Here’s the thing people forget: when you’re starting something, you don’t need a sophisticated product. You need the simplest product that gets you to the goal. And the goal, since we live in a market economy, is that the thing generates revenue. By giving real value back to users, obviously, but revenue nonetheless.

To do that you need a product that solves the problem as fast as possible. And then you need distribution. You need access to the ears of the people you want as customers. That second part hasn’t gotten one bit easier.

The bar didn’t drop. It moved.

The numbers make this uncomfortably concrete.

According to Sensor Tower data reported by the New York Times in July 2026, the App Store added around 560,000 new apps in the first half of 2026 alone, nearly matching the ~600,000 released in all of 2025. New releases had already grown 30% in 2025 over the year before. In the first half of 2026 they roughly doubled.

Downloads over the same period? Up 2%.

Supply doubled. Demand moved 2%. Analysts attribute the surge to exactly what you’d expect: agentic coding tools putting app development in everyone’s hands.

So no, the bar didn’t get lower. Building got easier and being chosen got dramatically harder. Every developer who spent a career getting good at the building part is now watching that skill get commoditized, and I understand why that’s frightening.

I think it’s the opposite of a problem.

What actually differentiates you now

If everyone can produce a technically competent product, the technical product stops being the differentiator. What makes someone pick your thing out of a hundred thousand others is what it always was, just now with nothing else to hide behind:

• Storytelling. Why this exists, why you made it, why it should matter to them.
• Taste. The specific human choices in how it looks, how it moves, what you left out.
• Communication. How you talk to the person on the other side: before, during and long after they pay you.

Because the one who pulls out a credit card is still a human being. Not a robot. Humans don’t evaluate architectural sophistication. They get convinced by a story, by a feeling, by trust.

So yes, product development, meaning sophisticated technical product development, is largely dead as a moat. Which means the ask for us developers has changed: become entrepreneurs. Absorb the product management. Absorb the marketing. Learn to talk to the user who shows up.

And we can do it, precisely because we understand what AI actually enables. We know where the leverage is, so we can carry all of those functions at once in a way that wasn’t realistic five years ago.

What I learned building EasyPapiro

The biggest effort we put into EasyPapiro has nothing to do with code. It’s customer care.

Every single ticket gets answered by me, in first person, with zero AI in the loop. That’s a deliberate choice, and it is expensive in the only currency I actually have: time. But it’s also the thing users remember, and the reason the product’s reputation is what it is. The technical part of EasyPapiro could be rebuilt by a competent person in a couple of weeks. The relationship couldn’t.

That, plus the storytelling around it, is the whole product.

Which brings me to Armadio

Armadio is the app I’m launching now, the first product out of the app studio I’m building. It’s an AI stylist: you photograph the clothes you already own, and it composes outfits from your real wardrobe, matched to the occasion and to today’s weather. No shopping suggestions, no clothes you don’t have.

Here’s the honest part: I vibe coded the entire thing. I did not write a single line of code.

I’m a developer with years of native mobile behind me and I chose not to touch the editor, because the code was never going to be the reason someone keeps this app on their home screen. All the attention and all the care went somewhere else: into how the app presents itself, into how well the user can communicate with me and I with them through it.

That’s the only thing that counts at the end. Everything else is now a commodity, and the sooner we make peace with that, the sooner we get to do the interesting work.

You can try it at armadio.app.

Sources:

• App Store added nearly as many new apps in H1 2026 as in all of 2025 (9to5Mac)
• Vibe coding significantly boosted App Store review submissions in 2025 (AppleInsider)

EasyRegalo is the natural spinoff of EasyPapiro. While building the papiro platform we realized we were sitting on something valuable: every graduate already has a unique, AI-generated caricature that their friends love. Why should it live only on a scroll?

With EasyRegalo, that same caricature becomes a real gift, printed on t-shirts, mugs, tote bags and more. A personal, ironic and memorable present: the t-shirt the whole crew wears while singing under the graduate’s window, the mug they’ll drink from the morning after, the tote they’ll carry around to remember it all.

How it works

The flow is designed to be effortless: pick the caricature (or create a new one in minutes), choose the products, and the gift arrives in 10 days maximum, in time for the graduation. The draft is ready in a few minutes, production and shipping are handled through print-on-demand.

Traction

The spinoff launched riding EasyPapiro’s existing funnel (10k monthly visitors) and has already shipped 100+ gifts. Same audience, same caricature, new revenue stream. A textbook example of expanding a validated product sideways instead of building something new from scratch.

Check it out at easyregalo.com.

Armadio is an AI stylist built on top of your real wardrobe. You photograph the clothes you already own, the AI recognises and cuts out each garment, and from then on the app composes outfits using only what’s actually in your closet. No shopping suggestions, no items you don’t have.

The problem isn’t owning too few clothes: it’s not seeing the combinations. Armadio knows the colour, fabric and formality of every piece and pairs them the way a stylist would if they had your wardrobe in front of them. You rediscover forgotten items, buy less on impulse, and open the closet already knowing what to wear.

How it works

• Scan your clothes. Take a photo and the AI isolates the garment, categorises it and files it in your digital wardrobe. Shoot a full look and each piece gets cropped out separately.
• Outfit of the day. Every morning there’s a look waiting, built from your own clothes and matched to the occasion and today’s weather.
• Unlimited outfits. Generate new combinations on demand for any occasion.
• Rate my look. Wear something, get a score and concrete advice on how to improve the pairing.

The design direction is deliberately quiet: warm neutral palette, editorial serif, sage green as the only accent. The UI is a passe-partout: the colour is supposed to come from the clothes, not the chrome.

Tech Stack

The app is React Native on Expo with expo-router, targeting iOS first. Subscriptions run through RevenueCat, analytics through PostHog. The backend and marketing site are Next.js, with garment recognition and outfit composition powered by the Anthropic API.

Traction

Launched in July 2026 as a solo project. It’s live on the App Store with a 5.0 rating across 30+ reviews, and monetises through Armadio Premium (unlimited outfits, outfit of the day, look rating) on a monthly or annual subscription.

Check it out at armadio.app or download it on the App Store.

Overview

IntrAssist is Giorgio Pecorari’s startup, built under Oparius S.r.l. Giorgio and I have known each other since high school. He’s spent the last ten years working in customs, and he’s always been the guy who wouldn’t shut up about technology. This company is pretty much the two halves of him finally meeting. I’ve been helping out as a consultant since March 2026, mostly on the web side, well before the thing was live.

Here’s the problem it goes after. If your company moves goods across borders inside the EU, you have to file Intrastat declarations. Which in practice means someone sits down with hundreds of pages of shipping invoices and copies out country, HS code, value, weight, incoterms, line by line. It takes forever, nobody enjoys it, and one wrong digit turns into a compliance headache.

IntrAssist eats the folder of invoices and hands back the declaration. That’s the whole pitch.

How it works

• Upload the invoices. A zip, a pile of PDFs, whatever you’ve got. It goes into the processing queue, hundreds at a time is fine.
• The AI reads them. Our own parsing pipeline goes through every page, finds the fields that matter and turns them into Intrastat rows.
• Then it checks its work. VAT numbers against VIES, customs codes against the official TARIC registry, plus sanity checks on taxable value, net weight and incoterms before anything gets generated.
• Export and go. Excel, CSV or XML, ready to drop straight into the customer’s ERP.

All in the browser, nothing to install.

The numbers on the site are ~3 seconds a page and 86% less time than doing it by hand. Basically the difference between losing an afternoon and losing a coffee break.

The part I find genuinely interesting is that the rules weren’t reverse-engineered from documentation. Giorgio has filed these declarations by hand for a decade, so every edge case in there comes from someone who’s actually been burned by it. A lot of software in this space is built by developers alone, and you find out the moment a real invoice shows up looking nothing like the happy path.

My role

Most of my work has been web development: the landing page, the marketing site, and the web app the customers actually log into every day: upload flow, processing queue, the validation dashboards, the export.

The interesting constraint here isn’t visual. These people already do this job well, they just do it slowly, and the whole product is worth nothing if the interface makes them second-guess a number. So it’s a lot of thinking about how you show a hundred extracted rows in a way someone can scan and trust, and where to put the “check this one” flag so it doesn’t get ignored.

I also gave a hand on the invoice parsing side, though that’s mostly not my work.

Traction

The company’s been up and running since June 2026, selling to customs brokers and in-house trade compliance teams. Pricing is custom, based on volume, plus a one-off onboarding.

Check it out at intrassist.com.

Overview

Anapana is Italy’s first mindfulness and meditation app built entirely in Italian: not translated, not adapted, but designed from scratch for Italian speakers. The app helps people train their minds to be present through guided meditations, breathing sessions, and a structured 30-day program, all grounded in neuroscience and mindfulness research.

My role here is twofold: I lead the mobile development of the product (iOS and Android), and I also own the growth side of the app, from acquisition strategy to retention and monetization experimentation.

My role

Mobile Development I’m responsible for the full mobile experience across both platforms. This means owning the architecture, the meditation player, session flows, subscription integration, and everything in between. The codebase is built for performance and reliability, because when someone is trying to meditate, the last thing they should be thinking about is their app.

Growth Beyond engineering, I manage the growth function: analyzing user behavior, running experiments on onboarding and paywall flows, optimizing conversion across the subscription funnel (quarterly, semi-annual, annual), and identifying the levers that actually move retention. It’s the part of the product where data and intuition have to work together.

What the app offers

• 30-day structured program: builds a meditation habit from scratch, no prior experience needed
• Guided meditations: expert-led sessions on focus, stress, and awareness
• Breathing exercises: practical tools for day-to-day calm
• Personalized practice: adapts to the user’s experience level and goals
• Science-backed: developed with input from mindfulness, neuroscience, and psychology experts

Links

• anapana.it

Overview

SEO Wrap is my own project, born from a simple observation: Google Search Console is full of valuable data, but making sense of it (let alone sharing it) is tedious. So I built something that turns your entire year of search performance into 8 beautiful, shareable visual stories, inspired by the format popularized by Spotify Wrapped.

Connect your Search Console account, wait 30 seconds, and get a personalized SEO year-in-review covering everything from your top queries and champion pages, to geographic reach, device breakdown, hidden insights, and monthly trends.

The whole experience is free, requires no credit card, and zero technical setup. It’s designed for website owners and marketers who want to actually understand and communicate their SEO performance, not just stare at spreadsheets.

Recognition

• 🏆 #1 Product of the Day on OpenHunts
• 🥈 #2 Product of the Day on PeerPush

What it shows

• Overview: total clicks, impressions, and year-over-year growth
• Top queries: the searches that drove the most traffic
• Champion pages: best-performing URLs with detailed stats
• Geographic reach: where your audience comes from
• Device breakdown: mobile, desktop, tablet split
• Monthly trends: how performance evolved through the year
• Hidden insights: surprising discoveries in the data
• Year-end summary: everything in one shareable card

Why I built it

I wanted a faster, more visual way to review and present SEO progress, both for my own projects and when working with others. Building SEO Wrap also gave me the chance to go deep on the Google Search Console API, data visualization, and the challenge of making complex analytics feel human and accessible.

Links

• seowrap.now

I’ve always been told that writing by hand is the best way to journal. The idea is that forming letters on paper creates some special cognitive pathway that helps you think more clearly and organize your thoughts better. That’s why every journaling app out there is built around writing. They assume that to really reflect on your life, you need to sit down and carefully put your feelings into words on paper.

But here’s what I’ve been wondering lately: what if that’s not true for everyone? What if some of us think better when we talk rather than when we write? What if we could flip the whole journaling thing on its head and use our voice instead?

My Personal Discovery

This all started with a simple realization I had about myself: I’m way better at expressing my emotions and working through complex thoughts when I’m talking out loud than when I’m trying to write them down. It’s like there’s this direct line from my brain to my mouth that just works better than the one to my hands.

I started noticing this when I’d try to journal about something difficult that happened during the day. I’d sit there with a pen and paper (or more often, my phone), and I’d struggle to get the words out. But then I’d call a friend and suddenly I’m explaining the whole situation perfectly, with all the nuance and emotion that I couldn’t capture in writing.

The thing is, writing has these built-in barriers that I never really thought about before. You have to think about spelling, grammar, sentence structure, all this stuff that has nothing to do with what you’re actually feeling. It’s like trying to have a deep conversation while also solving a puzzle. Sometimes the puzzle-solving part takes over, and you lose the emotional thread you were trying to follow.

Why Voice is So Much Richer

Here’s the thing about voice that I find fascinating: when you talk, you’re not just saying words. You’re communicating through your tone, your rhythm, how fast or slow you’re speaking, the little pauses and stutters. All of this stuff that writing completely strips away.

I’ve noticed that when I’m talking about something I’m excited about, my voice gets higher and I talk faster. When I’m struggling with something, I slow down and my voice gets quieter. When I’m not sure about something, I’ll pause or say “um” a lot. These are all clues about what’s really going on in my head that I would never capture if I was just writing.

And here’s something else I’ve realized: those little mistakes and corrections we make when we’re talking? The “um”s and “uh”s and mid-sentence corrections? Those actually tell you something about what’s happening in your brain. When I’m writing, I edit all that stuff out, but when I’m talking, it’s all there: the raw, unfiltered version of my thinking process.

The Beauty of Unfiltered Thoughts

One of the things I love most about voice journaling is that it captures your thoughts exactly as they happen. When you’re talking, you don’t have time to think “should I say this?” or “how should I phrase this?”. You just speak. And what comes out is often the most honest version of what you’re thinking.

I’ve found that when I try to write about something, I end up editing myself before I even get the words down. I’ll think “that sounds stupid” or “I should rephrase that” and end up with something that’s not really how I feel. But when I’m talking, I can’t do that. The words just come out, and they’re usually more honest and more revealing than anything I could write.

And here’s the cool part: when you do try to correct yourself while talking, the original thought is still there in the recording. It’s like having a complete picture of your thinking process, including all the detours and corrections. This has been incredibly valuable for me. I can see patterns in how I think that I never would have noticed if I was just reading my written journal entries.

Building ThinkAloud: My Solution

After months of thinking about this problem, I decided to build something that would let me journal the way I actually think, through voice. That’s how ThinkAloud was born.

The idea is simple: you press a button and start talking. As you speak, your words get transcribed in real-time, so you can see your thoughts materialize on screen. But it’s not just a voice recorder. The app actually analyzes what you’re saying and asks you questions to help you dig deeper into your thoughts.

I’ve been working on this for a while now, learning about speech recognition technology and how to make sense of the patterns in our speech. It’s been a fascinating journey, and I’m excited about how it’s turning out.

Here’s what the app looks like: you can see the real-time transcription happening as you speak

Why Voice Journaling Works Better (For Me)

After using both methods for a while, I’ve noticed some clear differences between voice and written journaling. Here’s what I’ve found:

The Natural Flow

When I’m talking, my thoughts just flow. There’s no stopping to think about spelling or grammar or how to structure a sentence. It’s like having a conversation with myself, and the words come out exactly as I’m thinking them.

Capturing the Full Picture

Writing only captures the words, but voice captures so much more. I can hear in my recordings when I’m excited about something (my voice gets higher and faster), when I’m struggling (I slow down and get quieter), and when I’m not sure about something (lots of pauses and “um”s). This gives me a much richer picture of what was really going on in my head.

No Self-Editing

This is a big one for me. When I’m writing, I’m constantly editing myself: “that sounds stupid,” “I should rephrase that,” “that’s not quite right.” But when I’m talking, I can’t do that. What comes out is what I’m actually thinking, not what I think I should be thinking.

Speed and Efficiency

I can capture a day’s worth of thoughts in about 10 minutes of talking. If I tried to write all that down, it would take me an hour or more. Plus, I’d probably give up halfway through because writing is just more work for me.

What ThinkAloud Actually Does

So here’s how the app works under the hood:

Real-Time Transcription: As you’re talking, your words appear on screen almost instantly. It’s pretty magical to watch your thoughts materialize as you speak them.

Smart Analysis: The app doesn’t just transcribe, it actually tries to understand what you’re saying. It looks for patterns in your speech, emotional themes, and topics that come up frequently.

Guided Questions: Based on what you’ve said, it asks you questions to help you think deeper about certain topics. Like if you mention feeling stressed about work, it might ask “What specifically about work is causing this stress?” or “When did you first notice this feeling?”

I’m still working on making this part better, but it’s already been really helpful for me. Sometimes the questions it asks make me realize things I hadn’t thought about before.

Why This Matters

I think the reason this is so important is that we’ve been assuming everyone thinks the same way. We’ve built all these journaling tools around writing, but what if some of us just aren’t wired that way?

I know plenty of people who are amazing writers and love journaling with pen and paper. But I also know people like me who think better when they’re talking. We shouldn’t have to force ourselves into a writing mold just because that’s what’s available.

What I’ve Learned

Building ThinkAloud has taught me a few things:

People are different: What works for one person might not work for another, and that’s okay.

Technology can adapt to us: Instead of us adapting to technology, we can build tools that work the way we naturally think.

Voice is powerful: There’s something really special about capturing our thoughts exactly as they happen, without the filter of writing.

Wrapping Up

I’m not saying voice journaling is better than writing. I’m saying it’s different, and for some of us, it might be exactly what we need. ThinkAloud is my attempt to give people like me a way to journal that actually works with how our brains are wired.

If you’ve ever struggled with traditional journaling or felt like you couldn’t quite capture your thoughts in writing, maybe give voice a try. You might be surprised by how much more natural it feels.

This is just my experience and what I’ve learned along the way. I’d love to hear from others who’ve tried voice journaling or who have similar struggles with written journaling.

Overview

Thinkaloud is a journaling app I developed during the summer of 2025 that addresses a common problem I’ve personally experienced with traditional journaling. While I’m a big fan of journaling, I’ve always found that written journaling is incredibly time-consuming and mentally demanding. I was looking for a solution that would allow me to journal while doing other activities that don’t require much thinking, such as driving.

The solution I created is an app with a voice interface that lets you talk about your day. It transcribes what you’re saying and then provides results using artificial intelligence. Through AI, you get additional insights and questions that help improve your thinking and self-reflection.

What makes this project particularly interesting is that it’s not just about the technical implementation. It’s been a journey of learning and growth, especially in the realm of SaaS marketing. I’m actively creating content across multiple platforms - Instagram reels, TikTok videos, YouTube content, blog posts. This hands-on experience with marketing has been incredibly valuable and has significantly contributed to my professional development.

Technical Details

• Platform: iOS (launched July 2025)
• Technology: React Native
• Key Features: Voice recognition, AI-powered transcription, intelligent insights, and reflection prompts

Marketing Strategy

The app is actively marketed through multiple channels:

• Blog articles on the website
• Instagram reels and posts
• TikTok videos
• YouTube Shorts

This multi-platform approach helps us reach users where they are and build a comprehensive marketing presence.

Available on

• iOS App Store
• Website
• Instagram
• TikTok
• YouTube

And the reason behind it’s simple: if you’re a content creator, you easily realize how much more convenient it is to generate a blog post, user-generated content for an Instagram reel, or now they’re even coming up with YouTube and Twitch simulations, completely generated by AI. This is clearly made possible by models like LLMs, classic text-based ones, GPT and similar, or multimodal LLMs, specifically services like GPT-4o Image Generation, Sora from OpenAI, but also Veo3 from Google, which are capable of generating realistic content that’s indistinguishable from reality, let’s say from a viewer’s perspective, but which are nothing more than AI-generated.

The Downside of AI-Generated Content

This clearly presents enormous problems. When you generate a blog post with artificial intelligence, you don’t even realize that the model, as we think, can hallucinate.

Maybe it does hallucinate from wrong information, maybe from information that doesn’t resonate. And so you generate content that might be cheap. Search engines at the SEO level notice it, there’s a deranking of this content and so fundamentally you get almost the opposite effect. You’re not publishing content, but you’re publishing really cheap content that won’t attract users’ attention.

The Alternative: Authenticity

However, there is an alternative. I strongly think that the people who create content on the internet have the desire to be authentic. They have the desire to expose themselves, to show themselves, to show what they have inside. This applies both in terms of blog posts, personal blog posts like this one you’re seeing, but also in terms of blog posts about their products, which are still an extension of themselves and therefore their artistic expression, but also regarding various content.

Why AI Blog Posts Feel Inauthentic

Regarding blog posts, a measure I’ve found, which I’m currently using for the blog post you’re reading right now, is to think more about the medium.

In my opinion right now, from my direct experience, but also from that of others I’ve had the pleasure of talking to, the generation of blog posts with AI is not fulfilling, but it’s convenient. The convenience, the fact that from a prompt, from just a few pieces of information, I can generate a blog post really quickly compared to taking an hour to write it, far outweighs the feeling of writing something inauthentic. And the reason is clear: we all compete in an era where we need to seek others’ attention. If we produce more content, we have more chanches to attract the user attention.

If we give content that attracts attention, we get more clicks, more impressions, and so this clearly has advantages. If you do it on a personal blog, where maybe you talk about other products, clearly the influence you gather also goes to your products. If it’s a product blog, clearly you attract clicks to the product and so on.

My Solution: Voice-to-Text Authenticity

But in my opinion, there are more efficient ways to be authentic. One of these is using voice.

A Bit About Me

A bit of background about me: I’m a somewhat atypical developer, I’m not the classic developer who likes to stay in corners, let’s say.

I was born with an introverted mindset that then, through various life experiences, became very extroverted. I understood that expressing myself makes other people understand me, but it also helps me first and foremost to be sure of what I have inside, right? And this over the years has made me become more and more extroverted. And many colleagues would also say that I’m quite talkative, I like to talk, I like to express myself, I like to elaborate concepts and I definitely have a small problem with the art of summarizing, right? In fact, when I talk, the various concepts I have in my head all seem much more important than they are, and so I tend to say more things rather than fewer things.

But I like doing it and it often happens that I send long audio messages on WhatsApp, I send long audio messages on Telegram, both about personal things and work, and so I experimented with this thing.

My Voice-to-Text Workflow

Initially, I started writing blog posts with voice for EasyPapiro. Specifically, I would go out for a walk, go on Telegram to send myself an audio message, and this audio was the blog post.

I would talk, talk, talk, talk, and then I would give this audio to a speech-to-text model that would then be reformatted a bit to make it into a blog post. I did this with VoiceLog, a product I created a year ago that allows you to do exactly this: it creates a preview of a blog post from a Telegram audio. Then I took a step further in the sense that speech-to-text models have improved a lot, and now my workflow for creating blog posts is a bit different.

I use Super Whisper, which has a great ability to understand what I’m saying and synthesize it well. Then I use a minimum of AI to correct those small spelling things or, I don’t know, when I talk about a product, to put the right links, I do a bit of post-processing, and then with my blog, with this blog you’re reading, I go to publish and I publish the post.

me “writing” this blog post

Why This Works

This, in my opinion, is a very beautiful way to use AI to be authentic. It’s in the sense that through speech you’re as authentic as possible. You can’t read in the blog post when maybe I go from one topic to another, or maybe when while I’m talking I focus on something that particularly interests me, which is an expression of me, in fact, an expression of the content I want to give. With post-processing I don’t distort the content, I only correct spelling or format it, and so it comes out as a really very human discourse.

The Result: Fighting AI with AI

The beauty of this approach is that it leverages my natural communication style. As someone who enjoys talking and can articulate complex ideas in a single flow, I can now create content that feels genuinely human while still being efficient. What used to take an hour of careful writing now takes just 20 minutes from thought to publication.

Here’s the timeline: I started recording this audio at 3:50 PM on Sunday, June 22nd. By 4:10 PM, it was live on my blog. Twenty minutes total, from voice to published post.

The irony is perfect: we’re using AI to combat the very problem AI created. While AI-generated content threatens to make the internet feel artificial and soulless, we can harness AI’s speech-to-text capabilities to preserve human authenticity. It’s fighting fire with fire, but in the best possible way.

As a developer, I’m used to a linear process. When you’re coding, if something doesn’t work, there’s always a deterministic reason behind it. You can use logic to figure it out, fix it, and move on. You add one feature, then another, then another, and gradually build your product. Design works similarly - you add an element to your site or app, tweak it until it looks right, and you’re done. These are all linear processes where you get immediate feedback and can iterate based on that feedback.

But marketing? That’s a whole different beast.

The Content Machine

For Easy Papiro, a project I’ve mentioned before on this blog, we’re creating tons of content. We’re making short-form videos for Instagram, TikTok, and YouTube Shorts - my co-founder and I have created about 45-50 pieces of content that we publish daily. On top of that, I’m writing and managing Easy Papiro’s blog, specifically targeting our users’ use cases.

All of this content is created for marketing purposes, to reach our end users. For social media, we’re aiming for viral content. We publish and watch which pieces gain traction, which ones attract more people. For the blog posts, we’re targeting specific Google queries that we know are most relevant to our area of interest.

The Reality Check

You can do all the research in the world - study successful formats on social media, analyze what’s worked for other pages, use SEO tools for keyword research - but here’s what I’ve learned: marketing is anything but linear.

Every time I’ve thought:

“This has to work - I’ve been consuming Instagram content for 10 years, I know this format works!” or “This blog post is exactly what someone would search for on Google to find our product,”

I’ve been promptly disappointed. I’ve realized that for this type of product, I don’t actually know what hooks will work, even though I was certain I did.

The Developer’s Dilemma

I’ve been on social media for 10 years, watching new formats and trends emerge constantly. I thought I knew what worked. But it’s never that simple. It’s never linear. It’s never deterministic. As a developer, I try to model everything deterministically, but the truth is, we’re talking about masses of people. We’re shouting in a crowded square, trying to get people to notice our product, and there’s no deterministic way to figure out the best way to shout.

The Answer: Patience

So what’s left? How do you do this kind of work?

The answer is patience - something I’ve never had to cultivate as a developer. Patience that leads to consistency. The ability to keep publishing day after day, week after week, month after month - posts, content, videos, blog posts - accumulating your knowledge of what works. After maybe two weeks of mediocre view counts, that one piece of content you thought was just filler, that you never expected to become popular, suddenly takes off. And that’s exactly what happened to us.

Marketing, being not an exact science but rather a science dependent on infinite variables, is teaching me patience. It’s forcing me to cultivate it, to embrace the uncertainty, and to keep showing up day after day, even when the results aren’t immediate. And you know what? I’m starting to appreciate this lesson.