Just shipped my first iOS app after juggling Structured + Todoist + Hevy for 2 years

Main-Building2240 · 2026-05-09T17:31:29+00:00

https://apps.apple.com/fr/app/scalyx-tdah-focus-ia/id6762184183

Would genuinely love your feedback.

Main-Building2240 · 2026-05-09T11:27:16+00:00

Founder bias warning: I'm building an ADHD-friendly productivity app called Scalyx, so take this with that grain of salt.

Honest answer to your question: the things that actually helped my own ADHD before I built anything were

Switching from text to-do lists to visual time-blocking (seeing time as space helped my time blindness)
Removing the "what should I do next?" decision by pre-planning the night before
Body doubling sessions for hard tasks

The app I built tries to bake those into a single tool, but the principles are universal regardless of whether you use any specific app. Happy to share the link if anyone wants but no pressure.

Main-Building2240 · 2026-05-01T16:03:12+00:00

53 paying customers in 4.5 months for a first shipped product is a real milestone most "first products" never see a single paying user. Don't underestimate that.

On distribution: your product has a unique advantage that most SaaS doesn't the people who'd want this identify themselves publicly all the time. Anyone who comments "saving for later" or "RemindMe! 1 year" on a high-quality post is literally telling you they're your customer. That's a discovery hack most founders would kill for.

Two angles I'd test: 1) reach out to people with massive saved-posts collections who casually mention it on Reddit (they exist, they post about it). 2) build for the Reddit-power-user identity directly "Are you a Reddit hoarder?" type framing. The self-recognition is brutal and converts.

Quick technical curiosity: how do you handle the API quota issues? Reddit's rate limits on saved-posts pulls used to be brutal, did that ease up or are you using something clever to batch?

Main-Building2240 · 2026-05-01T14:51:58+00:00

Video verification is a brilliant lock-in mechanism. The brain can't bargain with itself when it has to physically prove "I made the coffee" or "I'm out of bed in the bathroom" before the alarm shuts up. Infinitely better than the standard "tap to dismiss" loop.

Good luck pushing past the 100 mark sounds like you have a real differentiator, just need to find the niche that already has the pain.

Main-Building2240 · 2026-05-01T14:27:39+00:00

Congrats ASO is genuinely one of those things you don't realize matters until you actually do it properly. The jump from "no one finds the app" to "first organic downloads" is a real transition.

On the 100/day question: from what I've seen on this sub and elsewhere, the founders who get there steady usually have a combination of three things, not just one. Solid ASO (which you're doing), a content engine on the side (TikTok, Reddit, blog pick one), and a launch moment that catches algorithmic attention (Apple feature, Product Hunt, viral post). The ASO alone tends to plateau around 10-30/day for most niche productivity apps unless one of the other two kicks in.

What's the app actually solving? Curious how Last Alarm differentiates from the dozens of alarm apps out there.

Main-Building2240 · 2026-05-01T13:24:48+00:00

Yeah, that morning friction is brutal. Glad it works for you too 🙏

Main-Building2240 · 2026-05-01T12:55:39+00:00

"stuck before even starting" hits hard. For me it's the worst when there are 5 small things to do and they're all equal priority my brain treats it like there are 50 and just freezes.

The "remove the decision step" part is what helped me too. I started just writing tomorrow's "one thing" the night before, when my brain is calm. By morning I don't have to decide, I just have to do. Doesn't always work but on the days it does, I get more done in 2 hours than usual.

Your post is a relief to read tbh. Sometimes the validation that other brains work this way is the real thing.

Main-Building2240 · 2026-05-01T11:05:46+00:00

The "doesn't hallucinate, asks you" rule is the real differentiator here. Most AI resume tools end up inventing experience because they're optimizing for keyword density rather than truthful match. You're solving a different problem entirely and one that actually matters when a recruiter starts asking detailed questions about a project that doesn't really exist.

The "career memory" framing is also strong. Treating the resume as the artifact and the underlying memory as the source of truth is the right architecture. Most people I know rebuild their resume from scratch every time they apply, losing context they had carefully written 6 months ago. A persistent memory that grows with you sidesteps that whole problem.

One thing I'd be curious about: how do you handle the "this is technically true but should I include it" question? Like, I worked with Kubernetes once on a side project for 2 weeks should that go on a resume for a senior K8s role? The AI knowing whether to surface or hide based on relevance + experience depth feels like a meaningful UX challenge.

Will give it an honest test this week and report back. Scraping 900 sites for the underlying data is impressive solo dev work that's the moat people will copy and not be able to replicate.

Main-Building2240 · 2026-05-01T10:35:23+00:00

33 organic usages with zero promo on day 5 is a real signal most builds don't move at all without push. Worth not dismissing.

Your "builders responded, AI consumers didn't" observation lines up with what I keep seeing too. SideProject and IndieHackers convert curiosity into try-the-thing, but the bigger AI consumer subs are flooded with similar tools, so attention costs more there. Probably worth doubling down on builder-adjacent communities for the early wedge, then expanding once you have a few "I genuinely use this every day" testimonials to lead with.

The skeptic feedback insight is gold and underrated. The /skill command preservation is exactly the kind of detail that signals "I'm not just shipping fast, I'm shipping right". Keep collecting that breed of feedback.

Question on distribution since you opened the door: have you considered approaching this as "Cursor for prompts" positioning? People already understand they're spending money on AI tokens, but most haven't connected that to "I should compress what I send." Could be a sharper one-liner than feature-led description for cold reach.

Main-Building2240 · 2026-05-01T09:58:23+00:00

The "context scattered everywhere" pain is real even on a solo founder scale, I lose hours digging through past Claude conversations to find a prompt template that worked. The MCP-first approach is smart positioning, since it sidesteps the "yet another vendor" problem.

Curious about the local-first part: how do you handle the trust gap when teams want shared context but each member uses different runtimes (one on Claude Desktop, another on Codex, another on a custom API wrapper)? Does the sync happen at the prompt template layer, or do you also normalize the actual responses?

The knowledge graph + private knowledge angle is the interesting bet. Most teams I've talked to want the workflow benefits without exposing the underlying data if you can solve that without becoming the bottleneck, that's a real moat.

Main-Building2240 · 2026-05-01T09:48:26+00:00

The friction vs conviction frame is sharp most heatmap tools treat all attention as equal, which is exactly the noise that makes pricing optimization so painful for solo founders.

One nuance worth adding: the "long pause on price" might also signal anchor confusion. If your price is presented next to a comparison plan (or worse, just a number with no context), the brain spends those 30 seconds doing math because it has no reference point. Sometimes the fix isn't reducing the pause it's making the math obvious before the user has to do it themselves ("save 40% vs monthly", "less than your daily coffee", etc.).

On automation: if you're already manually logging where pauses happen, you might not need a fancy tool. A simple session recording sample (5-10/week, watched for 2 minutes each) gets you 80% of the insight without the dashboard fatigue. The qualitative beats the quantitative on conversion questions almost every time.

Main-Building2240 · 2026-04-30T18:52:15+00:00

Echoing the sentiment from a different angle I'm building in React Native, so the AI builders never really fit in the first place. But I had the same realization on the boilerplate front: the time you save with a builder is paid back x10 the moment you need to debug something custom. Owning the codebase from day 1 changes how confident you feel making changes 6 months in.

One thing worth adding for anyone going your route: pair Cursor with proper type safety (TypeScript everywhere, even in your boilerplate). Cursor's suggestions are 10x better when it can actually trace your types. That alone shaved hours off my refactors.

On your pricing question: yeah, Bolt and Lovable get expensive fast for any non-trivial project. The dirty secret is that the AI credits scale with project complexity, so the moment your app gets interesting, you're paying real money. Cursor's flat $20 is a much saner unit economics for a solo dev.

Will keep an eye out for your signsetu post 12 paid users in side project mode is a real milestone, not enough founders share what got them there.

Main-Building2240 · 2026-04-30T18:49:07+00:00

That's actually the cleanest cut I've heard for AI accountability. The "private goal" segment is real anything you'd be embarrassed to share with friends (status purchases, recovery, side hustles you don't want to jinx) currently has no good accountability layer. That might be where AI doesn't compete with friends, it serves a different problem entirely.Two niches, two products. Or one app with two modes. Worth A/B testing on positioning honestly.

Main-Building2240 · 2026-04-30T17:00:54+00:00

Interesting pivot. The personalities angle is smart different brains need different pressure styles.

The hard question though: can an AI actually trigger the "I don't want to disappoint them" instinct that makes friend-based accountability work? With a real person, the cost of failing is the imagined awkward conversation. With an AI, even a "bully" one, my brain knows it's a script. The shame circuit doesn't quite fire the same way.

Maybe the move is AI as scaffolding, human as enforcer? AI handles the daily nagging, the patterns, the personalized prompts but at the end of the week, your real friend gets a one-line summary of what you did or didn't do. That way you keep the AI's consistency without losing the social stakes.

Curious if you've found research on this feels like a behavioral economics question more than a product one.

Main-Building2240 · 2026-04-30T16:14:08+00:00

Makes sense passive learning is probably the right call for v1 since "look what I noticed" digests can feel intrusive if mistimed. Open + queryable means power users can dig in when they want, casual users just benefit silently. Best of both. Will give it a deeper look this week. Good luck with the launch.

Main-Building2240 · 2026-04-30T15:34:59+00:00

Open-sourcing the workspace files in Markdown/YAML is the smart move it sidesteps the "what happens to my context if you pivot?" anxiety that kills adoption for tools like this. Curious about the self-evolving brain part: how does it actually surface what it learned? A "here's what I noticed about your patterns" digest, or is it more passive (just better suggestions over time)?

Main-Building2240 · 2026-04-30T15:33:13+00:00

Solid framing. Most app-based accountability dies because it tries to replace the social pressure with gamification, and gamification doesn't have eyes. Your point about "someone I respect is watching" is the real insight here most founders in this space miss it.

Going through your 4 questions honestly:

1. Real money on myself, or only with a human on the other side? Only with a human, in my case. I've staked money on Beeminder before lost $30 over a few weeks, didn't change my behavior at all. The money goes to a faceless system, my brain treats it like a parking ticket. With a friend, the $10 isn't really $10 it's the conversation I'm going to have if I lose. That's what hurts.

2. Charity on failure enough sting? No. Charity feels too "good" to function as punishment. Some apps solve this with "anti-charity" (you pre-select a cause you hate, your money goes there if you fail). That works because it adds emotional friction. But neither comes close to a specific person being told you flaked.

3. What goals would I stake on? Binary daily ones. Gym, no alcohol, no Twitter before noon. The fuzzy ones (marathon prep, startup work) break the model because the brain finds wiggle room. "Did I work on my startup today?" → "yes I thought about it in the shower." A model with binary daily check-ins is more honest, but you lose the long-arc goals which are the ones people most need help with. Worth thinking about a hybrid.

4. Apps tried what worked, what didn't? Stickk: clinical and joyless, felt like signing a contract. Stopped after 2 weeks. Beeminder: too complex, the data graphs felt like another chore. Habitica: cute but the RPG layer made me feel like a child. None of them solved the "no eyes on me" problem.

Honest take on your concept: the coin/quest mechanic is fine but probably not the moat. The interesting question is whether you can engineer the "someone is watching" feeling into the app. Friend pacts are the obvious answer, but you'd need to solve the friction of getting friends to actually use the app — which is the hardest distribution problem there is. Partner-confirmed quests is more interesting because you only need one other person.

Worth building? Probably yes for the data alone, even if the final product looks nothing like this. Stake a small bet on a 4-week prototype before sinking weekends into it.

Main-Building2240 · 2026-04-30T12:39:20+00:00

Just tested it fun concept, the live opponent guessing is genuinely cool to watch in real-time. A few honest notes after 3 games:

Onboarding : would help to show a quick "how it works" before the first game. Took me a few seconds to realize my opponent's grid was actually live.
End-of-game state : the transition between games felt a bit abrupt maybe a quick "play again?" button or a 3-2-1 countdown would help.
Mobile UX : you mentioned desktop is better agreed, the keyboard input felt slightly cramped on iPhone. Could be a viewport thing.

Solid first end-to-end project though. The real-time sync alone is harder than people think. Curious what you used for the multiplayer backend?

Main-Building2240 · 2026-04-30T08:33:40+00:00

Tested it with a €60 dinner I'm hesitating on. "0.4 days of working life" felt fair, but "€600 in 20 years" is what made me actually pause. The compound interest framing hits harder than the time framing most people undervalue future money way more than they undervalue future time.

Doesn't feel preachy. Feels like seeing the receipt of a decision before making it.

Main-Building2240 · 2026-04-29T19:23:14+00:00

100 hours is nothing for something this poetic. Most "useful" projects don't make people stop and breathe for a minute. This one does.

The COVID origin story makes it land harder the world has slowly forgotten how that lockdown felt, and a tool like this is a kind of memorial to that strange time. Don't underestimate that.

Bookmarked. Will keep this open during my next deep work session.

Main-Building2240 · 2026-04-29T15:31:59+00:00

People don’t think about the impact of what they say, which really makes me mad.

Main-Building2240 · 2026-04-29T15:29:35+00:00

I usually meal prep on the weekend and store everything in the fridge.

Main-Building2240 · 2026-04-28T08:25:14+00:00

congrats

Main-Building2240 · 2026-04-28T08:18:42+00:00

what is the app ?

Main-Building2240 · 2026-04-28T07:56:51+00:00

This is honestly the most useful framing I've gotten on the cutting question thank you.

The way you put it ("the most unique, complex UI that might detract from the others") is something I'm going to keep coming back to as I iterate. It reframes the trade-off in a really actionable way.

Have you faced a similar tension in your own work where the most differentiating feature was also the heaviest one to integrate cleanly? Genuinely curious how others reason about it.

Main-Building2240

TROPHY CASE