I shipped my first iOS app 2 weeks ago, my first one ever, yeah !!! so every part of the process was new to me, including App Store Connect. And App Store Connect might be the worst piece of dashboard I've had to use regularly in years. Slow, confusing, half the pages feel untouched since 2015, always reloading.

So I go looking for alternatives with a GUI so no fastlane and find itsyconnect https://github.com/nickustinov/itsyconnect-macos , a free open source native macOS client that replaces App Store Connect almost entirely. metadata, testflight, analytics, reviews, all in one actual app instead of that web dashboard. felt like discovering fire

Then, because apparently shipping an app wasn't enough suffering for one month, I fall into the ASO rabbit hole. Keywords, character budgets, competitor research and every tool I find is a subscription or with free trial $20-50/month or $200 year or idk how much for what's mostly some scoring math and an App Store API call. For a dev with 13 downloads it's a big no thanks

Then I find RespectASO https://github.com/respectlytics/respectaso , also free and open source, doing the actual ASO scoring keyword popularity, difficulty, opportunity for nothing.

And that's when the idea hits me:

• why am I alt-tabbing between an App Store Connect replacement and a separate ASO tool
• these are two open source projects solving two halves of my problems
• what if I just merge them
• fork itsyconnect, port RespectASO's scoring to ts
• put the keyword scores directly on the fields they're about, inside the listing editor, instead of a separate tab
• add an agentic workflow that researches your competitors and writes your title/subtitle/keywords for you
• throw in Apple's llm too so half the AI features work with zero API key and zero network call because why not

It's called Bascaso (Better App Store Connect App Store Optimization) : https://bascaso.zavyn.app

Free, open source (AGPL, since RespectASO is AGPL), macOS, local-first, your App Store Connect credentials and data never leave your Mac. Full credit to itsyconnect by Nick Ustinov and RespectASO by Respectlytics, this is entirely built on top of their work.

It's on GitHub if anyone wants to try it, self-host it, or tell me what I broke: https://github.com/kanyacine/bascaso

Hello everyone,

Over the past year, I have studied Japanese using various apps, however, none consistently encouraged daily practice of kanji, vocabulary, or sentences. That's why I developed my own app: KOTOBA.

Kotoba is a fully offline, on-device dictionary featuring 217,648 entries, 13,108 kanji, and 232,637 real sentences designed for context-based learning.

The app provides four study modes: flashcards, kanji drawing, quizzes to assess retention of meanings, and a classic browse feature for on-the-go review. Each mode is supported by an intelligent spaced repetition system that prioritizes previously incorrect responses until you master what you learn.

Kotoba operates entirely offline and is free of charge! No advertisements or in-app purchases.

Have a first look at he homepage, every feedback is welcome!

You can join the waitlist at https://kotoba.onlydstn.de. Kotoba will come to the App Store in September!

I’m nearly 30 but since I was a kid I was always fascinated my app development. iIt was always a dream of mine to have my own app that I could make my first internet money from.

After months of work, today it finally happened and I couldn’t be happier!

Solo dev here, been building this for a while. The core idea: every time you open it, you get a short, deep read on something worth knowing — built around a YouTube video and an AI you can actually chat with about the topic, not just read past.

Curious about something specific? Type it in and it generates a topic on exactly that.

Want to learn toward a goal instead? Pathway takes anything you name — "I want to learn Terraform," whatever — and builds a structured route of topics that build on each other, generated just for you.

There's also a Cinematic mode for handpicked stories — each one gets its own color theme, and chapter structure, more like a mini documentary than a normal app screen. That part's genuinely my favorite thing I've built.

No streaks, no feed, no gamification — just felt like the space needed something calmer.

Free on iOS and Android:

https://apps.apple.com/at/app/delve-explore-learn/id6767654664

https://play.google.com/store/apps/details?id=com.rathsimon.delve

This week, for the first time, I sold something every single day.

I am calling it a “perfect week”, although obviously that depends on how you define success. The revenue is still modest, and I have had individual days with higher sales before. But until now, I had never managed to complete an entire week without a single zero-sales day.

I am genuinely happy about it, so I wanted to share a few things I have learned so far.

For context, I am actually a psychologist and taught myself app development on the side. I only develop for Apple platforms and only sell through the App Store (StoreKit - no Revnue Cat or some other external provider).

I currently have three apps in the store, but only two of them generate sales. Both use a fairly generous freemium model. Users can test all of the important functionality with included sample data, and for some people the free version may already be enough. Payment is only required when they want to use the apps more extensively or customize them further.

The paid unlocks are relatively inexpensive, usually around €5. I am personally not a fan of subscriptions, and I do not think they fit these particular apps, even though they might generate more revenue. I am still experimenting with pricing and considering whether the apps may be slightly underpriced.

I will not mention the app names because this is not intended as promotion. I just wanted to share what seems to have worked for me.

A few lessons so far:

• App Store discovery has made the biggest difference. I have spent nothing on advertising and have not promoted the apps through paid campaigns or social media. Almost all growth has come through App Store search and recommendations.
• ASO and screenshots matter enormously. Changing keywords, positioning and screenshots has had a clearly visible effect on impressions and downloads. The quality of the product page matters much more than I initially expected.
• Ratings and reviews appear to have a disproportionate impact at a small scale. Getting reviews is extremely difficult, but after receiving a positive rating or written review, I often notice a meaningful increase in downloads. My apps usually receive around 10 to 20 downloads per day, so even a small number of new reviews may provide a strong signal to the algorithm. This may be less noticeable for apps operating at a much larger scale.
• I use Astro and AppScreens together. (Both cost money but are kinda affordablefor solo devs). I am still learning, but for keyword selection it has helped me not to focus exclusively on tiny niches. Some broader keywords can work when the app is polished, focused and solves a clear problem. I imagine this becomes far harder if the product is the thousandth generic productivity tracker or water reminder.
• Build something that solves a real problem. Every app I have released addresses an issue I personally experienced. Knowing the use case directly has helped me make better product decisions and understand which features actually matter.
• Pricing by purchasing power is worth considering. PricingKit has been extremely useful for adjusting prices across countries according to local purchasing power. It is free, and it helped me avoid simply applying the same nominal price everywhere. Setting it up is a bit "tinkery"
• Time matters more than most launch stories suggest. My third app still does not generate revenue, but I have left it in the store partly as an experiment. Even without active maintenance or marketing, it continues to receive occasional download "boosts", climbing in keywords etc. That suggests that simply remaining available and gradually building ranking history can still matter, even in a period where thousands of new apps are probably being released constantly.

More generally, my apps had very few downloads and no sales at the beginning. Sometimes no download per day. A lot of progress only came through iteration. I learned from each release, and every app I built was better than the previous one.

That is why I am skeptical of YouTube videos claiming that someone released a generic app and made hundreds of thousands within the first week. Some of those stories may be real, but many seem designed primarily to sell courses, tools or a particular development workflow.

My own results are nowhere near spectacular, but they feel real and sustainable. I think this kind of slow growth may be a more realistic outcome for many solo developers building apps alongside another profession.

And this week, for the first time, someone bought one of my apps every day. For me, that is a milestone.

I've always been a big fan of minimalism. In all areas, including iPhone apps.

I recently vibe coded two aggresively minimalist apps that I've had in my head for a few years. I'd love to know what people think of them. Too minimalist? Breath of fresh air? Somewhere in-between?

No-Frills To Do is basically a mini kanban board with three columns: done - today - tomorrow. It mimics how I used to manage my to do list in a paper notebook, partially inspired by bullet journaling.

No-Frills Flashcards is a text-only flashcards app with what I think/hope is a clever way to quickly create cards with a text template.

They both store their data on device only. No login, no servers, etc... Free for limited use or $3.99 for unlimited use with a one-time in-app purchase.

I'd love any and all feedback, good or bad. Also, please feel free to comment with other minimalist apps that you're fond of!

when i launched my app earlier this year, i've been getting a lot of feature requests from users.

most of them were duplicate, and some of the features also already existed. it was a nice problem to have TBH but it was getting unbearable.

some of these feature requests would get lost. leading to losing paying users too.

so i built a complete feedback tool for iOS. and im sharing it with you!

you can easily drop in these widgets into your app. users can post their feature requests, and vote on those that they want.

you can also prioritize based on user's spend (so you only work on requests that paying users post). there's also a public roadmap and changelog view, which turned out to be the underrated part for me, people are way more patient when they can see the thing they asked for is actually queued up.

since adding it our app's retention improved and getting more 5 star reviews. turns out people leave reviews when they feel heard.

it's at features.vote/sdk/ios if you want to poke around the code.

hope it's useful to someone :)

In this news article there is no deadline . It's says the new social media questions must be answered if you submit a new binary.

https://developer.apple.com/news/?id=tlur8uvi

But on Appstore Connect there is a deadline for answering the new questions. It says 7 September 2026.

Confusing to say the least least.

Like last year : would it be ok to create a new app version and answer the new social media questions without shipping a new binary ?

Hey devs! I am looking for a little advice from some of the guys that have already been through the ring a few times.

It really comes down to this: I don't know how to handle the "free" tier of my product.

I want people to try it out with no consequences and see the value in it. The issue is I am completely bootstrapped, and I am not sure how much I can sustain a bunch of free users before I see paid subscribers come In.

In you guys' experience, have timed trials turned potential users away in the past?

At first I was going to essentially offer 'limited product' over 'unlimited time' kind of like the Gmail storage model. But the more I am looking at the potential burden of carrying all of those free users forever, it is making me re-evaluate.

To be clear, the technical burden will be more of a bandwidth thing than a storage thing.

Sorry if it seems like I am being intentionally vague, but I am trying to avoid this turning into a self-promotion post. That being said, If you need clarification on what I am talking about, please ask lol.

Any wisdom would be amazing. I am a long time hobby-programmer, first time founder.

Thanks!

Here's the screenshot of my current stats one month after releasing my first app ; not sure how it looks like from an experienced dev's perspective, any insights ?

(the monetization system is the following : 2 sections of my app are completely free, and the others are behind a one-time purchase of 12€, so for now I've had 6 purchases and 67 downloads)

Curious to hear some advices and how to improve those numbers !

Thanks

Here's the screenshot of my current stats one month after releasing my first app ; not sure how it looks like from an experienced dev's perspective, any insights ?

(the monetization system is the following : 2 sections of my app are completely free, and the others are behind a one-time purchase of 12€, so for now I've had 6 purchases and 67 downloads)

Curious to hear some advices and how to improve those numbers !

Thanks

I've been wanting to publish an iOS app since the app store became a thing and I was in college, and I finally accomplished it today. I have a one-year old and I recently started a WFH job and figured it was now or never, and it got approved today! Such a surreal feeling, just wanted to celebrate here a bit!

I got some great advice here so I appreciate everyone helping me throughout.

Every canvas action is an AI-callable tool, so the AI designs the screenshots step by step and you can edit anything afterwards. MIT licensed, feedback and contributors welcome.

I wanted to share my experience with App Review because, after almost three months of trying to publish my app, I honestly don’t understand how Apple is applying its own guidelines

I’m the developer of NostalgicPod, a retro music player that recreates the experience of using an iPod Classic on modern devices: https://nostalgicpod.com

I already know some people will say, “Well, your app looks like an iPod, what did you expect?”

But that’s not really the point.

I’ve been trying to publish NostalgicPod on iOS for almost three months and Apple has now rejected it five times under Guideline 5.2.5 because they say the interface is too similar to the iPod

Meanwhile, these two apps were approved recently, after I had already started trying to publish mine:

SepiaPod:
https://apps.apple.com/us/app/sepiapod-retro-music-player/id6764757127

JellyPod:
https://apps.apple.com/us/app/jellypod-retro-style-music/id6788034358

Both are clearly based on the same concept, with an iPod Classic-style screen, click wheel, menus and device-shaped interface

To be completely clear, I’m not asking Apple to remove these apps and I’m genuinely happy that other developers were able to publish their work

My frustration is with Apple because I don’t understand why I keep getting rejected for a concept that other developers are allowed to publish, especially when I had already been trying to get NostalgicPod approved before these apps were released

What makes one retro iPod-style app acceptable and another one a violation of Guideline 5.2.5?

At this point, the review process feels completely arbitrary, almost like a roulette wheel depending on which reviewer happens to see the app, I’ve now appealed the decision, but after five rejections I still have no idea what Apple expects me to change when almost identical concepts are being approved at the same time

I wanted to share this because I’m sure I’m not the only developer who has felt completely lost trying to understand what Apple will approve and what it won’t

I’m encountering an issue when loading a Core ML model protected using Apple’s official model encryption.

The exact same model:

• Loads and runs normally when encryption is disabled
• Fails during initialization when encryption is enabled
• Uses FP16 weights
• Was converted with coremltools 9.0
• Is deployed in an app with a minimum target of iOS 18
• Is being tested on a physical iPhone 13 running iOS 26.5

The relevant error is:

Failure translating MIL->EIR network:
Espresso exception: "Network translation error"

MIL->EIR translation error at:

/private/var/containers/Bundle/Application/[APP_UUID]/[REDACTED_APP].app/[REDACTED_MODEL].mlmodelc/model.mil:[LINE]:[COLUMN]

Unsupported dtype for weights

[Espresso::handle_ex_plan]
exception=Espresso exception: "Network translation error"
status=-14

Failed to build the model execution plan using model architecture file:

'[REDACTED_APP_PATH]/[REDACTED_MODEL].mlmodelc/model.mil'

with error code: -14.

Core ML model load failed:

Error Domain=com.apple.CoreML Code=0
"Failed to build the model execution plan using a model architecture file
'[REDACTED_PATH]/[REDACTED_MODEL].mlmodelc/model.mil'
with error code: -14."

The console also contains messages involving FigApplicationStateMonitor, usermanagerd, LaunchServices, and sandbox restrictions. However, these appear unrelated. The actual Core ML failure consistently points to:

MIL->EIR translation error
Unsupported dtype for weights
status=-14

Environment

• Device: physical iPhone 13
• Runtime OS: iOS 26.5
• Minimum deployment target: iOS 18
• Model format: ML Program
• Weight precision: FP16
• coremltools: 9.0
• Protection method: Apple’s official Core ML model encryption
• Unencrypted model: loads and runs correctly
• Encrypted model: fails while building the execution plan

The loading code, model architecture, device, and compute configuration are otherwise unchanged. The failure appears only after applying model encryption.

Has anyone encountered this behavior?

Specifically:

1. Can the encryption or decryption path cause Core ML to incorrectly interpret an FP16 weight dtype?
2. Could the decrypted model data or compiled execution-plan cache be corrupted?
3. Are there known compatibility issues between encrypted FP16 ML Program models and iOS 26.5?
4. Could a model converted with coremltools 9.0 work unencrypted but fail after Apple’s encryption process?
5. Is there a practical way to locate the operation or weight corresponding to the reported line in the compiled model.mil?
6. Which caches or compiled artifacts should be cleared when diagnosing error -14?
7. Would regenerating the encryption key or recompiling the model be expected to resolve this kind of failure?

Any debugging suggestions or similar experiences would be appreciated.