App Store Connect CLI, Agents, and Mobile Release Automation With Rudrank Riyam

youtube-cover
Guest
Rudrank Riyam
Creator of ASC CLI & Software Engineer
@
Rork

App Store Connect is not where most mobile developers want to spend their time. Rudrank Riyam built ASC CLI to move release work, metadata updates, feedback, analytics, and App Store workflows into a command-line interface that agents can use.

In this episode, Mike Grabowski talks with Rudrank about building a CLI “by agents and for agents,” why App Store automation still has rough edges, and how open-source tooling changes when the main user might be Codex, Cursor, or another coding agent rather than a person clicking through dashboards.

Episode summary

Rudrank Riyam is a software engineer at Roark and the creator of ASC CLI, an open-source command-line tool for automating App Store Connect workflows. The conversation covers the original TestFlight feedback pain point, the decision to write the CLI in Go, practical workflows such as localization and analytics, lessons from running many agents against one codebase, and what changed after Roark acquired the project while keeping it MIT-licensed and open source.

Why ASC CLI exists

ASC CLI started with a narrow problem: Rudrank wanted to fetch TestFlight feedback without opening App Store Connect, waiting on spinners, or going through Xcode. Fastlane did not cover the endpoint he needed, and the current wave of agentic tooling made a CLI a natural interface. From that first endpoint, the project grew into a broader App Store Connect automation layer that can help agents inspect metadata, screenshots, submissions, reviews, release state, and additional flows such as privacy fields and certificates.

Go, boring patterns, and agent-friendly code

Although Rudrank has spent much of his career writing Swift, ASC CLI is written in Go. The choice was practical: GitHub CLI offered a proven open-source reference architecture, Go is well suited to CLIs, and the coding agents Rudrank tested were more comfortable producing predictable Go than Swift. That “boring” quality mattered. A release automation CLI should be stable, explicit, and easy for both humans and agents to reason about.

From TestFlight feedback to full release workflows

The tool now supports workflows that go well beyond the first TestFlight feedback use case. Rudrank describes agents shipping an app by checking the latest submissions, identifying missing metadata and screenshots, and using App Store Connect API access to move through the release process. For indie developers, the biggest real-world use case has been localization: asking an agent to translate app titles, subtitles, descriptions, and keywords into multiple languages, then applying those changes without repeating App Store Connect UI work twenty times.

What agent-built projects teach about architecture

Rudrank pushed ASC CLI forward with multiple agents working in parallel, sometimes overnight. But that speed came with a cost: early commands and file structures became inconsistent because agents were solving separate parts without shared context. The project had to go through heavy deprecation and refactoring before the 1.0 release. His main takeaway: agents move faster when the codebase has clear modules, separate concerns, small files, and an agents.md that explains how work should be done.

Building for agents without forgetting developers

A recurring point in the episode is that patterns that help humans also help agents. Clean file structure, obvious command naming, discoverable modules, and reliable verification all reduce token waste and make contributions easier. That matters because many ASC CLI contributors are also using agents to open issues and pull requests. Rudrank even added an asc snitch command so an agent can report friction it encounters while using the CLI.

Open source after Roark

Roark first sponsored the project, then acquired it and hired Rudrank. He was clear that ASC CLI had to remain MIT-licensed and open source, and Roark agreed. The day-to-day work still looks community-driven: issues arrive, contributors send pull requests, Rudrank reviews and releases. Internally, Roark uses the CLI for app publishing workflows, while the wider community continues to shape the public tool.

Listen to the episode to learn how ASC CLI turns App Store Connect into an agent-readable interface for real app publishing workflows.

Resources

Insights

Learn more about AI

cover

Nov 17Talk

Efficient On-Device LLMs in React Native Done Right

Artur Morys-Magiera will cover efficient on-device LLMs in React Native, including runtimes, model selection, quantization, and platform constraints.

cover

Nov 17Talk

On-Device AI After WWDC: What Changed for React Native

Mike Grabowski will explain what changed for system-provided on-device AI after WWDC and what React Native developers can build with it.

cover

Nov 16Talk

Beyond Coding Agents: Making ADLC Work Across Platforms

Mike Grabowski will explain how to close the full agentic development lifecycle across mobile, web, and native platforms.

Building the React Native Software Factory — cover

Nov 11Talk

Building the React Native Software Factory

Join us at React Foundation Meetup London on November 11 to explore how AI agents build and debug React Native apps, from one terminal to the cloud.

Building a Software Factory: Write Specs an Agent Can Build From — cover

Nov 6Article

Building a Software Factory: Write Specs an Agent Can Build From

Learn how to research requirements, resolve open decisions, and write testable specs that AI coding agents can implement without the planning conversation.

 Large-Scale Migrations With Coding Agents: Planning, Verification, and Rollback — cover

Nov 4Article

Large-Scale Migrations With Coding Agents: Planning, Verification, and Rollback

Plan codebase migrations with coding agents using reviewable requirements, verification checks, staged rollouts, and defined rollback criteria.

Quantization Impact on LLM Quality: A Case Study of Apex — cover

Nov 4Talk

Quantization Impact on LLM Quality: A Case Study of Apex

Artur Morys-Magiera and Lech Kalinowski share findings from 344 benchmark runs with Apex, our Gemma-based LLM, examining the trade-offs between model size, decode speed, and quality.

Conversational Banking: From Customer Questions to Authorized Actions — cover

Nov 2Article

Conversational Banking: From Customer Questions to Authorized Actions

Explore conversational banking architecture through a card-dispute example, covering tool access, authorization, execution, observability, and human handoff.

Building a Software Factory: The Night My Agents Waited for Me — cover

Oct 28Article

Building a Software Factory: The Night My Agents Waited for Me

Learn how permissions, review limits, and missing product decisions stalled two overnight coding agent runs, and how their maintainer revised the workflow.