Firebender

What do they actually do

Firebender is an AI coding assistant that runs as a plugin inside Android Studio and other JetBrains IDEs. You install it from the JetBrains Marketplace or their site, then use an in‑IDE chat and inline edit UI to ask questions about your codebase and make natural‑language edits that stream back into your files (plugin; Quickstart).

Beyond reading source, it integrates with Android‑specific tools like Logcat, the emulator, Layout Inspector, and Compose previews so the assistant can inspect runtime behavior and rendered UI instead of relying only on static code. Firebender also ships “Composer,” a research preview that turns Figma designs into Jetpack Compose code and iterates using live previews for better pixel accuracy (Compose blog; docs: Compose previews).

It supports multi‑agent workflows (e.g., “plan” vs “heavy” modes, custom sub‑agents and slash‑commands) and exposes experimental features like a “mobile‑use” agent that can control/test a device. The team ships frequent updates (public changelog) and emphasizes enterprise needs like SSO and privacy/no training on customer code (multi‑agent, commands, experimental, changelog, security/trust). They and their community also claim daily use among engineers at companies like Tinder and Instacart, though these are team/community claims rather than independent audits (YC profile; Reddit AMA).

Who are their target customer(s)

• Android engineers shipping features in Android Studio/IntelliJ: They spend time understanding unfamiliar code and writing repetitive edits or refactors; they want faster, less error‑prone changes without leaving the IDE.
• Mobile engineers debugging crashes and runtime issues: They context‑switch between logs, emulators/devices, and source files to reproduce and fix issues; they need tooling that reads logs and inspects rendered screens to speed up fixes.
• Designers/engineers handling Figma → Jetpack Compose handoff: Manual translation from designs to code and then chasing pixel/animation mismatches is slow; they want a more reliable way to convert and validate UI output in previews.
• Engineering teams running refactors or multi‑step fixes/onboarding: Repeated edits across files and multi‑step workflows are tedious to coordinate; they want orchestrated, automatable flows that operate inside the IDE.
• Security/compliance‑conscious orgs evaluating AI dev tools: They worry about code exposure and model training on private code; they need SSO, privacy assurances, and compliance signals before adopting a tool.

How would they acquire their first 10, 50, and 100 customers

• First 10: Directly recruit Android engineers and small teams from developer channels (JetBrains plugin page, r/androiddev, Discord, YC network) and offer concierge onboarding and one‑off fixes to prove value quickly (plugin; AMA; YC).
• First 50: Run hands‑on tutorials and live workshops at Android meetups/conferences; publish Composer demos and sample projects; convert attendees with time‑limited trials and streamlined in‑IDE onboarding (Quickstart/docs; Composer blog).
• First 100: Package pilots for mid‑size/enterprise mobile teams (SOC 2/SSO, clear success metrics like faster bug‑fixes/UI handoff) and publish benchmarks/case studies to reduce procurement friction (trust, multi‑agent docs, Kotlin‑bench).

What is the rough total addressable market

Top-down context:

SlashData estimates there are about 17.7M mobile developers in 2024; Statista reports 87% of mobile developers target Android, implying roughly 15M Android‑targeting developers (SlashData; Statista). Android Studio is the official IDE for Android development, so most of these developers are reachable via JetBrains‑based IDEs (Android Developers).

Bottom-up calculation:

Assuming ~15M Android‑targeting developers, ~80% using Android Studio, and $30/user/month ($360/year), the annual TAM for an Android‑focused in‑IDE AI assistant is ≈ 12M seats × $360 ≈ $4.3B.

Assumptions:

• Share of mobile developers targeting Android ≈87% (applied to 17.7M mobile devs)
• ~80% of Android developers primarily use Android Studio (official IDE, estimated share)
• Pricing assumed at $30/user/month ($360/year), comparable to AI IDE assistants

Who are some of their notable competitors

• GitHub Copilot: General in‑IDE AI pair programmer with autocomplete, chat, and edits inside JetBrains/Android Studio; overlaps on code chat/edits but isn’t focused on Android runtime tooling or Figma→Compose workflows.
• Sourcegraph Cody: IDE chat plus whole‑repo code search with enterprise options and LLM choice; strong on "ask the codebase" and cross‑repo context rather than Android emulator/Layout Inspector or Compose preview loops.
• Tabnine: AI code completions and inline suggestions with on‑prem options; improves general productivity but lacks Android‑specific runtime integrations or UI preview‑driven generation.
• Codeium: Completions and edits with enterprise deployment; focuses on generic IDE assistance rather than Android emulator/Layout Inspector or Figma→Compose conversion.
• Amazon (CodeWhisperer → Amazon Q): Amazon’s developer AI in JetBrains offering code suggestions and AWS‑centric guidance/security; overlaps on in‑IDE help but emphasizes AWS toolchain integrations over Android runtime/UI generation flows.