Software that evolves from the people who use it. Not a buzzword. An architecture. A fundamentally different relationship between apps and their users.
Every piece of software starts decaying the moment it launches. Users encounter friction. Their needs change. The market shifts. Competitors release something new.
The traditional response is a human-powered feedback loop: collect feedback (slowly), prioritize it (subjectively), build it (expensively), ship it (eventually). This cycle takes weeks. Often months. Sometimes it never happens at all.
Meanwhile, the gap between what users need and what the app provides grows wider every day.
Self-living software closes this gap automatically.
Five principles. One continuous loop.
A built-in feedback widget captures what users think — in context, in the moment, with minimal friction. Not surveys. Not analytics. Real words from real people.
The widget is embedded in every Chorus app. One tap, type what you're thinking, submit. 10 seconds. Because it's low-friction, you hear from the 20% of users who would never email your support team.
The AI doesn't just collect feedback — it interprets it. "The search is broken" might mean the index is slow, the results are irrelevant, or the UI is confusing.
The Analyst agent reads between the lines. It examines the user's context, cross-references with existing codebase knowledge, identifies patterns across multiple reports, and determines root cause vs. symptom.
The AI team generates a plan, implements the changes, and runs them through quality gates — type checking, test validation, and deployment verification.
Specialized agents handle different aspects: the Lead coordinates, Dev writes code, QA reviews, Design advises on UI. It's not one AI trying to do everything. It's a structured team with checks and balances.
The improvement goes live. The user who reported the issue sees it fixed. The feedback loop closes in minutes, not sprints.
Every change flows through GitHub (your repo) → Vercel (your hosting) → production. You can see every commit, every deployment, every change in your own dashboards.
Each cycle teaches the system more about what your app's users care about, what patterns cause problems, and what changes make things better.
Over time, the AI team develops a deep understanding of your specific app, your users' expectations, and your design preferences. The 50th improvement is smarter than the first.
Not every app needs to be fully autonomous. Self-living software is a spectrum. You choose where on it your app lives.
Traditional app. Feedback goes to a backlog. Humans do everything. Changes ship on a schedule.
App collects feedback. AI analyzes and suggests. Humans approve and deploy.
Routine changes ship automatically. Major changes need approval. This is Chorus's default.
← Chorus default. Most users land here.
All feedback is analyzed, implemented, tested, and deployed without human intervention.
Not autopilot
You're still in control. Configure which changes auto-deploy and which need approval. Security changes always require human sign-off.
Not ai slop
Every change goes through quality gates: type checking, test validation, and deployment verification. Broken code doesn't ship.
Not a replacement for developers
If you have a dev team, Chorus orchestrates feedback analysis while your team does implementation. Self-living ≠ no humans.
Not magic
The AI isn't perfect. It sometimes misunderstands. That's why there are controls, gates, and approvals. It's a system, not a genie.
Large language models can generate, modify, and debug production code reliably enough to handle the majority of routine changes that make up an app's evolution.
GitHub, Vercel, Supabase — the entire deployment stack is programmable. An AI agent can modify code, trigger builds, run tests, and deploy to production through API calls.
A persistent, embedded mechanism for users to tell the app what they want — in context, in the moment, with minimal friction. The critical innovation that closes the loop.
60–80%
of a software product's total lifetime cost is maintenance — not initial development.
Self-living software attacks this directly. Not by eliminating maintenance cost, but by making it continuous and automatic instead of periodic and manual. When a confusing label gets fixed the day someone reports it instead of three sprints later, that's not just faster — it's fundamentally cheaper.
Build an app. Use it. Submit feedback through the widget. Watch your app evolve. That's self-living software.
Start building — freeFree credits on signup. No API key needed to start.