AI snippet manager that saves, enriches, and generates your code

Built with Pieces?
Let's make sure it's production-ready.

An AI-powered developer tool for saving, enriching, and reusing code snippets, with an AI assistant that helps generate and explain code in context. Maintains a personal library of snippets across projects and IDEs. We help non-technical founders identify and fix the issues AI tools leave behind.

TypeScriptPythonDartFlutterReact

Common issues we find in Pieces code

These are real problems we see in Pieces projects during our audits — not hypotheticals.

highBugs

Saved snippets used out of original context introduce bugs when reused

Code snippets saved from one project often have implicit dependencies — specific utility functions, environment variables, or framework versions — that are not present in the project where the snippet is reused, causing silent failures or runtime errors.

highSecurity

Security-sensitive snippets like auth helpers reused across projects with different requirements

Authentication, token validation, and cryptography snippets saved from one project may use algorithms or key lengths appropriate for that context but inadequate for a different security model, spreading security assumptions that do not apply.

mediumCode Quality

Version drift as saved snippets fall behind updated library APIs

Snippets saved against older versions of React, Dart, or TypeScript accumulate as libraries update, resulting in a snippet library that increasingly uses deprecated APIs or patterns that generate deprecation warnings or compilation errors in new projects.

mediumCode Quality

Mixed coding patterns from different projects used inconsistently in the same codebase

When developers pull snippets from different projects saved in Pieces, each snippet may follow a different style — one uses async/await, another uses callbacks; one uses Tailwind, another uses CSS modules — creating inconsistency within the target project.

mediumBugs

Flutter and Dart snippets include platform-specific code not guarded by platform checks

Mobile code snippets may use platform-specific APIs (iOS haptics, Android back-button handling) without the appropriate platform guards, causing runtime crashes on the other platform when reused.

mediumTesting

Snippets generated by AI without test coverage used as foundational code

AI-generated snippets in Pieces are treated as ready-to-use building blocks, but they come without tests. When these snippets are used as the foundation for new features, the testless pattern propagates into the new codebase.

lowPerformance

Large snippet usage contributes to bundle bloat through duplicated utility code

Reusing snippets that implement utility functions rather than importing from a shared library leads to multiple copies of the same logic across the codebase, increasing bundle size and creating maintenance overhead when the logic needs to change.

mediumDeployment

Snippet metadata and AI enrichment do not capture deployment environment requirements

Pieces' AI-enriched snippet descriptions explain what code does but do not capture environment-specific requirements — Node.js version, OS dependencies, required environment variables — leading to deployment failures when snippets are used in different environments.

Start with a self-serve audit

Get a professional review of your Pieces project at a fixed price. Results reviewed by experienced engineers.

Security Scan

Black-box review of your public-facing app. No code access needed.

$19
  • OWASP Top 10 checks
  • SSL/TLS analysis
  • Security headers
  • Expert review within 24h
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Code Audit

In-depth review of your source code for security, quality, and best practices.

$19
  • Security vulnerabilities
  • Code quality review
  • Dependency audit
  • AI pattern analysis
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Best Value

Complete Bundle

Both scans in one package with cross-referenced findings.

$29$38
  • Everything in both products
  • Cross-referenced findings
  • Unified action plan
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100% credited toward any paid service. Start with an audit, then let us fix what we find.

How it works

1

Tell us about your app

Share your project details and what you need help with.

2

Get a clear plan

We respond in 24 hours with scope, timeline, and cost.

3

Launch with confidence

We fix what needs fixing and stick around to help.

Frequently asked questions

How does Pieces store my code snippets and is it secure?

Pieces stores snippets locally on your machine by default, with an optional cloud sync feature. Local storage means your code does not leave your machine unless you enable sync. The cloud sync feature encrypts snippets in transit and at rest. For proprietary code, the local-first default is a strong privacy posture.

What is the best way to keep Pieces snippets from becoming outdated?

Add library versions to your snippet titles or tags when you save them (e.g., 'React 18 useEffect pattern'). Periodically audit your snippet library — set a quarterly reminder to review commonly used snippets for API deprecations. When a library releases a major version, search Pieces for snippets that use that library and update or archive them.

How does Pieces AI differ from GitHub Copilot for day-to-day coding?

Pieces AI is centered on your personal snippet library — it generates and explains code in the context of what you have saved. Copilot is a real-time completion tool in your editor. They solve different problems: Pieces is better for building and reusing a personal knowledge base, while Copilot is better for moment-to-moment code generation. Many developers use both.

Can Pieces help with Flutter and mobile development specifically?

Pieces works well with Flutter and Dart — you can save widget patterns, state management snippets, and platform-specific code. The AI assistant understands Dart and Flutter context. The main caution is around platform-specific snippets: always verify that iOS-only or Android-only code is properly guarded when reusing across platforms.

Does Pieces work offline or does the AI require an internet connection?

Core snippet storage and retrieval in Pieces works offline. The AI assistant features require a connection to the AI backend. Pieces also supports using your own API keys for models like GPT-4 or Claude, giving you control over which model powers the AI features and the associated costs.

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