Pieces for Developers: A Cursor Alternative for On-Device AI with Long-Term Memory

Pieces for Developers is an on-device AI coding assistant and long-term memory engine developed by Mesh Intelligent Technologies, a Cincinnati-based software company. Unlike cloud-dependent coding assistants, Pieces runs locally on your machine and captures context at the operating system level — tracking activity across browsers, IDEs, terminals, and collaboration tools in real time. It integrates with VS Code, JetBrains, Chrome, Firefox, and more than 15 developer tools to provide AI-powered code assistance that is grounded in what you've actually been working on, not just what's currently open in your editor. More than 150,000 developers use Pieces for its core differentiator: the LTM-2 (Long-Term Memory v2) engine, which enables time-based memory queries like "what was I debugging last Tuesday?" and automatic stand-up generation from your recent activity. Pieces supports BYOK (bring your own key) with OpenAI, Anthropic, and local Ollama models, keeping sensitive code and context entirely on-device by default.

Key Strengths

• LTM-2 long-term memory engine: Pieces' most distinctive capability is its persistent memory system, which captures and indexes your development activity — code snippets, browser searches, terminal commands, meeting notes — and makes them queryable over time. Developers can ask questions like "what API did I look at three days ago?" or "show me the snippet I saved while reading the AWS docs last week" and get accurate, contextual answers.
• OS-level cross-application context capture: Unlike IDE-bound tools that only see what's open in your editor, Pieces monitors context across your entire development environment: browsers, Slack, Teams, Zoom, terminal sessions, and IDE windows. This creates a holistic picture of your development context that allows the AI to give more relevant suggestions and understand the full scope of what you're working on.
• On-device by default with full BYOK flexibility: All captured context and AI processing runs locally by default. Developers who work with proprietary or sensitive codebases can use Pieces without any code leaving their machine. BYOK support for OpenAI, Anthropic, and Ollama means you choose where inference happens.
• Automatic stand-up generation: Pieces can generate daily stand-up notes automatically from your captured activity — summarizing what you worked on, what's in progress, and what blockers you encountered. For teams with daily standups, this alone can save meaningful time each day.
• Broad IDE and tool integration: With integrations for VS Code, JetBrains (IntelliJ, PyCharm, WebStorm, etc.), Chrome, Firefox, and over 15 tools, Pieces works inside developers' existing environments rather than requiring them to switch to a new editor or interface.

Known Weaknesses

• No built-in real-time autocomplete: Pieces' Copilot provides conversational AI assistance and context-aware code generation, but it does not offer Cursor-style ghost-text Tab completions as you type. Developers who rely heavily on inline autocomplete as their primary interaction model will find Pieces' approach different and potentially less fluid for moment-to-moment coding.
• Team pricing is opaque: While the individual plan is free, team pricing requires contacting Pieces directly — there are no publicly listed per-seat rates. This makes it harder for teams to budget upfront or compare costs against alternatives without going through a sales conversation.
• Context capture can raise privacy questions in shared environments: The OS-level activity capture that makes Pieces powerful also means it records a broad range of developer activity. In shared workstations, contractor setups, or environments with strict audit requirements, the scope of what Pieces captures may require careful configuration and policy review.

Best For

Pieces for Developers is best suited for developers who context-switch frequently across multiple projects, tools, and browsers and need AI assistance that understands their full work history — not just the current file. It's particularly valuable for engineers doing research-heavy work (reading documentation, comparing APIs, evaluating libraries), for teams that want to generate standups automatically, and for individuals or organizations that need all AI processing to remain on-device for security or compliance reasons. JetBrains users in particular will appreciate having an AI assistant that works natively in their IDE without switching to a VS Code-based editor.

Pricing

• Free (individual): Full access to Pieces Copilot, LTM-2 memory engine (9-month context window), basic AI features, BYOK for OpenAI/Anthropic/Ollama. No credit card required.
• Teams: Extended context window (9+ months), team-level memory sharing, BYOM (bring your own model), admin controls. Contact Pieces for pricing.
• Enterprise: Custom deployment, SSO, compliance features — contact Mesh Intelligent Technologies for details.

Technical Details

• Core technology: LTM-2 (Long-Term Memory v2) local indexing engine
• Platforms: macOS, Windows, Linux (desktop app); VS Code, JetBrains (IDE extensions); Chrome, Firefox (browser extensions)
• Model support: BYOK — OpenAI (GPT-4o, GPT-4.1), Anthropic (Claude 3.x), Ollama (local models)
• Data residency: On-device by default; no code leaves the machine without explicit configuration
• MCP integration: Yes (Model Context Protocol tool integrations)
• Context window: 9-month activity history (individual), extended for teams
• Users: 150,000+
• Open source components: Selective; core proprietary with open source SDK

How It Compares to Cursor

Cursor and Pieces operate in meaningfully different product categories. Cursor is a real-time AI IDE that augments the moment-to-moment act of writing code — Tab completions, inline diffs, and an editor-bound chat panel. Pieces is an AI memory and context layer that sits across your entire development environment and provides assistance grounded in your full work history, not just the current file. In practice, Pieces and Cursor are more complementary than competitive: many developers use Cursor for active coding sessions while using Pieces to retrieve snippets, understand historical context, and generate standups. However, for developers who primarily want AI assistance that works across JetBrains IDEs, stays on-device, and remembers their work over weeks and months, Pieces directly addresses gaps that Cursor does not.

Conclusion

Pieces for Developers fills a specific and underserved niche in the AI coding assistant market: persistent, on-device, cross-application developer memory. Its LTM-2 engine, OS-level context capture, and BYOK flexibility make it a compelling tool for developers who want AI assistance that grows smarter over time with their own work history. For teams that need AI to stay on-device for compliance reasons, for JetBrains users who want native IDE integration, or for any developer who wants their AI to remember what they were working on last week, Pieces offers capabilities that are genuinely difficult to find elsewhere.

Sources

• pieces.app — Official website
• github.com/pieces-app
• docs.pieces.app — Official Documentation

FAQ