scritty vs Cognition AI

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-10-30
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scritty or Cognition AI: which should you choose?

DimensionscrittyCognition AI
PricingFreeFreemium (enterprise pricing undisclosed)
Target AudienceIndividual developers & teams using AI agentsEnterprise engineering teams
Core FunctionShared memory for AI agentsAutonomous software engineer
IntegrationsVSCode, JetBrains, CLI (no native integrations listed)GitHub, Slack, Jira, Linear, Datadog, Windsurf, Android Emulator, Windows VM
Key DifferentiatorPersistent, shared context across multiple AI agentsEnd-to-end multi-step task execution with productivity guarantee

If you're an enterprise team needing an autonomous agent that plans, codes, and ships production code end-to-end, Cognition AI's Devin is the clear choice—it's backed by a $10M guarantee and Fortune 500 deployments. For individual developers or small teams using multiple AI coding assistants who want persistent, shared memory across sessions, Scritty is a free, lightweight solution that solves context repetition. They address completely different problems: autonomous engineering vs. context sharing.

scritty
scritty

A terminal emulator that captures every AI coding agent turn you run inside it and makes that memory searchable across providers.

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Cognition AI
Cognition AI

Cognition's Devin is an autonomous AI software engineer that plans, writes, tests and ships merge-ready pull requests

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Pricing
Free
Contact Sales
Plans
FreeFree
EnterpriseCustom
Popularity
7 views
7.3k views
Skill Level
Intermediate
Advanced
API Available
Platforms
DesktopWebMobile
WebMobileDesktopAPICLI
Categories
🔌 MCP Servers & Agent Tooling💻 Code & Development
🛠️ Autonomous Coding Agents
Features
Terminal emulator with auto-capture of prompts and responses from supported AI coding CLIs
Agent detection and turn attribution for Claude Code, OpenAI Codex CLI, GitHub Copilot CLI, Gemini CLI, Antigravity CLI, xAI Grok CLI and local Ollama
Hybrid vector + keyword search across all agents and sessions (Ctrl+Shift+M)
MCP server so your agents can query the shared corpus directly
CLI memory search and session management
Rules engine injecting prompt.toml standing instructions on every send (Ctrl+Shift+R)
Hard enforcement rules injected on every message (Ctrl+Shift+E)
Goal state kept in front of the agent to prevent drift (Ctrl+Shift+G)
Reads native vendor rule files: CLAUDE.md, AGENTS.md, copilot-instructions.md, GEMINI.md
Live per-section toggles for each rules layer from inside the terminal
Browser sync of the same PTY and memory panel via token-secured embedded web server
Installable PWA with a standalone app window in Chrome or Edge
Phone pairing via QR code over an explicit Tailscale Funnel opt-in, with reconnect
TLS always on, bearer tokens stored as hashes, CIDR allowlist, loopback-only by default
Pluggable vector backends: qdrant, pgvector, chroma, weaviate
Autonomous planning, coding, testing and pull request creation in your repository
SWE-2 coding model with multiple effort levels (September 2026)
SWE-1.7 coding model positioned as frontier intelligence at lower inference cost
Fusion model harness for Fable and Astra in Devin Desktop and CLI, up to 39% efficiency claim
FrontierCode 2.0 benchmark scoring merge-worthiness rather than test-passing
Auto-Triage of monitored bugs with automated fix pull requests
Security Vulnerability Remediation Program for clearing backlog findings
Session persistence so long-running jobs survive restarts
Scheduled Sessions that retain state across recurring runs
Auto-fixes for review comments on open pull requests
Embedded IDE takeover plus an interactive browser the agent drives itself
Devin for Terminal CLI with handoff into a cloud session
Voice mode for instructing Devin inside a session
Native Windows VMs and an Android emulator for mobile testing
Devin Desktop and mobile apps for monitoring sessions
Integrations
Tailscale
MCP
Slack
Microsoft Teams
GitHub
GitLab
Bitbucket
Linear
Jira
Databricks
MongoDB
PagerDuty
Pylon

Who should pick scritty, and who should pick Cognition AI?

  • Enterprise engineering manager
    Pick: Cognition AI

    Devin can autonomously handle multi-step tasks like bug triage, test generation, and cross-platform builds, integrating directly with existing enterprise tools (GitHub, Jira, Datadog). The $10M productivity guarantee and Fortune 500 deployments provide trust.

  • Solo developer using multiple AI assistants
    Pick: scritty

    Scritty's free shared memory eliminates the need to repeat context across Cursor, Copilot, Claude, etc. It's lightweight, persistent, and works with editors and CLI.

  • Team working on legacy COBOL modernization
    Pick: Cognition AI

    Cognition AI specifically includes COBOL modernization as a capability, and Devin can handle the complex, multi-step analysis and code changes needed.

  • Developer concerned about privacy
    Pick: scritty

    Scritty offers local storage for privacy; Devin is cloud-based and enterprise-focused. Scritty's free tier with local-only option is better for sensitive projects.

  • Team needing end-to-end automated PR creation
    Pick: Cognition AI

    Devin autonomously creates PRs with merge-worthy code, as measured by FrontierCode. It can also auto-fix review comments, reducing human overhead.

Frequently Asked Questions

scritty vs Cognition AI: which should you choose?

If you're an enterprise team needing an autonomous agent that plans, codes, and ships production code end-to-end, Cognition AI's Devin is the clear choice—it's backed by a $10M guarantee and Fortune 500 deployments. For individual developers or small teams using multiple AI coding assistants who want persistent, shared memory across sessions, Scritty is a free, lightweight solution that solves context repetition. They address completely different problems: autonomous engineering vs. context sharing.

Can Scritty work with Devin?

Yes, technically you could use Scritty to store context that Devin could query, but Scritty is designed for assisted agents (Copilot, Cursor) while Devin is autonomous. There's no official integration.

Is Devin free to try?

Cognition AI offers a freemium tier, but advanced features likely require paid enterprise plan. Specific pricing is not public.

Does Scritty support team collaboration?

Yes, Scritty supports cloud-synced memory for teams, though there's no on-prem option yet.

Which tool is better for CI/CD integration?

Devin integrates with GitHub for auto-PRs and with Datadog for monitoring; Scritty has no native CI/CD integration.

Can I use Scritty without a cloud account?

Yes, Scritty offers local storage for privacy, so cloud syncing is optional.

Does Devin work with Android emulator natively?

Yes, Devin includes Android emulator integration for testing mobile apps.

What programming languages do they support?

Devin is language-agnostic (handles any language its VM supports); Scritty is memory-agnostic, storing context regardless of language.

Which tool has better support?

Devin, with enterprise backing and $10M guarantee, likely offers dedicated support; Scritty is community-supported for now.

What else are scritty and Cognition AI compared with?

Where can you read more about scritty and Cognition AI?

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