Devin vs Poolside
Detailed side-by-side comparison to help you choose the right tool
Devin
🔴DeveloperAI software engineer
Cognition’s cloud software engineering agent for planning, coding, testing, and opening pull requests on delegated engineering tasks.
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Starting Price
$500/moPoolside
AI Coding & Development
Frontier AI research lab building foundation models and enterprise systems for autonomous software development and AGI applications.
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Starting Price
CustomFeature Comparison
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💡 Our Take
Choose Poolside if you need a custom foundation model and multi-agent platform deployed inside your own VPC or on-prem, with Forward Deployed Research Engineers co-owning outcomes in regulated or air-gapped environments. Choose Devin if you want a hosted autonomous engineering agent with public pricing that a team can start using in days rather than running a multi-month enterprise deployment.
Devin - Pros & Cons
Pros
- ✓Better suited than autocomplete for scoped engineering chores and migrations
- ✓Public customer story gives concrete benchmarks: 8–12x efficiency and over 20x cost savings on Nubank migration scope
- ✓Teams plan supports collaboration, billing, admin analytics, and shared usage
Cons
- ✗Requires careful task scoping; vague product work can still go sideways
- ✗Not a substitute for senior engineering judgment, architecture ownership, or review
- ✗Heavy agent sessions can create usage and review overhead if unmanaged
Poolside - Pros & Cons
Pros
- ✓Backed by $626M in total funding including a $500M Series B at a $3B valuation (October 2024), signaling top-tier investor confidence and resources
- ✓Founded by Jason Warner (former GitHub CTO) and Eiso Kant, bringing deep developer-tools and infrastructure expertise at the executive level
- ✓True enterprise deployment model with on-premises, VPC, and air-gapped options — data never leaves the client security boundary
- ✓Forward Deployed Research Engineer model provides joint outcome ownership rather than self-serve software, unique among the 80+ AI coding tools in our directory
- ✓Custom foundation models trained specifically for software engineering, not general-purpose LLMs retrofitted for code
- ✓Works across heterogeneous environments including multi-cloud, legacy systems, and air-gapped networks without rip-and-replace migrations
Cons
- ✗Enterprise-only pricing with no published rates, free tier, or self-serve option — inaccessible to solo developers, startups, or mid-market teams
- ✗Limited public track record and case studies compared to established competitors like GitHub Copilot or Cursor
- ✗Multi-month Forward Deployed Engineer engagements require significant organizational commitment and budget (typically six- to seven-figure contracts)
- ✗Workstation deployment is restricted to defense clients only, limiting flexibility for commercial enterprises that want local-only installs
- ✗Product is still evolving — the platform is being 'battle-tested daily' in enterprise environments rather than shipping a mature, stable feature set
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