# Pensero > Pensero is the operating system for the agentic software development lifecycle (agentic SDLC). It measures the work of humans, AI-assisted engineers and agents on one scale, pinpoints the next move and helps teams prove it worked. Key facts: - Plans: Starter (free, self-serve), Pay as you go (billed monthly on what you use) and Enterprise (custom: a 6-week audit, then the Agentic Transformation Program billed per phase, then an annual platform license with no per-seat charge). Pensero publishes no per-seat or per-user prices. - The 5 levels of AI in engineering: human-only, AI-assisted, AI reviews, orchestrated agents, fully autonomous agents. - Measures delivered work by size and difficulty, with cost and quality, for humans, AI-assisted engineers and agents. - Deployment: Pensero Cloud, EU-based deployment, your own cloud or on-premises. - Offices: New York, Barcelona and Madrid. Founders: Dave Garcia and Bernardo Hernández (Co-CEOs). CTO: Ivan Peralta. - Privacy: measures teams and types of work, not individuals. No keystroke monitoring. ## Product - [Platform overview](https://pensero.ai/): delivery, quality, AI impact, talent, benchmarking, and CapEx visibility for engineering organizations - [Next moves](https://pensero.ai/platform/next-moves): what to scale, change, hand to agents or stop - [How it works](https://pensero.ai/how-it-works): the 6-week audit, the Agentic Transformation Program and the platform - [Integrations](https://pensero.ai/integrations): supported tools across the delivery stack - [About](https://pensero.ai/about): the team, the offices and the founders - [Enterprise](https://pensero.ai/landing/enterprise): R&D capitalization, on-prem, custom integrations, priority support - [Security](https://pensero.trust.site/): security posture and compliance documentation ## Customers - [SEAT CODE case study](https://pensero.ai/customers/seatcode): AI scaled from 5 pilot teams to the whole engineering organization, with one objective measure for each next investment - [Stord case study](https://pensero.ai/customers/stord): 25% velocity gain and automated R&D capitalization - [ClosedLoop case study](https://pensero.ai/customers/closedloop): mixed human and agent teams, 4x faster delivery and 80% fewer defects - [Persuit case study](https://pensero.ai/customers/persuit): 2.5x delivery points per engineer, with quality held - [Exoticca case study](https://pensero.ai/customers/exoticca): 39% shorter cycle time and 140% more delivery - [Cubbo case study](https://pensero.ai/customers/cubbo): maintenance load reduced from 70% to 30% of engineering time - [Zynap case study](https://pensero.ai/customers/zynap): clarity on engineering performance, AI adoption and product alignment ## Guides - [How to Measure the ROI of AI Coding Tools](https://pensero.ai/blog/measure-roi-ai-coding-tools): framework for proving AI tooling value - [The AI Quality Tax](https://pensero.ai/blog/ai-quality-tax): why AI-assisted code can mean more rework, and how to manage it - [AI Coding Tool Efficiency Metrics in 2026](https://pensero.ai/blog/ai-coding-tool-efficiency): the metrics that matter for AI-assisted development - [Your AI Spend Is Compounding: How to Control It](https://pensero.ai/blog/compounding-ai-spend): managing AI cost growth across engineering - [Guide to Capitalizing Software Development Costs](https://pensero.ai/blog/capitalizing-software-development-costs): R&D capitalization for engineering and finance leaders - [How to Benchmark Engineering Team Performance](https://pensero.ai/blog/benchmark-engineering-team-performance): comparing your org against industry peers - [Best Engineering Delivery Metrics to Track](https://pensero.ai/blog/engineering-delivery-metrics): choosing delivery metrics that reflect real output - [How to Measure and Improve Engineering Delivery Performance](https://pensero.ai/blog/engineering-delivery-performance): a practical delivery-performance playbook - [Engineering Cycle Time and How to Reduce It](https://pensero.ai/blog/engineering-cycle-time): definition, measurement, and reduction tactics - [How to Shift Engineering Maintenance vs. Innovation](https://pensero.ai/blog/engineering-maintenance-vs-innovation): rebalancing KTLO against roadmap work - [Contractors vs Full-Time Engineers: Who Delivers More?](https://pensero.ai/blog/contractors-vs-full-time-engineers): comparing cohorts with delivery data - [How to Measure New Hire Ramp-Up Time](https://pensero.ai/blog/hire-ramp-up-time-engineering): onboarding effectiveness metrics ## Comparisons - [Pensero vs Jellyfish](https://pensero.ai/landing/jellyfish): how Pensero differs from Jellyfish - [Pensero vs LinearB](https://pensero.ai/landing/linearb): how Pensero differs from LinearB - [Jellyfish vs DX](https://pensero.ai/blog/jellyfish-vs-dx): independent comparison of the two platforms - [Jellyfish vs LinearB 2026](https://pensero.ai/blog/jellyfish-vs-linearb): which engineering intelligence platform fits which team - [Jellyfish vs Swarmia](https://pensero.ai/blog/jellyfish-vs-swarmia): comparison for 2026 - [LinearB vs DX 2026](https://pensero.ai/blog/linearb-vs-dx): two different answers to the same problem - [DX vs Swarmia 2026](https://pensero.ai/blog/dx-vs-swarmia): developer-focused platform comparison ## Glossary - [Glossary index](https://pensero.ai/glossary): ~100 definitions of engineering performance terms - [Software Engineering Intelligence](https://pensero.ai/glossary/software-engineering-intelligence): what an SEI platform is - [Cycle Time](https://pensero.ai/glossary/cycle-time): definition and why it matters - [Change Failure Rate](https://pensero.ai/glossary/change-failure-rate): DORA quality metric explained - [Lead Time for Changes](https://pensero.ai/glossary/lead-time-for-changes): DORA delivery metric explained - [Developer Productivity Metric](https://pensero.ai/glossary/developer-productivity-metric): how productivity is measured - [KTLO](https://pensero.ai/glossary/ktlo): keeping the lights on — maintenance work defined - [Technical Debt Ratio](https://pensero.ai/glossary/technical-debt-ratio): quantifying tech debt - [Rework](https://pensero.ai/glossary/rework): rewritten code as a quality signal ## Optional - [Full reference for AI assistants](https://pensero.ai/llms-full.txt): key facts, plans, the 5 levels, customer evidence and FAQs - [Blog index](https://pensero.ai/blog): 200+ articles on engineering metrics, AI adoption, and team performance - [Other resources](https://pensero.ai/blog/other-resources): additional articles and resources - [Careers](https://pensero.ai/careers) - [Support](https://pensero.ai/support) - [Terms of service](https://pensero.ai/terms) - [Privacy policy](https://pensero.ai/privacy-policy) - [Book a demo](https://pensero.ai/book-demo)