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The New Waydev

Updated July 24, 2026

Overview / Description

Waydev is an AI engineering intelligence platform that tracks agent-generated code from IDE to production for engineering leaders, managers, and C-level executives at mid-to-large software organizations. It answers the question most teams cannot yet answer: what percentage of AI-written code actually ships to customers.

At the core of Waydev is its AI Checkpoints feature, which monitors every AI coding agent — Copilot, Cursor, Claude Code, and others — capturing which agent wrote each PR, how many tokens were consumed, the cost per PR, the acceptance rate, and the deployment status. This lets engineering leaders compare vendors not on demo metrics but on what actually reaches production.

Waydev measures engineering productivity using three established frameworks: SPACE (Satisfaction, Performance, Activity, Communication, Efficiency), DORA Metrics (deployment frequency, lead time, change failure rate, mean time to recovery), and Developer Experience (DX) analysis. These are combined with AI Adoption, AI Impact, and AI ROI dashboards so executives can see whether AI tooling is translating into business outcomes.

The platform is organized into five modules — Automation, Delivery, Health, Planning, and Studio — and generates executive-ready reports including Resource Planning, Project Costs, and Custom Dashboards. Claimed outcomes from the homepage include a 22% faster time to market, 2.2x velocity improvement, 28% faster cycle time, and 28% reduction in code churn. Waydev is backed by Y Combinator and rated a G2 Market Leader in 2025.

Pricing is tiered by engineering team size, covering Small (10–50 engineers), Medium (50–500 engineers), and Enterprise (500–5,000 engineers, demo-based). A free trial is available.

Used For

Engineering leaders and C-level executives at mid-to-large software organizations use Waydev to measure AI coding agent adoption, compare vendor ROI, and track engineering productivity using SPACE, DORA, and DX frameworks.

Pricing

Plan

Free

Small (10–50 engineers): Pricing not published — contact sales

View pricing

Plan

Free

Medium (50–500 engineers): Pricing not published — contact sales

View pricing

Plan

Free

Enterprise (500–5,000 engineers): Demo-based — contact sales

View pricing

Plan

Free

Free trial available

View pricing

Pros & Cons

Pros

  • AI Checkpoints attribute every PR to the specific coding agent (Copilot, Cursor, Claude Code) that wrote it, recording tokens consumed and cost per shipped PR
  • Side-by-side vendor comparison shows acceptance rate and deployment status for each AI coding tool, enabling data-driven purchasing decisions
  • Covers SPACE, DORA, and DX frameworks in a single platform, eliminating the need for separate productivity measurement tools
  • Five dedicated modules (Automation, Delivery, Health, Planning, Studio) plus executive dashboards for Resource Planning and Project Costs
  • Published outcome benchmarks: 22% faster time to market, 2.2x velocity, 28% faster cycle time, and 28% code churn reduction

Cons

  • Pricing for Enterprise tier (500–5,000 engineers) requires a demo call — no self-serve option or published price
  • Depth of SPACE and DX measurement may be more than small teams or startups need; the platform is clearly aimed at mid-to-large organizations
  • No public information on which specific IDEs or CI/CD systems are supported beyond generic 'existing engineering toolstack' references

Questions & Answers

Alternatives

LinearB, Jellyfish, Pluralsight Flow, Swarmia, GitClear

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