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$4B+

spent on AI coding tools
the largest category of enterprise AI spend

31%

of developer work goes unmeasured
in traditional engineering metrics

6%

of organizations trust current metrics
to measure modern engineering performance
WHY HARNESS

Token spend without a velocity increase is wasted spend

Most organizations know token usage. Very few understand the impact on delivery and outcomes.

Measure Adoption
Seats do not equal usage. Usage does not equal productivity.
Understand which AI coding tools teams use, how deeply they are adopted, and productivity impact.
Optimize Efficiency
Developer token consumption is rising. Most of those tokens never ship code to production.
Identify wasted and optimizable spend, and measure cost per developer, agent, or feature.
Improve Impact
AI ships code faster. It also ships bugs, security vulnerabilities, and tech debt faster too.
Connect AI activity to production outcomes, clearer engineering ROI, and stronger security posture.
ADOPTION

Measure AI adoption and token consumption

Find your power users, see which agents actually get used, and measure the code generated.

Track tokens consumed by developer, team, agent, and model.
Measure AI-authored code at the commit level.
See AI-assisted PRs, acceptance rates, and code contribution.
Identify power users and ghost seats.
See whether increased token spend produces more shipped code.
Ingests data from
Claude
Cursor
Copilot
Windsurf+
EFFICIENCY

Stop tokenmaxxing and reduce wasted spend

Most tokens get burned because of poor prompting and using the wrong model. See exactly where your spend leaks.

Find tokens spent on code that's abandoned, rewritten, or never shipped.
Spot expensive model choices, bloated prompts, and missed cache hits.
Compare API and token costs by developer, team, agent, or repository.
Track cost per feature, bug fix, or engineering initiative.
Separate the workflows that ship code from the ones that just burn tokens.
IMPACT

Track AI-generated code from prompt to production

Stop guessing whether coding agents make you faster. Measure ship rate, churn, and delivery.

Connect AI adoption to PR velocity, deployments, and throughput.
Track features delivered, backlog reduction, and production outcomes.
Measure quality regressions, security risk, and engineering rework.
Monitor DORA metrics, sprint health, and business alignment.
Compare delivery efficiency and output across teams.
Ingests data from
Jira
Azure
GitHub
Bitbucket
Gitlab
Jenkins
PagerDuty
ServiceNow
Harness AI Harness AI · this week’s summary
Claude adoption hit 78% this week, but % AI-generated code dropped to 31% from 42%. The backend team is burning 2.4x more tokens per merged PR than the frontend team.
Recommended next step
Investigate backend token consumption — pinpoint which repositories or workflows are driving the 2.4x excess spend.
Ask Harness...
HARNESS AI

Query, visualize, and act on engineering data

Query engineering data in real time, build dashboards instantly, and automate workflows using Harness AI.

Explore adoption, spend, delivery, and engineering health using natural language.
Generate dashboards instantly without manually configuring reports or filters.
Query engineering data in real time with MCP-powered workflows and agents.
Surface bottlenecks, regressions, and optimization opportunities automatically.
PLATFORM CAPABILITIES

One platform to measure AI spend and development impact

Track every token from prompt to production. Know which agents, teams, and workflows turn AI spend into shipped features.

Role-based access control
Control visibility and permissions across teams, business units, and engineering leadership.
Organization hierarchies
Model teams, reporting structures, and business units with metrics that roll up automatically.
Harness native integrations
Connect CI/CD, feature flags, cloud cost, security, incident, and delivery data across the Harness platform.
Out-of-the-box insights
Prebuilt dashboards for AI adoption, engineering efficiency, productivity, security, and business alignment.
Software delivery knowledge graph
A unified, real-time data layer connecting AI activity, SDLC workflows, and engineering outcomes.
Custom insights with Studio
Build custom dashboards, reports, and engineering views tailored to your organization.
BUILT FOR EVERY ROLE

Insights for every role

Executive Leaders
Engineering Managers
Business & Finance Partners
Developers
EXECUTIVE LEADERS

Know if your AI bet is paying off.

See AI adoption, token spend, shipped code, and delivery performance in one view. Understand whether the engineering organization is getting faster or just more expensive.

EXECUTIVE LEADERS

Coach your team into AI fluency.

See who's getting leverage from AI and who's struggling, then turn power-user patterns into team-wide practice with data on sessions, model choices, and shipped code.

BUSINESS & FINANCE PARTNERS

Turn AI invoices into ROI.

Attribute every token to a developer, team, agent, or business unit and tie that spend back to features delivered, so AI shows up as a P&L line and not a mystery charge.

EXECUTIVE LEADERS

Spend less time fighting your tools.

See which agents, models, and prompts work best for your workflow and where you're burning tokens on retries, bloated context, or sessions that never ship.

INTEGRATIONS

Insights you can trust start with data you can trust

Connect your AI coding agents, source control, and delivery tools to track every prompt to every deployment.

Jira
GitHub
Gitlab
Bitbucket
Harness CI/CD
Jenkins
Azure DevOps
GitHub Actions
Claude
Cursor
Copilot
Windsurf
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Software Engineering Insights