New research: Leading indicators of AI coding agent effectiveness
New research: Leading indicators of AI coding agent effectiveness
Span vs. LinearB:
The AI-native alternative
LinearB centers on Git activity and DORA metrics. Span connects full agent traces to code, PRs, and outcomes for prompt-to-prod visibility into AI impact and engineering performance. See why modern engineering teams are switching to Span.
Why Span
Built for the way engineering works now
Built for the way engineering works now
Span gives leaders a clearer view of engineering performance and AI impact, without adding more reporting work or requiring every team to follow the same process.
Span gives leaders a clearer view of engineering performance and AI impact, without adding more reporting work or requiring every team to follow the same process.
Prove and improve AI impact
Go beyond measuring AI-assisted PRs and DORA outcomes. Span connects full agent traces to code, spend, and outcomes, showing what improves delivery, quality, and cost.
The right view for every role
Give every role the right level of context, beyond team-level delivery metrics. HRIS-grade permissions protect sensitive individual, survey, and trace data.
Prompt-to-prod visibility
See what happened before the PR opened. Follow AI-assisted work from the full agent session through the code, review process, and outcome.
Verify every result
Go beyond Git and workflow signals. Trace AI and delivery findings back to the session, code, PRs, and tickets that produced them.
Flexible by design
Adapt Span to your broader operating model, not only the Git workflow. Our co-build approach helps teams shape the platform around how they run engineering.
Works without perfect hygiene
LinearB relies more heavily on active tickets, configured fields, and Git links. Span reconstructs work when the planning system is incomplete.
Prove and improve AI impact
Go beyond measuring AI-assisted PRs and DORA outcomes. Span connects full agent traces to code, spend, and outcomes, showing what improves delivery, quality, and cost.
Prompt-to-prod visibility
See what happened before the PR opened. Follow AI-assisted work from the full agent session through the code, review process, and outcome.
Flexible by design
Adapt Span to your broader operating model, not only the Git workflow. Our co-build approach helps teams shape the platform around how they run engineering.
The right view for every role
Give every role the right level of context, beyond team-level delivery metrics. HRIS-grade permissions protect sensitive individual, survey, and trace data.
Verify every result
Go beyond Git and workflow signals. Trace AI and delivery findings back to the session, code, PRs, and tickets that produced them.
Works without perfect hygiene
LinearB relies more heavily on active tickets, configured fields, and Git links. Span reconstructs work when the planning system is incomplete.
Prove and improve AI impact
Go beyond measuring AI-assisted PRs and DORA outcomes. Span connects full agent traces to code, spend, and outcomes, showing what improves delivery, quality, and cost.
Flexible by design
Adapt Span to your broader operating model, not only the Git workflow. Our co-build approach helps teams shape the platform around how they run engineering.
Verify every result
Go beyond Git and workflow signals. Trace AI and delivery findings back to the session, code, PRs, and tickets that produced them.
Prompt-to-prod visibility
See what happened before the PR opened. Follow AI-assisted work from the full agent session through the code, review process, and outcome.
The right view for every role
Give every role the right level of context, beyond team-level delivery metrics. HRIS-grade permissions protect sensitive individual, survey, and trace data.
Works without perfect hygiene
LinearB relies more heavily on active tickets, configured fields, and Git links. Span reconstructs work when the planning system is incomplete.
Detailed Comparison
How Span stacks up against LinearB
How Span stacks up against LinearB
Go beyond measuring AI-assisted PRs and DORA outcomes. Span connects full agent traces to code, spend, and outcomes, showing what improves delivery, quality, and cost.
Go beyond measuring AI-assisted PRs and DORA outcomes. Span connects full agent traces to code, spend, and outcomes, showing what improves delivery, quality, and cost.
CAPABILITIES
AI effectiveness & ROI
AI effectiveness & ROI
Workstreams & investment mix
Workstreams & investment mix
AI-native cost capitalization
AI-native cost capitalization
Brag sheets & performance summaries
Brag sheets & performance summaries
Works without perfect data hygiene
Works without perfect data hygiene
Roles & permissions
Roles & permissions
Time to value
Time to value
Pricing
Pricing
Connect full agent traces to shipped PRs, rework, and quality to see what improves AI coding results.
Connect full agent traces to shipped PRs, rework, and quality to see what improves AI coding results.
See where engineering time goes, including unplanned work.
See where engineering time goes, including unplanned work.
Automate software capitalization from real activity, even when issue links are incomplete.
Automate software capitalization from real activity, even when issue links are incomplete.
Generate evidence-backed updates for ICs, managers, and leaders in seconds.
Generate evidence-backed updates for ICs, managers, and leaders in seconds.
AI inference fills gaps when tickets, links, and project structures are incomplete.
AI inference fills gaps when tickets, links, and project structures are incomplete.
Tailored views for ICs, managers, and leaders, with HRIS-grade permissions.
Tailored views for ICs, managers, and leaders, with HRIS-grade permissions.
Customers report getting to value 3–4x faster, with less setup and cleanup.
Customers report getting to value 3–4x faster, with less setup and cleanup.
$45 per contributor / month. Transparent and predictable.
$45 per contributor / month. Transparent and predictable.
linearb
Classifies AI-assisted commits and PRs using tool signals and thresholds.
Classifies AI-assisted commits and PRs using tool signals and thresholds.
Infers allocation from tickets, project fields, and Git links, leaving gaps when data is incomplete.
Infers allocation from tickets, project fields, and Git links, leaving gaps when data is incomplete.
Builds capitalization on ticket-based allocation and configured rules.
Builds capitalization on ticket-based allocation and configured rules.
Summarizes Git and workflow activity, with limited evidence beyond the delivery pipeline.
Summarizes Git and workflow activity, with limited evidence beyond the delivery pipeline.
Relies on current tickets, team mapping, configured fields to stay accurate.
Relies on current tickets, team mapping, configured fields to stay accurate.
Roles and team controls, but less granular governance for sensitive data and AI activity.
Roles and team controls, but less granular governance for sensitive data and AI activity.
Quick for basic Git analytics; broader value requires more mapping, integrations, and configuration.
Quick for basic Git analytics; broader value requires more mapping, integrations, and configuration.
Published tiers add complexity through automation credits and gated capabilities.
Published tiers add complexity through automation credits and gated capabilities.
The Span Advantage
Why teams choose Span over LinearB
Why teams choose Span over LinearB
01
Built for the AI software factory
LinearB was built around Git activity, DORA metrics, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, tests, and codebase conditions improve results.
04
Improve more than the PR pipeline
gitStream is built to route reviews, enforce policies, and automate Git workflows. Span helps teams improve the broader system around the model, from task definition to environment readiness.
02
See what happened before the PR
LinearB shows how work moves through review and release. Span captures the agent session that produced it, including the actions, iteration, and verification behind the code.
05
Less dependent on ticket structure
LinearB’s allocation model relies more heavily on active issues, configured fields, and Git links. Span reconstructs work from code and engineering activity when the planning system is incomplete.
03
Go beyond DORA metrics
DORA shows whether delivery improved. Span connects those outcomes to agent behavior, engineering context, and the underlying work so leaders can understand why.
06
Shows the evidence behind every answer
Move from a metric, classification, or AI finding to the underlying code, PRs, tickets, and agent traces. Understand what changed and why.
01
Built for the AI software factory
LinearB was built around Git activity, DORA metrics, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, tests, and codebase conditions improve results.
02
See what happened before the PR
LinearB shows how work moves through review and release. Span captures the agent session that produced it, including the actions, iteration, and verification behind the code.
03
Go beyond DORA metrics
DORA shows whether delivery improved. Span connects those outcomes to agent behavior, engineering context, and the underlying work so leaders can understand why.
04
Improve more than the PR pipeline
gitStream is built to route reviews, enforce policies, and automate Git workflows. Span helps teams improve the broader system around the model, from task definition to environment readiness.
05
Less dependent on ticket structure
LinearB’s allocation model relies more heavily on active issues, configured fields, and Git links. Span reconstructs work from code and engineering activity when the planning system is incomplete.
06
Shows the evidence behind every answer
Move from a metric, classification, or AI finding to the underlying code, PRs, tickets, and agent traces. Understand what changed and why.
01
Built for the AI software factory
LinearB was built around Git activity, DORA metrics, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, tests, and codebase conditions improve results.
03
Go beyond DORA metrics
DORA shows whether delivery improved. Span connects those outcomes to agent behavior, engineering context, and the underlying work so leaders can understand why.
05
Less dependent on ticket structure
LinearB’s allocation model relies more heavily on active issues, configured fields, and Git links. Span reconstructs work from code and engineering activity when the planning system is incomplete.
02
See what happened before the PR
LinearB shows how work moves through review and release. Span captures the agent session that produced it, including the actions, iteration, and verification behind the code.
04
Improve more than the PR pipeline
gitStream is built to route reviews, enforce policies, and automate Git workflows. Span helps teams improve the broader system around the model, from task definition to environment readiness.
06
Shows the evidence behind every answer
Move from a metric, classification, or AI finding to the underlying code, PRs, tickets, and agent traces. Understand what changed and why.
Glossgenius
glossgenius.com
"Span helps us take a more data-driven approach to velocity and gives every team and engineer visibility into how they can improve. We quickly moved the needle by giving teams insight into their working patterns and their own maker time."
Brady Allchin
VP of Engineering
Classpass
classpass.com
"We looked at other products, but ultimately chose Span. It came down to the magic and usability. Span just feels built by engineers who understand how teams actually work."
Henrique Boregio
Director of Engineering
Glossgenius
glossgenius.com
"Span helps us take a more data-driven approach to velocity and gives every team and engineer visibility into how they can improve. We quickly moved the needle by giving teams insight into their working patterns and their own maker time."
Brady Allchin
VP of Engineering
Classpass
classpass.com
"We looked at other products, but ultimately chose Span. It came down to the magic and usability. Span just feels built by engineers who understand how teams actually work."
Henrique Boregio
Director of Engineering
Transparent, predictable pricing
Transparent, predictable pricing
No negotiation games, hidden costs, or surprises.
No negotiation games, hidden costs, or surprises.
$45
contributor/mo
billed annually
Glossgenius
glossgenius.com
"Span helps us take a more data-driven approach to velocity and gives every team and engineer visibility into how they can improve. We quickly moved the needle by giving teams insight into their working patterns and their own maker time."
Brady Allchin
VP of Engineering
Classpass
classpass.com
"We looked at other products, but ultimately chose Span. It came down to the magic and usability. Span just feels built by engineers who understand how teams actually work."
Henrique Boregio
Director of Engineering
Everything you need to unlock engineering excellence
Everything you need to unlock engineering excellence