New research: Leading indicators of AI coding agent effectiveness
New research: Leading indicators of AI coding agent effectiveness
Span vs. Jellyfish:
The AI-native alternative
Jellyfish relies on planning and delivery metadata. 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
Connect AI usage and spend to shipped work, delivery, rework, and quality. Identify the harness fixes, workflow changes, and developer practices that improve the KPIs that matter.
The right view for every role
Give executives, managers, teams, and ICs the context they need. HRIS-grade permissions keep sensitive individual, survey, and trace data controlled.
Prompt-to-prod visibility
Follow AI-assisted work from the agent session through the code and PR it produced. Understand how the work happened, not only what shipped.
Verify every result
Drill from any metric or finding into the PRs, tickets, code, and agent traces behind it. Span gives leaders evidence they can inspect, verify, and trust.
Flexible by design
Adapt Span to your operating model, metrics, workflows, and culture. Our co-build approach helps teams shape the platform around how they run engineering.
Works without perfect hygiene
Span’s AI inference engine fills gaps when tickets, links, and project structures are incomplete. Get a useful view without forcing more process onto teams.
Prove and improve AI impact
Connect AI usage and spend to shipped work, delivery, rework, and quality. Identify the harness fixes, workflow changes, and developer practices that improve the KPIs that matter.
Prompt-to-prod visibility
Follow AI-assisted work from the agent session through the code and PR it produced. Understand how the work happened, not only what shipped.
Flexible by design
Adapt Span to your operating model, metrics, workflows, and culture. Our co-build approach helps teams shape the platform around how they run engineering.
The right view for every role
Give executives, managers, teams, and ICs the context they need. HRIS-grade permissions keep sensitive individual, survey, and trace data controlled.
Verify every result
Drill from any metric or finding into the PRs, tickets, code, and agent traces behind it. Span gives leaders evidence they can inspect, verify, and trust.
Works without perfect hygiene
Span’s AI inference engine fills gaps when tickets, links, and project structures are incomplete. Get a useful view without forcing more process onto teams.
Prove and improve AI impact
Connect AI usage and spend to shipped work, delivery, rework, and quality. Identify the harness fixes, workflow changes, and developer practices that improve the KPIs that matter.
Flexible by design
Adapt Span to your operating model, metrics, workflows, and culture. Our co-build approach helps teams shape the platform around how they run engineering.
Verify every result
Drill from any metric or finding into the PRs, tickets, code, and agent traces behind it. Span gives leaders evidence they can inspect, verify, and trust.
Prompt-to-prod visibility
Follow AI-assisted work from the agent session through the code and PR it produced. Understand how the work happened, not only what shipped.
The right view for every role
Give executives, managers, teams, and ICs the context they need. HRIS-grade permissions keep sensitive individual, survey, and trace data controlled.
Works without perfect hygiene
Span’s AI inference engine fills gaps when tickets, links, and project structures are incomplete. Get a useful view without forcing more process onto teams.
Detailed Comparison
How Span stacks up against Jellyfish
How Span stacks up against Jellyfish
Connect AI usage and spend to shipped work, delivery, rework, and quality. Identify the harness fixes, workflow changes, and developer practices that improve the KPIs that matter.
Connect AI usage and spend to shipped work, delivery, rework, and quality. Identify the harness fixes, workflow changes, and developer practices that improve the KPIs that matter.
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.
jellyfish
Tracks usage, spend, and agent-authored output without the full session behind it.
Tracks usage, spend, and agent-authored output without the full session behind it.
Relies more heavily on ticket structures and planning metadata.
Relies more heavily on ticket structures and planning metadata.
More dependent on complete planning data and linked work.
More dependent on complete planning data and linked work.
Primarily designed for executive and leadership reporting.
Primarily designed for executive and leadership reporting.
Requires more consistent process hygiene to keep reporting accurate.
Requires more consistent process hygiene to keep reporting accurate.
Built primarily for executive reporting, with less flexibility across roles.
Built primarily for executive reporting, with less flexibility across roles.
More upfront taxonomy, configuration, and process alignment.
More upfront taxonomy, configuration, and process alignment.
Complex enterprise pricing requiring negotiation
Complex enterprise pricing requiring negotiation
The Span Advantage
Why teams choose Span over Jellyfish
Why teams choose Span over Jellyfish
01
Built for the AI software factory
Jellyfish was built around planning, allocation, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, and codebase improvements lead to better results.
04
Faster implementation and results
Customers report getting to value 3–4x faster with Span than traditional platforms. Span starts with your existing systems and reduces the upfront taxonomy, cleanup, and configuration work.
02
Less dependent on process hygiene
Jellyfish relies more heavily on clean Jira or Azure DevOps structures. Span’s AI inference engine fills gaps across code and tickets without adding more tagging or process overhead.
05
Flexible enough to fit your organization
Span’s co-build approach adapts to your metrics, workflows, reporting needs, and rollout model instead of forcing every team into the same framework.
03
Built for more than executive dashboards
Jellyfish was built primarily for executive reporting. Span gives leaders, managers, teams, and ICs tailored views, backed by HRIS-grade permissions.
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
Jellyfish was built around planning, allocation, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, and codebase improvements lead to better results.
02
Less dependent on process hygiene
Jellyfish relies more heavily on clean Jira or Azure DevOps structures. Span’s AI inference engine fills gaps across code and tickets without adding more tagging or process overhead.
03
Built for more than executive dashboards
Jellyfish was built primarily for executive reporting. Span gives leaders, managers, teams, and ICs tailored views, backed by HRIS-grade permissions.
04
Faster implementation and results
Customers report getting to value 3–4x faster with Span than traditional platforms. Span starts with your existing systems and reduces the upfront taxonomy, cleanup, and configuration work.
05
Flexible enough to fit your organization
Span’s co-build approach adapts to your metrics, workflows, reporting needs, and rollout model instead of forcing every team into the same framework.
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
Jellyfish was built around planning, allocation, and delivery reporting. Span connects full agent traces to code and outcomes, showing which prompts, workflows, and codebase improvements lead to better results.
03
Built for more than executive dashboards
Jellyfish was built primarily for executive reporting. Span gives leaders, managers, teams, and ICs tailored views, backed by HRIS-grade permissions.
05
Flexible enough to fit your organization
Span’s co-build approach adapts to your metrics, workflows, reporting needs, and rollout model instead of forcing every team into the same framework.
02
Less dependent on process hygiene
Jellyfish relies more heavily on clean Jira or Azure DevOps structures. Span’s AI inference engine fills gaps across code and tickets without adding more tagging or process overhead.
04
Faster implementation and results
Customers report getting to value 3–4x faster with Span than traditional platforms. Span starts with your existing systems and reduces the upfront taxonomy, cleanup, and configuration work.
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