InteliG vs LinearB: Why Engineering Metrics Aren't Execution Intelligence

LinearB is a good metrics tool. It tracks DORA metrics, cycle time, PR throughput, and developer activity. It gives you dashboards with numbers that go up and down. It tells you what happened.

It does not tell you what any of it means.

And that distinction — between measurement and intelligence — is the entire gap that engineering leaders are living inside right now.

What LinearB Does Well

Credit where it’s due. LinearB does developer activity measurement better than most. Cycle time breakdowns per team. PR pickup time. Review bottlenecks. DORA metrics benchmarked against industry averages. If you want to know how fast your PRs are moving, LinearB will tell you.

It also plugs into Jira, so it can correlate ticket status with code activity. WorkerB automates some workflow tasks. The gitStream feature helps with PR routing.

If your entire goal is to measure developer throughput and put it on a screen, LinearB does that.

But throughput is not intelligence.

What’s Missing: The Questions That Actually Matter

Here’s what a CTO actually needs to know on a Monday morning:

• Is our Q1 platform migration on track — not by ticket status, but by actual code movement?
• How much are we spending per initiative, and is the ROI justified?
• Who made the decision to change the authentication architecture, and what was the reasoning?
• Why did deployment frequency drop last week — was it a holiday, a hard problem, or a team silently stuck?

LinearB cannot answer any of these. It can show you charts adjacent to these questions. But it cannot reason about them, connect them across domains, or give you an actual answer.

That’s the difference between a metrics tool and an execution intelligence platform.

What InteliG Does Differently

InteliG is not a better LinearB. It’s a different category entirely. It operates across four pillars that LinearB doesn’t touch.

Strategy: Code Connected to Intent

LinearB requires Jira as the system of record. Your tickets say one thing. Your code says another. You spend half your standup reconciling the two.

InteliG uses Git as truth. Commits auto-classify to strategic initiatives based on what the code actually touches — not what someone remembered to update in a ticket. Action items auto-close when the corresponding code ships. You see initiative progress measured by real engineering output, not ticket drag-and-drop.

No Jira required. No manual status updates. The code tells the story.

Finance: The Cost No One Tracks

LinearB shows you how many PRs shipped. It does not show you what they cost.

InteliG tracks cost per initiative, ROI per contributor, and engineering spend against strategic outcomes. When the CFO asks “what did we get for that $400K in Q1 engineering spend?”, you have a real answer — broken down by initiative, team, and contributor. Not a velocity chart.

Knowledge: Decisions Linked to Code

Every engineering org makes hundreds of decisions a week. Architecture choices. Tradeoff discussions. Meeting outcomes. Almost none of it gets captured in a way that connects back to the code it produced.

InteliG links meeting decisions, architecture rationale, and team context directly to the code that resulted from them. Six months from now, when someone asks “why did we build it this way?”, the answer exists — connected to the commits, the discussion, and the people involved.

LinearB has no knowledge layer. Decisions happen outside the tool and stay lost.

AI Reasoning: Cognis Answers Questions

This is the fundamental difference. LinearB gives you data and leaves you to interpret it. InteliG has Cognis — a reasoning engine that works across all four pillars.

You don’t look at a dashboard. You ask a question.

“Is the payments migration at risk?” Cognis analyzes commit patterns, contributor allocation, effort quality, and strategic alignment — then gives you a reasoned answer with evidence and confidence levels. It tells you the database migration stalled because the only contributor working on it got pulled into incident response last week. That’s not something a cycle time chart will ever surface.

Cognis reasons about why, not just what.

Who Should Use What

If you need a developer activity dashboard and you’re happy with Jira as your system of record, LinearB is a reasonable choice. It does throughput measurement well.

If you need to connect engineering output to strategic outcomes, understand what your engineering investment actually produces, preserve institutional knowledge, and ask questions that get reasoned answers — that’s InteliG.

Metrics tell you what happened. Execution intelligence tells you what it means and what to do about it.

The CTO’s job isn’t to stare at cycle time charts. It’s to make decisions. InteliG is built for that.

Connect GitHub and ask Cognis →