Question 1

What is Agentic Engineering Intelligence?

Accepted Answer

Agentic Engineering Intelligence measures the combined work of human engineers and their AI agents, capturing where time goes, every agent run and token cost, at the source, across all repos, and tying it to shipped output.

Question 2

How is DevClocked different from Waydev?

Accepted Answer

Waydev reads your Git history and infers which commits were AI. That's the artifact after it lands. We sit in the work session and capture it as it happens, real hours, every agent run, the tokens, including everything that never became a commit.

Question 3

How is DevClocked different from Tokscale?

Accepted Answer

Tokscale tells you what you spent. We tell you what you shipped for it. Measuring spend is the easy half; tying it to real human hours and shipped output, the leverage, is the hard half, and the part that matters.

Question 4

How is DevClocked different from Jellyfish or LinearB?

Accepted Answer

Same data limit as Waydev, they're built on Git and pull requests about humans, with AI bolted on as adoption stats. We're built on the work session itself, captured at the source.

Question 5

How is DevClocked different from Langfuse or agent observability?

Accepted Answer

Different end of the pipe. Langfuse traces what the model does, for people building agents. We measure the output and cost of people using them to ship software.

Question 6

What is the Leverage Score?

Accepted Answer

Your Leverage Score is the ratio of total shipped output, human and agent combined, to the human hours you invested. It shows whether AI is acting as a true force multiplier or mostly adding cost.

Question 7

How does agent session capture work?

Accepted Answer

When you run Claude Code, Cursor, Windsurf, or other AI coding tools, DevClocked captures the session: duration, tokens in and out, cost, and project attribution. Agent sessions appear beside manual coding sessions.

Question 8

What token and cost data does DevClocked track?

Accepted Answer

DevClocked maps token usage to projects and sessions so you can see total tokens, cost per shipped feature, and whether spend is compounding output or getting lost to context resets.

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