What are Green Worklogs?

The name reflects their visual treatment in Enji's interface: automatically generated entries appear in green, making them immediately distinguishable from manually logged time while contributing to the same analytical layer.

For teams where manual time tracking is inconsistent, culturally unpopular, or simply not enforced, Green Worklogs makes full project analytics accessible without requiring a behavioral change from developers. They address one of the most common adoption blockers for delivery intelligence platforms: the data quality problem created by incomplete time logs.

Green Worklogs are generated using a defined formula applied nightly across all team members with activity in connected tools:

(N − T) / K

Where:

• N = the employee's target working hours for the day, based on their configured schedule
• T = time spent in meetings and other activities with a known duration, pulled from calendar integrations
• K = the number of tasks with recorded activity during that day

The remaining available time (after accounting for meetings) is distributed across the active tasks, weighted by the type of activity recorded against each one.

Enji differentiates between two categories of activity artifacts when applying this distribution:

1. Static artifacts, like task creation, comments, and status changes, receive a fixed time allocation, reflecting their lower time intensity.
2. Dynamic artifacts, like commits, branches, and merge requests, receive an equal share of the remaining distributed time, reflecting the deeper work they represent.

This distinction prevents the formula from treating a quick status comment the same as a substantive code contribution, producing a more accurate picture of where developer time actually went.

Green Worklogs are only generated when no manual worklogs exist for that day. If a team member has logged time manually (even partially), the automatic generation does not run for that day, ensuring manual entries always take precedence.

Generation runs automatically every night: no manual trigger required and no action needed from team members or managers.

The conditions for generation are:

1. The feature is enabled in project settings; it is opt-in, not active by default.
2. No manual worklogs have been submitted for the employee on that day.
3. The employee has at least one task with recorded activity in a connected tool during that day.

When all three conditions are met, Enji calculates the worklog distribution and creates the entries, making them available in the same reporting interfaces as manually logged time.

The opt-in design is intentional. Teams that already have strong manual logging habits won't have their data affected: automatic generation only runs when no manual entries exist for that day. For roles like sales, delivery managers, and project managers, whose work is largely made up of meetings and communication rather than trackable code activity, they significantly reduce the routine overhead of time logging and free up attention for higher-impact work.

The direct consequence of incomplete time tracking is incomplete analytics. Without worklog coverage, several of Enji's most important reporting capabilities produce either blank data or misleading results:

• Project Margins: cost per feature, budget burn rate, and earned value calculations all depend on logged hours converted to monetary cost. Gaps in worklog coverage mean cost figures underrepresent actual spend, making profitability analysis unreliable.
• Enlightening Worklogs: the planned vs. actual hours comparison that surfaces overload, underutilization, and estimation accuracy requires actual hours to compare against. Incomplete logs produce gaps that distort both individual and team-level analysis.
• PM Agent responses: when a delivery manager asks about team capacity, sprint cost, or feature-level time investment, the answer is only as complete as the underlying data. Green Worklogs ensure the PM Agent has more complete data to draw from, reducing the gaps that would otherwise skew capacity, cost, and sprint-level answers.
• Employee contribution reporting: performance visibility and workload analysis across team members rely on consistent time data. Teams without manual logging habits would otherwise appear to have low activity, misrepresenting their actual contribution.

Green Worklogs effectively lowers the barrier to meaningful delivery intelligence: teams no longer need to establish a time-tracking culture before they can access accurate project cost data, capacity analysis, or AI-generated project summaries.

The two approaches are complementary rather than competing. Manual logs remain the higher-accuracy input wherever they exist. Green Worklogs provide the coverage layer that makes analytics reliable for teams that don't log consistently and can serve as a transitional baseline while logging habits are being established.