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Keep a current status for queues and tools, but record every status change in a separate append-only history. That gives a task system two useful answers: what is happening now, and how it got there. In his September 30, 2026, account of AgentRQ, Mustafa Turan describes this hybrid design rather than replacing the current status with a full event-sourced system. The implementation is a product-specific choice, not a universal rule for every agent platform.
Why a current status alone is not enough
A task marked completed tells you its present state, but not whether it spent time waiting for a person, became blocked, or returned to active work before closing. Overwriting one status field erases those earlier transitions, making it difficult to answer questions such as how long a task took or how much of that time was work versus waiting.
AgentRQ keeps the current status for present-state reads and adds an append-only history for the timeline and duration calculations. As Turan puts it, “The current state is a projection; the transitions are the data.” Read Turan’s implementation account on DEV Community.
How the status history works
Record each transition as it happens
Each history entry captures the prior state, the next state, the time of the change, and the agent or model attribution. The record is not edited later, and an earlier transition is not inserted retroactively. A state’s duration runs from its entry timestamp until the next transition; if it is still current, its interval continues to the present.
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Write the status and history together
In AgentRQ, status transitions are recorded in the storage layer’s task-save path, in the same transaction as the status change. This is intended to prevent a task update without its matching history entry, while ordinary edits that do not change status do not create false transitions.
Using one storage-layer writer is meant to cover changes from MCP tools, the web app, the CLI, scheduled tasks, and cross-workspace events. The described design locks the task while recording a transition, so a subsequent change sees the first change as its starting point. That consistency depends on the locking and transaction design; append-only records by themselves do not settle every concurrency question.
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Why keep a current status instead of using full event sourcing?
Full event sourcing would reconstruct the current state from the event stream. Turan says AgentRQ did not choose that approach because existing readers—including agent MCP clients—already rely on the current status, and changing them was unnecessary for the duration use case.
| Approach | What it preserves | Main trade-off |
|---|---|---|
| One overwritten status field | Simple present-state reads for queues, filters, and counters | Past transitions and duration evidence are lost |
| Current status plus append-only history | Existing current-status readers and a timeline of transitions | Adds storage, a write per transition, and history-maintenance rules |
| Full event sourcing | Transitions as the basis for rebuilding current state | Requires readers to derive state from events; Turan says that migration was not needed for AgentRQ’s use case |
The hybrid model is a fit for AgentRQ’s existing interfaces and reporting needs. Another system may reasonably choose differently depending on its readers, consistency requirements, and appetite for added complexity.
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Represent human waiting without changing the task’s real status
A task waiting for a person is not necessarily blocked because the agent cannot proceed. AgentRQ represents “needs input” as a derived interval in the history while leaving the task’s actual status unchanged. That avoids making a new status affect agent behavior, queues, filters, or counters.
When one or more actual questions are unanswered, the history records a needs-input interval. It ends when the last open question is answered and the task returns in the history to its actual status. The implementation counts open questions rather than toggling a single flag, excludes pending to-do items that are not questions, and does not reopen the interval for a question added to a completed task. Correctness depends on every question-creation and question-answer path rechecking the derived state.
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What the duration metrics mean
AgentRQ’s per-task view separates four measurements so that work, blockers, human waiting, and overall elapsed time are not conflated.
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- Worked time: time recorded in the working state or states.
- Blocked time: time spent in a blocked state.
- Needs-input time: time represented in the history as waiting for a human response.
- Start-to-close time: elapsed time from the task’s first
ongoingtransition to closure, excluding time before work began.
The task timeline and dashboard use the same duration calculation. The four totals answer different questions; in particular, start-to-close is not measured from task creation.
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How to interpret the latency dashboard
The described Task Latency panel appears in workspace and account statistics. For a selected range, it reports p50, minimum, and maximum for the four duration measures. The minimum and maximum help show the range and expose outliers; p50 is intended to describe a typical task when a few long-running tasks create a long tail.
At account level, the system merges histogram buckets by adding their counts, then estimates p50 by interpolating within the bucket containing the median and clamping the result to the exact minimum or maximum. It does not sort every underlying task duration to compute an exact median. The estimate is exact when the relevant bucket contains only one task.
Turan’s 2026 illustration describes 42 tasks closed in a week, with p50 values of 108 minutes start-to-close, 66 minutes worked, 19 minutes blocked, and 7 minutes waiting for a person. These are example dashboard figures, not an independent benchmark or a claim about typical agent performance. Each p50 is calculated separately, so the four figures need not add up.
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Limits and implementation costs to account for
- Past events cannot be recovered automatically. Existing tasks start their timeline at their next recorded status change; the described one-time dashboard backfill can use only whatever history exists.
- “Immutable” does not mean retained forever. In AgentRQ, moving a task moves its history, while deleting the task deletes its history.
- The state enum has migration constraints. The described enum grows by appending values; reordering or renaming stored values would change their meaning. It also includes an explicit
noneinitial state. - There is additional write and state-maintenance work. Each status change adds a history write, and the derived needs-input interval is only reliable if all question paths update it.
- Aggregate p50 values are estimates. Histogram aggregation trades an exact calculation over every task for a bucket-based estimate.
When this design is a good fit
Keeping both a current status and a transition history is useful when existing tools need fast, familiar present-state reads while operators also need timelines and elapsed-time breakdowns. It is less compelling if no one needs to inspect transitions or measure durations, or if the system is prepared to make events—not a separate status field—the authoritative source for every reader.
For AgentRQ, the key design decision is not that every agent must use immutable history. It is that current state and historical evidence serve different purposes, and the implementation records both without forcing existing status readers to change.
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