Why blank tickets fail when agents join the queue.

Blank tickets used to waste human time. Someone reconstructed history from Slack, tribal memory, and half-related PRs. Then an agent entered the same queue.

Agents do not fill gaps the way senior engineers do. They iterate. Empty intake becomes tokens, retries, and review churn on work that never should have started cold.

Intake is where memory should attach

SignalsAI treats intake as the moment prior art lands: related features, PRs, prompt sessions, and contributors gathered before anyone plans. Work can enter from a PRD with docs and links, from chat, from a manual create, or from triage on monitoring and support signals.

You review the synthesis with citations. You accept a suggested feature lead. Planning then breaks work into tasks with repo and file context already attached, not a blank canvas pasted into an IDE.

One queue still needs ownership and cost

Memory at intake is not enough if humans and agents disappear into separate tools. The delivery layer puts both on one board: IDE active, waiting in review, waiting in QA, at risk. Duration, iterations, tokens, and cost stay visible so capacity is not a guess.

• Dispatch into a shared queue with clear ownership.
• Watch stages that match how work moves, not generic ticket status.
• Surface agent loops and review stalls in the risk feed before standup.

Governance keeps memory reusable

Compounding context only helps if it stays safe. Redaction, role-based access, and override audit keep delivery memory usable. Tracker history can import once when you need it. There is no silent ongoing sync that quietly becomes a second source of truth for your codebase.

Source stays on your machines. Delivery signals and governed memory move. That boundary is what lets teams attach org memory at intake without treating the repository as a product upload.

If agents are joining your queue, stop starting from blank. Attach memory first. Then let humans and agents ship on the same loop.