Ship a cross-repository change with coding agents
Coordinate backend and frontend changes with compatible contracts, separate pull requests, and explicit integration checks.
30 stories
Coordinate backend and frontend changes with compatible contracts, separate pull requests, and explicit integration checks.
Choose MCP tools by the missing information in a task, and give each connection a clear access boundary.
Track accepted changes, review effort, cycle time, and regressions without confusing activity with impact.
Break a framework migration into reviewable batches, preserve behavior, and verify the combined application before rollout.
Give a coding agent a bounded dependency patch with explicit compatibility checks and review requirements.
Use a scheduled investigation and small reviewed changes to make repository maintenance manageable.
Schedule a bounded documentation check that verifies changed commands and opens a reviewable pull request.
Seven bounded recipes for recurring repository work, with explicit triggers, stop conditions, and review expectations.
A practical study design for measuring accepted work, failed attempts and reviewer effort across a real backlog.
Put standing rules in project instructions, repeatable procedures in repository skills and task details in the prompt.
Make an agent task transferable with a shared thread, a pushed branch, a draft pull request and a clear next action.
Import useful session history and skills into Hoplite, with clear boundaries around credentials and project state.
A preflight and recovery checklist for transferring a live task, including conversation, repository state, and environment checks.
Use the Hoplite CLI to create a cloud thread from a local agent session and understand exactly what transfers.
Compare coding models on representative tasks, review effort, retries and cost before choosing a default.
Identify the processes behind sustained heat, reduce unnecessary local work, or move the agents to cloud sandboxes so the laptop stops running builds.
Use memory pressure and process ownership to diagnose RAM exhaustion, reduce concurrency, or move the agents' browsers and test workers into cloud sandboxes.
Find whether parallel agents are limited by local compute, memory, services, or a remote model, or skip the tuning and give each agent its own cloud sandbox.
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