01 · A proposal that is almost right
The assistant proposes a readiness probe.
orders-api has no readiness probe, so the assistant
proposes one on the container port, 8080. Reasonable
from the manifest alone. Wrong for this service: the health
endpoint is served by a sidecar on 8081.
02 · Say why, in plain words
A comment on the MR is all it takes.
The reviewer writes what they would write to a colleague. No
template, no form. Closing an MR without merging is a signal too,
and closing it with a reason is the strongest one.
A thumbs-down reaction on its own is not read; write a sentence.
03 · Collected within minutes
Every comment lands in one feedback store.
A collection job reads new comments on the assistant's MRs and
issues, Slack corrections and closed proposals, and stores each
with the proposal it belongs to. No model call happens here.
It polls every 5 minutes while people are actively commenting and
backs off to every 2 hours when things are quiet. The assistant's
own comments are excluded, so it never learns from itself.
04 · Commands act immediately
Some comments are instructions, and get an instant answer.
/reprompt regenerates the MR's diff on the next cycle,
usually within 15 minutes. /skip turns "not for this
resource" into a one-line annotation MR. The assistant acknowledges
each in the thread straight away and confirms again when the work
is done.
Only people on an allowlist can trigger them.
05 · Nothing goes unanswered
A queue of what still needs a reply.
Unanswered feedback is sorted into skip directives,
acknowledgements ("thanks", "LGTM") and substantive comments.
Substantive ones get a written answer in the thread: the root
cause and what changes. Today that answer is written with a
maintainer in the loop and posted by the assistant, which can also
retitle the MR and marks the feedback as answered.
06 · Tune the instructions In development
A weekly pass turns feedback into a prompt change.
Once enough feedback has accumulated for one agent, a weekly
analysis reads it against that agent's current prompt and proposes
a specific wording change, as a low-risk draft MR against your
installation's prompt configuration. Closed-with-a-reason items
weigh most, and the operator's own words are quoted in the
rationale.
This pass is built and held dormant while its threshold is
calibrated; today the same changes are made by hand from the
answered-feedback queue.
07 · Check the next run
Did the feedback actually land?
After the next full run, the team operating the assistant matches
each comment to the new proposal for the same workload and judges
it: fixed,
recurs, partial or not re-emitted. A fix that
quietly introduced a new mistake is flagged too.
Prompts are reloaded before every model call, so once a merged
prompt change is deployed it applies to the next proposal, with no
restart.