AI in production: tools, operating patterns, costs, and failure modes.
Splunk’s September releases combine agent traces, evaluations and token-cost monitoring. A rejected incident summary shows how retries and human corrections affect the apparent saving.
How Herdr keeps coding sessions available while you detach, and what changes when its server restarts.
Separate detection from response and find delays that an improving average can conceal.
The permissions, state and recovery paths an agent needs when its tool calls can change a running service.
Account for context limits, retries, latency, and the work behind a useful result.
Conflicting restart instructions show where a source-backed notebook helps: finding the relevant passages, dates and exceptions for the runbook owner.
Power and cooling affect the work a GPU pool can sustain. Device signals, request completions and queue growth help distinguish a physical limit from a workload change.
A rollback exception tests whether Opus 4.6 preserves decisive evidence across a long session, and whether the resulting answer arrives in time to help.
A timed-out scaling request needs a durable record and destination-state checks. Reusable operational skills need to recover unfinished work as well as start it.
A rollback proposal crosses from recorded evidence into a changing system. The handoff carries source references, current preconditions and unfinished actions.
Disturbed nights, specialist help and cleanup consume capacity beyond the primary shift. A workload worksheet connects that demand to staffing and delivery plans.
Grouping can shorten the incident queue while hiding a second failure. Following a replay past the first mitigation reveals whether that failure stays visible.
