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LLMOps

Running language models in production without losing control of them.

Part 1

From Rehearsal to Live Broadcast

why getting a language model working in a demo or notebook is a genuinely different challenge than running it reliably in production, night after night.

Part 2

What the Control Room Actually Watches

the core metrics an LLM system needs monitored continuously in production, beyond just whether it's technically still running.

Part 3

Before There Was a Control Room

how early LLM-powered features were deployed and maintained before LLMOps existed as a distinct discipline, and why that approach stopped scaling.

Part 4

The Director's Runbook

why LLM systems need the same deliberate deployment pipeline discipline as any other production software, adapted for their specific quirks.

Part 5

Switching Feeds Without Going to Black

how to version and roll back LLM systems in production without ever causing a visible outage for the people relying on them.

Part 6

The Sound Check Before Air

the pre-deployment testing and validation an LLM system needs before it ever reaches real production traffic.

Part 7

Watching the Levels in Real Time

why latency and throughput monitoring for LLM systems needs to account for patterns traditional infrastructure monitoring wasn't built to handle.

Part 8

When a Guest Mic Goes Dead

handling model and API failures gracefully in production, so one dead connection doesn't take down the whole broadcast.

Part 9

The Backup Generator

why genuinely critical LLM-dependent systems need real redundancy and failover planning, not just graceful handling of individual call failures.

Part 10

Catching Drift Before Viewers Notice

why production monitoring needs to watch for gradual model drift, not just sudden failures, and how that connects to the maintenance burden covered elsewhere in this content library.

Part 11

The Control Room's Cost Ledger

why LLM cost management needs continuous, granular tracking, not just periodic review of the monthly bill.

Part 12

Multiple Camera Feeds, One Broadcast

how routing requests across multiple models lets a production system balance cost, quality, and reliability, rather than committing to one model for everything.

Part 13

The Censor's Delay Button

why production LLM systems need a real content moderation and safety filtering layer, not just trust that the model will always behave.

Part 14

Logging Every Take

why comprehensive observability and logging for LLM calls is essential for debugging, auditing, and understanding real production behavior.

Part 15

The Standards and Practices Review

how compliance and governance requirements shape production LLM systems, from data handling to auditability.

Part 16

Rehearsing the Blackout

why practicing incident response before a real production failure happens matters as much as the technical safeguards themselves.

Part 17

Swapping the Anchor Mid-Season

the deliberate process for upgrading or switching the underlying model in a production LLM system without disrupting what's already working.

Part 18

The Ratings Report

how ongoing evaluation and user feedback loops keep a production LLM system improving over time, rather than just staying static after launch.

Part 19

Running Every Night, Not Just Opening Night

the sustained organizational discipline it takes to run an LLM system reliably over months and years, not just through a successful launch.

Part 20

The Full Control Room

reassembling every station covered across this series into the complete picture of a well-run LLMOps practice, from deployment through sustained operation.