Your first Linux lab: save a file and find it after a restart
Give Ubuntu a separate practice machine, confirm where your commands run and follow one small file through a shutdown and return.
Articles
Guides, news and explanations about AI and reliable systems.
Not sure where to begin? Choose a short reading path, or browse at your own pace.
Follow one slow status request through the evidence
A fleet chart can be correct while one customer group waits much longer. Use counts, a log and a trace to locate the next useful question.
Start the incident response from the impact you can confirm
Two exports are late, the API is healthy and the cause is unknown. Give responders a shared starting point without turning clues into conclusions.
What the model can do with your notes and what it still needs
Turning messy notes into a useful update is different from knowing what happened next. Separate the model’s learned abilities from the information and tools its app supplies.
Reliability begins with the report the customer can use
A healthy website can still leave someone without their report. Define the whole useful outcome before choosing a measurement or an engineering fix.
Model weights: change two numbers and watch an answer move
A tiny model predicts zero where the answer should be three. Follow one training step, save the learned values and see why changing the input is a different job from changing the model.
The citation is real. Does the restart advice follow?
A runbook quote can be genuine and still belong to the wrong release. Use a small Python checker to catch that mismatch, then see the mistake that only reading the condition will catch.
UserRepGen prepares the user’s part in an assistant test
The user can read logs but cannot change configuration. A useful simulation reveals that restriction at the right moment and lets you see whether the assistant adapts.
PulsarLM and the archive a long conversation must not forget
A retention condition may sit unused for many turns, then decide what can be deleted. Follow it through a smaller working context before counting the tokens saved.
The two experiments inside Anthropic’s AI replication study
Fifteen TV boxes ran one model. A different model directed a replication task in an emulated fleet. Keep the setups separate to understand what the study means for a device you operate.
Teach Hermes the report’s method, then change the data
Three pipeline jobs say success, but their data keeps aging. Build a checkable report, save the reviewed procedure and change one row to see what the assistant really carries forward.
Model inference: following a question to its answer
A downloaded model, a waiting cursor and a finished answer are different parts of the job. Follow one request to understand what runs, where the time goes and whether the result helps.