Recent submissions

Comment · 3 months ago
I wonder if any old software companies like amazon, microsoft, apple, or google have data on how many prs a software engineer would produce per day over time. I wonder what that major spikes on the graph would be? live reload? vscode? faster and faster laptops? llms?

I have a hunch the amount of prs written per day per engineer is likely the same or only 10-15% higher.

Comment · 6 months ago
the manus founders moved the entire company, researchers, and IP out of china to singapore. most of the researchers and business is still there, but unfortunately the founders wives/parents and family stayed in china. ultimately this is why they had to come back when the PRC summoned them after the meta acquisition.

sad day to be a chinese founder.

Comment · 8 months ago
surprised to hear others don't do this! obsidian also works well for daily notes
Comment · 8 months ago
i thought the reason claude code defaults to terminal-ish workflows (glob/grep) is bc they trained with bash-y sandboxes, and the creator argued for this approach vs indexing + bespoke tools. would be interesting to see how often the model defaults to using grep for everything (in my experience almost always..)
Comment · 1 year ago
Comment · 3 years ago
Comment · 3 years ago
Comment · 3 years ago
For testing:

- we have a dedicated dev environment for analysts to experience a dev/test loop. None of the pipelines can be run locally unfortunately.

- we have CI jobs and unit tests that are run on all pipelines

Observability:

- we have data quality checks for each dataset, organized by tier. This also integrates with our alerting system to send pagers when data quality dips.

- Airflow and our query engines hive/spark/presto each integrate with our in-house lineage service. We have a lineage graph that shows which pipelines produce/consume which assets but it doesn't work at the column level because our internal version of Hive doesn't support that.

- we have a service that essential surfaces observability metrics for pipelines in a nice ui

- our airflow is integrated with pagerduty to send pagers to owning teams when pipelines fail.

We'd like to do more, but nobody has really put in the work to make a good static analysis system for airflow/python. Couple that with the lack of support for column level lineage OOTB and it's easy to get into a mess. For large migrations (airflow/infra/python/dependecy changes) we still end up doing adhoc analysis to make sure things go right, and we often miss important things.

Happy to talk more about this if you're interested.

Comment · 3 years ago
How do you guys do the static analysis on the queries? I notice you support dbt, bigquery etc, but all of our companies pipelines are in airflow. That makes the static analysis difficult because we're dealing with arbitrary python code that programmatically generates queries :).

Any plans to support airflow in the future? Would love to have something like this for our companies 500k+ airflow jobs.

Comment · 3 years ago

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