Bitter lessons building AI products

This post details lessons learned in building AI products, emphasizing the importance of adapting roadmaps to evolving model capabilities rather than relying on clever engineering to overcome model deficiencies. It highlights the failure of an early Notebook Agent due to model limitations and the "pretty good" trap with visualization generation, where clever optimizations were outpaced by new model capabilities like tool calling. The team now prioritizes early customer validation, spotting capability shifts, and faster project killing. The post advocates for building AI features that leverage future model improvements rather than working around current limitations.