Phil Calçado highlighted the challenges of building generative AI products in production at the InfoQ Dev Summit. He discussed the need for effective tools for managers and reliability engineers as compared to existing automations for individual engineers. Calçado's initial attempts to automate managerial tasks failed due to misaligned user incentives, emphasizing that successful tools must deliver sustained value. From his experiences, he identified three detrimental mindsets impeding AI development, involving a focus on trendy model releases, incremental improvements, and an overly narrow engineering perspective.
"My initial idea back in 2021 was like, okay, can we automate this? Can I create basically VS Code for everything either the manager does or everything an engineer does?"
Calçado candidly admitted that "this product failed miserably." He pinpointed the core issue as a misalignment of incentives: users were more interested in reverse-engineering the assistant's internal design than relying on it for day-to-day productivity gains.
He distilled three dominant mindsets he's observed in AI development: chasing the latest model releases without addressing current limitations, focusing on incremental accuracy improvements, and being software-engineering centric without broader product thinking.
Collection
[
|
...
]