PayByPhone also shows ads in the parking experience (thankfully, not too obtrusively, and not until the parking is confirmed). So, they could be covering some of the cost that way.
This struck me too, but I think it is intentionally a high limit to prevent problems like relatively low impact/high LoC tests from tipping a small change into a large one. That would encourage gamification like skipping useful scenarios to keep a change "small".
Something that made MVC, dependency injection, and ORMs more palatable is that there is typically a well-structured interface between "our code" and "their code". The current state of agentic dev rarely has AI doing its thing behind some abstraction layer. It's really more like a new coworker that needs to be steered toward team norms very quickly.
I think the main challenge is pressure for more productivity with AI. I often go back and forth about if I am scrutinizing too much (and not being as productive as I could be) or not enough (and shipping slop). Building the additional QA harnesses and feedback loops for agents seems like the best known path forward to accelerate with some safety, but it is still pretty challenging to context-fiy all of the nuanced judgements a seasoned dev team makes.
Agree with you on model quality, but Anthropic has done a nice job developing stickiness. The connector ecosystem, integrations with desktop apps, browser use, etc. are all pretty compelling for a typical business use scenario. It's expensive, but also a "safe choice" akin to buying IBM or Microsoft back in the day. My workplace (not just developers) is deeply invested in the Claude ecosystem & it would be pretty disruptive to pivot it.
This is spot on. Also, many orgs build to the needs of the business or whims of stakeholders rather than customer needs. Good product strategy and product discovery remain difficult despite AI.
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