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I think this is the most important thing mentioned in the post. In order for the AI to actually help you with languages you don't know you have to question its solutions. I have noticed that asking questions like why are we doing it like this and what will happen in the x,y,z scenario, really helps.
I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment.
This is a test. You can't improve a system without testing it on real world conditions.
How do we know they're not tweaking the Copilot system prompts and settings behind the scenes while they're doing this work?
Can no one see the possibility that what is happening in those PRs is exactly what all the people involved expected to have happen, and they're just going through the process of seeing what happens when you try to refine and coach the system to either success or failure?
When we adopted AI coding assist tools internally over a year ago we did almost exactly this (not directly in GitHub though).
We asked a bunch of senior engineers to see how far they could get by coaching the AI to write code rather than writing it themselves. We wanted to calibrate our expectations and better understand the limits, strengths and weaknesses of these new tools we wanted to adopt.
In most of those early cases we ended up with worse code than if it had been written by humans, but we learned a ton. We can also clearly see how much better things have gotten over time, since we have that benchmark to look back on.
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https://docs.mermaidchart.com/blog/posts/7-er-diagram-exampl...
I recently started working for a startup, and they wanted an app.
What I shipped was a react native app (so I don't need to go in to Xcode to build), that renders a full screen web browser that points to our website. I've sprinkled in bits of injected JS to capture our cookies and local/session storage - which then gets saved to device storage and reinjected on app startup.
There are a few native-ish bits sprinkled in - onboarding, notifications, error screens, loading indicators, etc - but for the most part we don't need to worry about our API borking old versions (which is moving extraordinarily fast).
The only semi tricky bit was native auth integration - that needs treated with a bit more care, and stored securely, but it took a few days.
I ship the app to TestFlight and the AppStore using Fastlane from the command line, match handles the certs, and I never have to open Xcode.
It is honestly bliss, and i've heard a lot of app developers moving to this model (interestingly it normally follows a failed SDUX implementation)