339 karma · joined September 25, 2016
But what I am hearing is a lot of overwhelm and a sense that you need to take this stuff on by yourself, which isn’t the case. You should find more ways to push work onto your engineers. Your job is to make sure the team is tackling the big challenges.
In big tech orgs, that comes through writing proposals and creating alignment between teams. When it comes to strategy, see if you can boil it down to the top 1-2 things you need to do to unblock the team. Write a proposal. Get feedback on it. Get it on the roadmap. And make sure your team is working towards that.
Also, use Claude. Tell Claude your problems and the AI will give you some decent feedback or resources to approach your problems.
If you need more specialized coaching, there are services that can help you get mentorship.
They’re little putty molds that you shape to fit your ear.
I also rip them in half before molding so I get 2 ear plugs from 1 putty.
I listened to one. It was pretty good!! There’s no lyrical content, but the production was strong.
In that niche of “music you don’t really pay attention to” I predict AI generated music will only grow.
Why would I reach for that instead of Claude code building a dashboard with HTML/CS/JS?
I think there is a silver lining and opportunity if you choose to look at it that way. That’s how I overcame similar feelings.
Not all hope is lost. Do your homework as others have suggested and get an idea of how successful they’ve launched new products before. Set deadlines and think through the worst case scenarios so you can be honest with the progress. Lastly, try out their product and see for yourself once it’s out.
However, in the banking case (and likely government, but I cannot speak to that directly) they are running your data against a KYC API so chances of your information being valid are low.
Everything is upside down.
It looks like they updated their program terms to force you to buy their ink. Honestly I thought that was already the case since I had tried using cheaper ink and the printer rejected it.
How many wrong turns can you make into a different country?
But then they explained that one could use these models to generate the code that would process the financial data.
Sounds interesting, but yes the question is how do you validate this? Do humans write the test cases to ensure that, for example, ACH files are being processed accordingly? What about edge case detection? Self-correction in real-time? Many questions left unanswered.
Our Lambdas are currently written in Typescript and built with esbuild. We zip them and push to AWS.