simplemindedbot

“Crippling horse addiction” has so many meanings even in context. From heroin to animal cruelty to gambling to horse dancing. Wonderful phrase, I tip my hat to you.

As an additional note, Spellar does let you bring your own Open AI key but does not allow for purely local processing. You’ve still got to send the audio out for transcription and interpretation.

Also, I have no affiliation with Spellar, just a user.

Spellar.ai does a great job. There’s others out there for Mac but I like Spellar’s calendar integration.

Interestingly, their initial raison d’être was to help with English pronunciation and speaking speed, giving you real time feedback. They’ve downplayed this in recent releases, but the functionality is still there. Though, I’m a native English speaker and it always flagged me as pronouncing words incorrectly even though I’ve got little regional accent (I’ve been told this by others, not just my opinion. I had a speech therapist as a mother, hence little accent)

There’s not a “bot” that needs to attend the meeting and show up in the list of attendees thus giving away the recording of the call. Otter.ai, for instance, shows up as “Otter” (or another name) on a Zoom call when it is recording and taking notes.

So low-code is faster to get started with little programming knowledge but isn’t expandable. OTOH, a language and framework that you’ve taken the time and effort to learn takes a little longer to get started but is ultimately more suited to more complex tasks.

I think the takeaway from the narrative here is knowing when to switch from the low code platform and call it a PoC. I’d have cut that off around the point that the custom lambda came into play. That way you’ve used the low code environment for what it’s good at, creating something “they” can react to and easily explore basic functionality. While at the same time you’re taking those learnings and building the more robust solution.