Public evidence record
Published podcast speaker
Books, apps, and tools
app / built
“We'll build some great experiments that really resonate, and then we have to spend a lot of time ironing out the long tail of problems. So in Cash Card, for example, we built the entire functionality of Cash Card, I would say pretty much in a weekend or maybe a week of integration and work.”
tool / uses
“I would say really try and use these tools yourself. So the way in which I think we've been able to drive most of the adoption is Jack uses Goose, I use Goose, our executive team all have used Goose and use it regularly and use other AI programming tools and assistance as well, and we do it every single day.”
Claim ledger
18 transcript-backed records
01 / evaluation
“Whenever I hear a stat like this, I think an important element is this is the worst it will ever be.”
02 / belief
“Could we build something completely different that would matter more to our core reason for being? So I would say, yeah, question the sort of base assumptions.”
03 / belief
“I do think we're going to need a lot of human taste to anchor these AIs so they don't go off script to be honest. And that's really where our design lead and our design teams are pushing us to think, and that's a differentiator that I think will push us beyond this era of AI slop that everyone's talking about.”
04 / belief
“I think so. And I think that the trick is getting the AI to respect all of those incremental improvements, yeah, and sort of bake those in as a part of the specification, if you will.”
05 / belief
“We can share it in the show notes for you and yeah, you can install it. It comes for Mac and Windows and Linux I believe.”
06 / belief
“My career has basically been a string of failed product on top of failed product. And I think that, "Yeah, the Google wave example's there.”
07 / belief
“We discovered this as we were investigating what it's going to take to make these teams more tech-focused and to bring our DNA back to our roots, which really was putting engineering and design first, which is what technology first means to me. So yeah, I would say to companies, find your DNA and really try to optimize for what that is in a very simple and clear way.”
08 / belief
“I'm very happy to be contacted. And I would say the way people can be useful is, again, going back to this era we're in of a lot of change and uncertainty, I think people that demand more of their companies, of their employers, of their teams, demand something better.”
09 / belief
“Yeah, we believe in the power of open source and one of our core missions is to increase openness, and that means contributing to open protocols and contributing to open source.”
10 / belief
“Sometimes it kind of goes off the script entirely and you have to sort of pull it back a bit. So I think we're not quite at that era where it's completely self-improving and completely autonomous, but I do think we're in a transition phase where we can give it that nudge and say, "Hey, here's my wishlist of 10 things that I wish you could do.”
11 / belief
“The lines are going to be blurred between whether you're in legal or in risk or in engineering and design even. And so I think that the people that are able to embrace it to optimize for their particular work day and their particular set of tasks are really who are showing the most impact from these tools.”
12 / recommendation
“I would say really try and use these tools yourself. So the way in which I think we've been able to drive most of the adoption is Jack uses Goose, I use Goose, our executive team all have used Goose and use it regularly and use other AI programming tools and assistance as well, and we do it every single day.”
13 / prediction
“I think we should do it centrally and it's important for us to be ahead of the game and be an AI native company because that's where the industry is heading.”
14 / evaluation
“" And this is the thing that AI isn't good at, it's not able to have this portfolio judgment or judgment across a global sense of what's important and what matters. So a lot of times, I tell teams just question the base assumption, particularly our InfoSec teams because they'll twist themselves into knot sometimes trying to secure something and you'll be like, "We'll just ask the team that's building it to do it differently or to not build that at all if it doesn't matter, and then you won't have to increase your surface area of securing it.”
15 / recommendation
“They were kind of separate in almost every way except for some shared resources like our foundational resources like legal and some platforms and things like that. So I think that that was very useful for us for the stage of company that we were in, but when you really want to go deep in technology, when you really want to connect with these things that are industry changing events that are happening, you need a singular focus, and we changed the organization.”
16 / evaluation
“We'll build some great experiments that really resonate, and then we have to spend a lot of time ironing out the long tail of problems. So in Cash Card, for example, we built the entire functionality of Cash Card, I would say pretty much in a weekend or maybe a week of integration and work.”
17 / evaluation
“In the small, certain teams that are very, very AI natives or teams that are building AI first everywhere are working much differently than before because they're using vibe code tools and they're essentially building without writing lines of code by hand, and that just wasn't true through the three years ago.”
18 / prediction
“Yeah, so these are things that I think we were waiting for the calendar vendor to build as features into calendar, but we don't need to do that anymore because AI is able to orchestrate this for us.”