Eiso Kant
speaker
1,158 appearances
1 recordings
1 series
first heard Jul 2026
last heard 23 Jul
Eiso Kant’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.
Appearances
Let me take a second to think about it.
Look, ultimately, what is code, what is software, what is engineering is to go from something that is valuable for an end user or sets of end users, like an idea, an extra bug fix, a feature, to delivering that value.
And I think what we're doing with these models becoming more capable is that we are massively both cutting out middlemen and compressing the time that it takes to deliver that value.
And ultimately, that iteration cycle for any startup or any company is what allows you to win, right?
If you're able to solve a bug in two hours versus staying in the back walk for three weeks, if you're able to like be on a customer call and learn, hey, if this feature existed, it would like, you know, they'll be willing to pay more and it's more valuable to them.
And you ship it in a week instead of in a month.
And so I think ultimately, maybe the same things that we looked at years ago, pre-ADLM still apply.
And it's just a notion of cycle time.
In this case, it's lead time from the moment you have a valuable thing that you are looking to do for someone to the moment that it's actually shipped to them.
Every other metric is ultimately a leading indicator for that lagging indicator, right?
It doesn't matter if you're looking at amounts of code, PR, reviews, all of these kinds of things.
And so I think in this case, we are starting to move so quickly in some of these things that we can just sit back and look at what was traditionally the lagging indicator, which is the lead time from traditionally ticket to like, you know, like end result.
What I would look at in this new world that maybe we didn't think about before is how much can a single person do with that?
If you look at AI-native companies, they're not designed like the engineering orgs of pre-LMH.
They're actually designed with often just the builder and as close to the kind of customer to the ability to ship.
There isn't necessarily a huge team in between that sits there.
And I think that is, I think is exciting.
Like organizations where a single IC can just, you know, get much closer to that.
So I would look at from where the value sits, that's identified to the moment it's shipped and how many people are involved in that.
And you want the amount of people involved in that to be less and you want the time end to end to be shorter.
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