1
00:00:04,894 --> 00:00:05,374
How's it going?

2
00:00:06,954 --> 00:00:09,154
Who is the most energized in the room?

3
00:00:10,374 --> 00:00:12,474
Whoever that was, most energized.

4
00:00:12,914 --> 00:00:19,154
Well, welcome back for the closing keynote block here at AI Engineer New York 2026.

5
00:00:19,554 --> 00:00:26,374
I'm Alex Lieberman, co-founder, co-managing partner at Tenex, applied AI partner for Fortune 500 businesses.

6
00:00:26,734 --> 00:00:30,834
And we are most of the way through the first session today.

7
00:00:30,834 --> 00:00:34,194
and hopefully it's been filled with incredible conversation,

8
00:00:34,194 --> 00:00:40,394
which I'm going to share a little bit about some of the conversations I've had offstage in a minute.

9
00:00:40,814 --> 00:00:42,454
But hopefully the

10
00:00:42,554 --> 00:00:47,514
mix of the programming, the conversation you've had amongst everyone has been really fruitful today.

11
00:00:47,774 --> 00:00:57,714
Now, before we hop into the final block of the day, let's just take a moment again to give a round of applause to our partners who make this entire event possible.

12
00:00:58,514 --> 00:01:04,194
let's start with our presenting sponsor, Arize. Let's give a shout out to Arize.

13
00:01:04,834 --> 00:01:12,554
yeah rise next up we have our platinum sponsors oracle sonar work os and exa let's give a shout

14
00:01:12,554 --> 00:01:18,514
out for them and then two more we have gold sponsors i love them all they're all my favorite

15
00:01:18,514 --> 00:01:24,154
children can't read them all off right now but thank you so much our silver sponsors

16
00:01:25,634 --> 00:01:31,714
and to all of our supporting partners who make this possible thank everyone yeah i don't know

17
00:01:31,714 --> 00:01:35,054
if that was the first person who said they have the most energy, but that person has a lot of

18
00:01:35,054 --> 00:01:41,934
energy. So before we hop into the next block, one thing that I just wanted to share, and I'm sure a

19
00:01:41,934 --> 00:01:48,714
lot of you are already feeling this already, is not only is the energy palpable across the room

20
00:01:49,274 --> 00:01:56,114
in between all of the sessions, but what you realize when you come to AI Engineer is that

21
00:01:56,114 --> 00:02:01,694
the content is incredible. The speakers that are curated are incredible. The depth by which they

22
00:02:01,694 --> 00:02:07,474
talk about the work they're doing is incredible. But this is also just surface area that acts as

23
00:02:07,474 --> 00:02:13,434
a starting point for conversation amongst everyone in the room. And so for me, not only has it been

24
00:02:13,434 --> 00:02:18,474
incredible to stand in the back of the room at various points in the day and just listen to

25
00:02:18,474 --> 00:02:24,854
these incredible speakers who are truly living in Edge City, but then to use all of these

26
00:02:24,854 --> 00:02:30,854
conversations, all these talks as surface area to have conversations with folks. So a few

27
00:02:30,854 --> 00:02:35,494
conversations that come to mind that I've had throughout the day because of the content. One

28
00:02:35,494 --> 00:02:42,294
was a conversation with swyx, one of the people behind this incredible event. We were talking

29
00:02:42,294 --> 00:02:48,314
about just the diffusion gap that exists in enterprise AI right now. And just some fun

30
00:02:48,314 --> 00:02:54,274
stats for you all. We talked to hundreds of big enterprises at 10X across financial services,

31
00:02:54,274 --> 00:03:01,374
healthcare, industrials, et cetera. And the way I think about diffusion of AI across these

32
00:03:01,374 --> 00:03:08,254
organizations is almost in milestones of a race. So the first big milestone at an enterprise is

33
00:03:08,254 --> 00:03:13,754
just adopting a general purpose LLM. Out of curiosity, of the, let's call it 100 firms we

34
00:03:13,754 --> 00:03:19,744
talked to, what percentage of those firms do you think have adopted and rolled out an LLM to all

35
00:03:19,744 --> 00:03:30,524
their employees. Someone screwing out a number. 9%, I think I heard. 17%. So specific. 90%. So

36
00:03:30,524 --> 00:03:37,204
90% of the enterprises we work with have rolled out a general purpose LLN. Under that is people

37
00:03:37,204 --> 00:03:41,404
actually getting trained in how to use the technology, how to actually use these surfaces

38
00:03:41,404 --> 00:03:47,264
in their work. That's like 60%. Next up is coding agents, agents that are actually used within

39
00:03:47,264 --> 00:03:48,924
in engineering and product workflows.

40
00:03:49,224 --> 00:03:52,364
That's around 50% of all the enterprises we've been in.

41
00:03:52,524 --> 00:03:55,504
And then the final one, where we are truly still day one,

42
00:03:55,804 --> 00:04:00,964
is agents actually working in non-engineering workflows

43
00:04:00,964 --> 00:04:01,764
in an organization.

44
00:04:01,784 --> 00:04:04,004
That is around 5% right now.

45
00:04:04,184 --> 00:04:05,664
So going back to what I said earlier,

46
00:04:05,984 --> 00:04:08,404
this community really is Edge City.

47
00:04:08,564 --> 00:04:10,944
The topics that are being talked about,

48
00:04:11,144 --> 00:04:13,304
we are going to continue to see those play out

49
00:04:13,304 --> 00:04:16,684
over the next 12, 24, 36 months.

50
00:04:17,264 --> 00:04:20,464
I've had a variety of conversations like this throughout the day.

51
00:04:20,584 --> 00:04:23,884
It's a fusion gap, open source versus fine-tuned models,

52
00:04:24,184 --> 00:04:28,064
how hard it is to hire great AI engineers at scale.

53
00:04:28,284 --> 00:04:30,624
And so as we go about the rest of today,

54
00:04:30,824 --> 00:04:33,624
but also as you think about the conference in general,

55
00:04:34,024 --> 00:04:36,124
use the content as a starting point

56
00:04:36,124 --> 00:04:38,844
to have interesting conversations at the edge.

57
00:04:38,984 --> 00:04:42,484
With that, I would love to introduce you to our next talk,

58
00:04:42,624 --> 00:04:46,424
which is with Frank Long, the head of AI at Coatue.

59
00:04:46,424 --> 00:04:50,454
He's gonna be talking about a hedge fund as a function. Let's welcome Frank
