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1:42

Hello, Jared Santo here, Practical

1:45

AI's producer and co-host

1:47

of the ChangeLog podcast. Chris

1:50

and Daniel are out this week, and

1:52

I just got back from Raleigh, North Carolina,

1:54

attending the All Things Open conference. While

1:57

there, I moderated a panel all about AI's

1:59

impact.

1:59

on developers featuring keynoters

2:02

Emily Freeman and James Q. Quick.

2:05

We thought you might enjoy listening in on

2:07

that discussion so here it is. The

2:10

opening question didn't get recorded but

2:13

I asked each of them to introduce themselves

2:15

and tell us all if they're long-term,

2:18

bearish, or bullish on the

2:20

impact of AI on developers. James

2:23

Q. Quick, developer, speaker, teacher.

2:25

I've done

2:28

some combinations of those things professionally for 10

2:29

years now which is pretty fun and

2:32

on the AI front this is something I've actually talked a lot about.

2:35

I really enjoyed your talk by the way. That

2:37

was my first pitch was an AI talk and they're like no we

2:39

already have some money that's taking that so. My

2:42

take that I would love to get into more is a

2:45

very super positive thing and the thing that I've talked about

2:47

a lot recently is people's fear of it replacing

2:49

their jobs and kind of hopefully

2:52

maybe changing your mindset around that fear,

2:54

the fear that you might have and changing

2:56

it more into a positive thing so hopefully we can get

2:58

more into that long term.

3:00

I love that. I love that we're starting with bullish

3:02

or bearish like yes, no, go.

3:05

I'm Emily Freeman. I lead community engagement

3:08

at AWS. That means I come to communities

3:11

and conferences like these to

3:13

really

3:13

show up as a partner for the communities

3:15

that already exist.

3:16

I ran developer

3:18

relations at Microsoft prior to that

3:21

and I've certainly been in the community for a long

3:23

time wrote DevOps for Dummies, 97 things every

3:25

cloud engineer should know. I am

3:28

bullish on artificial intelligence

3:32

because it's happening right like this

3:34

is happening. We have

3:36

to kind of make it our own and

3:39

and lean into it rather than try

3:41

and fight it in my opinion.

3:43

I guess you guys agree. Yeah,

3:45

we should have made that more comfortable. We

3:48

should have set this up so we have a debate to kick

3:50

it off. Agreed.

3:55

Let's reel it in then. That's

3:58

long term both very positive. I

4:00

think I'm also in that in that camp so we

4:02

won't debate too harshly on that. But

4:04

what about today?

4:06

Where does it stand? I know we've had some good demos.

4:09

We have people using certain things. It's here.

4:11

We think it's staying. So to

4:13

developers it sounds like the message is it's time

4:16

to adopt. But how? How

4:18

do I get started if I'm just seeing

4:20

the demos on social media or

4:23

my colleague talks about it

4:25

and they show me what they're doing with it. What do I

4:27

do today to actually start my

4:30

AI journey.

4:31

I think getting started today

4:33

is really about acknowledging sort of where we're at

4:36

with AI and the tools that are available to

4:38

us in this moment. I think learning

4:41

as much as you can. This isn't new to

4:43

us. Right. Like we have to learn all the time

4:45

and adapt our skills and grow

4:47

as our technology grows.

4:50

So I believe that we have to again

4:52

lean into AI learn these things. I

4:55

mentioned prompt engineering earlier. I

4:58

don't think it's a permanent role, but

5:00

I think it is something that we have to engage with right

5:02

now and learning to design

5:07

our prompts to really lean into the specific

5:09

vectors of the model that you're

5:11

using is important. Learn

5:14

as much as you can about how it actually works on the

5:16

back end. I'm doing this right now. I

5:18

don't have a degree in data or

5:20

artificial intelligence. I'm

5:23

learning and I'm watching the content

5:25

that already exists and gleaning as much

5:27

as I can from it. So that's been

5:29

a great experience and

5:32

it's opening my eyes to sort of how we proceed

5:34

with this. But I think for now, it's just

5:36

exploring the tools, recognizing the strengths

5:39

and the limitations and being

5:41

ready to adapt

5:42

and change as we move forward. Perfect. I love the

5:44

adapt and change and I think if you don't

5:46

adapt and change and embrace

5:48

AI to a certain extent, this is dramatic,

5:50

but you'll get left behind. But the reason that's not

5:53

as scary as it sounds is that's been the case

5:55

with every technological advancement that we've ever

5:57

had. If you were writing machine

5:59

codes, years ago. If

6:01

you were still doing that, you would not be very

6:03

productive, right? Like maybe some of you are

6:06

and that's cool. But like we have

6:08

abstractions and we continue to have abstractions where

6:10

the world that we live in as developers is totally

6:12

different than it was five years ago, ten years ago, 20,

6:15

30 years ago. So this is just one of those things

6:17

and it doesn't happen overnight. It's a progression. And

6:19

so I think you look at like what's the easiest

6:22

way, can you add an extension to your text

6:24

editor to give you prompts, can you go to chat GPT.

6:26

I use that almost on a daily basis, not just for code,

6:29

but just a creativity standpoint.

6:31

Like give me an idea of a project I can build or give me

6:34

questions to ask my Discord is actually something

6:36

that I've done. So I think that's kind of

6:38

the easy way to do it. And I think like where we are

6:40

now is really I guess very similar to what

6:42

you said about like the ironclad stage.

6:45

I forget the exact phrasing, but basically

6:47

the verification phase where everything

6:49

you do with AI has to be

6:52

verified. And that means that our jobs

6:54

don't go away because we have to be developers and have

6:56

that knowledge to be able to do that verification process.

6:59

But I think that's you're

7:01

able to get a lot, but I think you also have to invest a pretty

7:03

good amount of time into the verification process

7:05

to make sure that it works, it works

7:07

correctly. And then if you're doing it for things outside

7:10

of code, it also fits your tone. So I use it for

7:13

blog posts and ideas for content and things,

7:15

but I have to like take that output and convert

7:17

that into something that is genuine for

7:19

me. So there's a lot that goes into just confirming,

7:21

verifying and tweaking the output that you

7:24

get.

7:24

I also just wanted to say I think there is

7:27

currently a bit of a misunderstanding about what a hype

7:29

cycle actually is. And so you'll hear this phrase

7:31

that AI, we're in a hype cycle of AI and

7:34

they're right. But the hype cycle,

7:36

if you actually go look, it was made by Gartner. Thank

7:39

you Gartner. And so it's

7:41

really just this, this sort of extreme

7:45

expectation, right? And so we're very

7:47

excited about it right now. And we haven't begun to really

7:50

see the technical limitations and the difficulties

7:52

that we will come across later. So being in a

7:54

hype cycle does not necessarily mean that AI is

7:57

going away. It is just

7:59

inflated right now.

8:02

Well to James's point I think very

8:05

few of us are writing machine code but the ones who

8:07

are getting paid very well to write it.

8:09

Like ridiculous amounts of money. Don't sleep on COBOL.

8:13

Still a thing. Still will be four

8:15

times a come. So in my experience

8:18

I think that AI codegen

8:20

in the small is very much here at the

8:23

function level, at the line level, maybe

8:25

at the module level. As

8:28

you get into broader strokes

8:30

understanding the system at large.

8:33

The things that really are in the

8:35

mind of the developers at this point. Do

8:38

you think it's always going to stay there? Do you

8:40

think it's going to move higher and higher up

8:42

the abstraction to where I can

8:45

say, hey AI

8:48

make me a Facebook for dogs? And

8:50

it will say, okay I'm done. Please

8:53

no. Well

8:56

that's the ridiculous end point but

8:58

if we look at like what a there

9:02

actually is one of those.

9:05

Or what perhaps.

9:08

If we look at the way that a client

9:11

would hire for instance an indie developer.

9:14

Right. A contract freelance dev and

9:16

they have a business idea and

9:18

the client has some sort of idea of what that

9:21

business is. Right. And so maybe

9:23

they're at like the user story level.

9:26

Now most people aren't quite there yet. You have to help

9:28

them flesh that idea out. But

9:30

at a certain point there becomes a feature that is

9:33

given to that person and then they go and implement it.

9:36

And right now I think it's fair to say that

9:38

that person will use AI tooling in order

9:40

to do that faster, better, stronger, etc.

9:43

But is there a point and if

9:46

so please prognosticate

9:48

when that point comes when I can simply

9:50

be the writer of the user story and

9:52

we don't need anybody in between me

9:54

and the computer.

9:56

I think we're a long ways off from that. time

10:00

you're talking about an abstraction, even the best

10:02

developer tools on the market right now, the difficulty

10:05

really comes in plugging everything together, right?

10:08

We have access to

10:10

so many different tools that

10:12

operate wonderfully and provide incredible

10:15

benefits, but making them all integrate

10:18

and flow together is always the hard

10:20

thing. And I see artificial intelligence

10:22

as the exact same thing. It will do really

10:25

well in small sort of pockets

10:27

of where we need it to, and then plugging

10:30

it all together will be the sort of last

10:32

moment, I think,

10:34

where we're involved.

10:35

I think the abstraction just gets higher and

10:37

higher. And again, that's been the evolution of

10:40

humankind, right? That's the reason we have

10:43

technology and inventions is so that we don't have to do

10:45

the stuff that we wasted

10:47

a bunch of time doing looking back now,

10:49

like 100 years or whatever. So

10:52

all the abstractions that we see in development from you

10:54

no longer have to manage your own servers, you no longer

10:56

have to do patches, you no longer have to do firmware updates

10:58

and that kind of stuff. That's

11:01

just the continual path that will go down.

11:03

And I think I'm glad that you started with, like, it's a

11:05

very far away way because

11:07

people's, I think, irrational fear is like

11:09

tomorrow they lose their job because they use chat

11:11

GBT to build the app. And that's not like anywhere near

11:14

the case. But I don't see

11:16

why the evolution of this wouldn't be

11:18

exactly

11:21

that where you say I want Facebook for dogs

11:23

and it gives it to you because that code and that logic is

11:25

out there. It takes a lot to put it together and to figure it out.

11:28

And this like prognosticate when

11:30

I years, but

11:32

that could be the goal. But one interesting thing and

11:35

in doing some research for one of the talks I gave, I came

11:37

across the Devin's paradox. Anybody

11:39

heard of that? Cool. So it makes

11:41

me sound smart. So Devin's paradox

11:43

says if a

11:45

lot of people fear, like, if something

11:48

can do my job faster, that

11:50

means I'm going to lose my job because it's going to do my job.

11:52

But Devin's paradox looks across

11:54

like we're only doing that in a

11:56

mind state of what we're capable of doing

11:58

now. We're not. thinking forward

12:01

about what as a whole we're capable of doing

12:03

with these augmented tools. So we

12:05

can't even imagine what problems

12:07

we can solve in 10, 15, 20, 50 years. So even if right now

12:11

we we have this idea of Facebook

12:13

in our head, we know what that is tangibly,

12:16

even if chat GBT or whatever can do

12:18

that. We don't know what problems

12:20

we'll be solving that are infinitely more difficult than

12:22

that at the time. So it's going to be continuing like

12:25

tools are getting better, but we're continuing to do more,

12:27

I think as a as ecosystem. Okay,

12:30

so we're gonna get past Facebook is what you're saying. Yeah.

12:32

Okay. Okay,

12:34

well, how about the other I know we're both we're all optimistic

12:36

long term. But what about this very

12:38

real possibility?

12:40

I'm a C level executive.

12:43

I'm

12:45

watching tick talk somebody else on tick

12:47

tock,

12:48

who's a C level executive

12:50

coach says, Look, developers are

12:52

getting more and more efficient things to AI. They

12:55

are now 40% more efficient. You

12:57

can just cut that directly off of your top line

12:59

and save your bottom line. We're in an economic

13:02

downturn, you need to cut your engineering team

13:04

today. Like that seems like a very real

13:06

fear and a very real possibility. What

13:08

are your thoughts? Sure, I'll take it.

13:11

No danger in that question.

13:13

No, I think I think I think

13:16

plenty of CEOs are probably watching this kind of videos on

13:18

the tick tock. I don't know why that abuses me so much like

13:20

a CEO. Yes, I call it the tick tock.

13:22

Because I think it's funny. Remember when Facebook was the Facebook?

13:25

And I'm a millennial. So

13:27

you know, only us have been coming up a lot

13:29

today. In a good way. Yes,

13:32

we're good. Despite what the baby members

13:35

say. So I think it is a very

13:37

real possibility to cut and for

13:39

that to be the impetus

13:41

and the sort of thought around

13:42

this. And you see this throughout history

13:45

as we become more efficient and effective. Instead

13:48

of earning ourselves more time to

13:50

live the life that we want, we

13:53

prioritize work and are always chasing

13:55

that that edge of the bottom line. Societally,

13:59

I think we could do better. with that, but

14:01

it's always going to be a reality. And I think

14:04

this is where we have to learn and grow and adapt.

14:07

If we sit still, to James's point

14:09

earlier, that will not

14:11

behoove you long term. So learning,

14:14

adding value in different ways and adapting

14:17

to this new technology is key, I

14:19

think, to increasing our value

14:21

and having

14:22

some more longevity in

14:24

our roles.

14:25

That said, I think the roles are going to change.

14:28

And again, we're not new to this. Our

14:30

roles have changed completely. We had sysadmins,

14:33

and now you rarely see that job title. But

14:36

the population of people in technology

14:38

roles has only grown from there.

14:40

And so I think that there's extreme opportunity

14:43

if, again, we lean in and we're not approaching

14:46

this in a fear-based mentality of

14:48

trying to dig our heels in and

14:50

maintain the current system

14:52

as it stands. I

14:55

feel like we need to be more controversial. No,

14:58

I don't have it. I'm saying all those things

15:00

I agree with as well. To your point

15:02

earlier in your talk, again,

15:05

I forget the exact phrasing, but we kind

15:07

of had to go through the ironclad situation

15:11

to learn what the pitfalls were and to

15:13

then get to this next iteration of building

15:15

ships that was so much better in so many ways. And

15:17

I can see a scenario where what

15:19

you're saying happens, and I can

15:21

see them getting bit in the ass really quickly from

15:24

not having developers for when things go wrong,

15:26

because as we all know, no matter who writes the code, stuff

15:28

goes wrong. And somebody has to fully understand

15:30

that. And maybe somebody with

15:33

non-technical background can go into chat GVT and

15:35

say, here's what I'm getting, what's going on?

15:37

But probably in that case, you really want someone with

15:39

a technical experience. I

15:41

just think it's such a slow, although

15:45

it seems super fast, I think it's a much slower

15:47

process than we give credit for. And I think

15:49

we just go down this rabbit hole of really thinking it's happening

15:52

now. And it's just not. And if that

15:54

has happened with a company, please share a story.

15:56

But I just haven't heard of that, but I can see

15:58

a time. And I think there'll just be... with that, but I

16:00

also go back to the Devin's paradox of like we

16:02

still approach this conversation now with

16:05

a fairly limited mindset of what we can think about

16:07

being capable of building right now and we

16:10

just don't know what else we'll be building and 100% agree

16:12

jobs will be augmented but

16:14

not really in any different way,

16:17

although maybe slightly accelerated, than how they've augmented

16:19

over the course of time because that's what inventions

16:22

are for. So I really, I just go back to that

16:24

when I kind of go down maybe the fear

16:26

rabbit hole or question marks of the

16:28

benefits going forward. Okay.

16:29

If there was a 30% cut

16:32

and I didn't want to be a part of it, what

16:34

would I do today? Learn. We

16:36

have to learn. And you

16:39

know, chat GPT has come up a lot and that's

16:41

like sort of the leader right now. We

16:43

don't know that that's going to

16:44

stay that way. And so you're going to see

16:46

a ton of new tools come

16:48

forward. You're going to see a ton of startups

16:51

get funded. This is where venture

16:53

capitalists are putting their money right now. There's

16:55

going to be a lot of new

16:57

tools entering the market and a lot of churn as

17:00

we sort of hone in on

17:02

who the big players will be long-term.

17:04

So I think learn. I think you have

17:06

to sort of make demands

17:09

where you can, right? I've talked about responsible

17:11

AI. This is super critical. And

17:14

we are in the place where it is truly

17:15

our responsibility to push

17:17

for this and push against

17:19

the

17:20

sort of market forces that would

17:22

say, you know, we're moving forward

17:24

quickly with a profit-based

17:27

approach to this, a profit-first

17:30

approach. We have to

17:32

go forward with a set

17:34

of guidelines and standards that

17:37

protect

17:38

everyone and use this

17:40

in that responsible way. So

17:42

that for me is key as we proceed

17:44

and really owning that as

17:47

the people who not only build these tools

17:49

but utilize these tools that

17:52

we are clear on our approach

17:54

and our tolerance of that

17:56

behavior. I'll double down

17:58

and go a little bit deeper on the owner's

17:59

piece of learning and

18:02

if like we're really honest we're

18:04

in a really shitty time right now like economically

18:07

and jobs and I feel like every month I

18:10

have a friend of mine who reaches out or

18:12

I just hear about having God let go I was let

18:14

go from my role like at the before

18:16

really this started like a year and a half ago that summer and

18:19

the reality is that's happening and it really

18:22

really sucks and it's really really hard but

18:24

I think your your skill

18:27

set has never been more important your

18:29

ability to communicate what you bring to the table has

18:31

never been more important I talk about this a lot from a

18:33

career perspective like you have

18:35

to be able to share your benefit and

18:37

your value and you have to be able to communicate that effectively

18:40

and also confidently when you go into potential interviews

18:42

or just how you show up and talk to people in general that's

18:45

never been more important I also think and I go

18:47

back to this a lot because it's very important to me community

18:50

like you never know when someone in this room

18:53

might be the person that helps you find your next job

18:56

you never know one of those connections is and I I

18:58

always clarify this like from a networking perspective

19:01

it doesn't mean find people that work at a company so

19:03

that when you go to apply there you can just have

19:05

an end like that's not why you do it you invest in

19:07

the community you show up you're a part of the conversations

19:10

and you're genuine and that will have

19:12

a significant return or at least can a little

19:15

personal story when I was let go for my

19:17

job a year and a half ago it was kind of a debate

19:19

for me of whether or not I was gonna go full time to work

19:21

for myself something I've been thinking about for a while

19:24

and so I posted on Twitter saying like if anyone is

19:26

hiring for several or develop relations

19:29

or like management positions in that realm

19:32

send me a message and I got 50

19:35

or so DMS of people like not

19:37

only saying we're hiring but also like kind

19:40

of like we'd like to hire you and I don't say that from like

19:42

a braggy perspective what I'm saying is like my

19:44

network at that point I had nothing to worry about

19:47

because I could find an opportunity because I'd earn

19:49

trust in a community and so all the people

19:51

that you're sitting next to the people that you talk to the people

19:53

on stage you never know what that's

19:55

gonna do for you so there's in recent

19:57

times never been a more important

20:00

time for your skill set to be very

20:02

sharp and for you to be continuing to evolve that

20:05

like you said and then also your network and

20:07

how you show up in community because you just never know.

20:09

I love that emphasis on community and

20:12

we are not a collection

20:14

of individuals who form a community.

20:16

We are a whole and not everyone

20:19

should have to have the gumption or tenacity

20:21

or privilege to demand certain things from

20:24

their specific workplace

20:26

or role and I think part of being a

20:28

community is protecting each other and

20:31

standing up for each other and showing up for

20:33

each other and if you have the room

20:35

to do that or the natural personality to

20:37

do that the more that you can kind of

20:39

be a leader in this community and push for

20:41

those things in your own workplaces and

20:44

locations the better off we will all

20:46

be.

20:47

I love like it just

20:50

sparks so much. The

20:52

automotive industry right now is going through

20:55

strikes and stuff and they did it in an interesting

20:58

way where they did it in bits and pieces

21:00

of taking more people off the line

21:02

so they can continue to budget to be able to do that

21:05

longer. There is also an acronym

21:07

for writers like the strikes and writing. I

21:10

think the power of community and people being able to

21:12

come together as a community to stand up for what they

21:14

think they deserve and I don't know that we are

21:17

here right now but I think it is just an example of

21:19

what people that come together with a common goal can

21:21

do for an entire industry and

21:24

maybe we get to a point where like we unionize

21:26

against AI I don't know like that is maybe not

21:29

but like the power of those connections

21:31

I think can lead to being able to really

21:33

make positive influence wherever

21:35

we end up.

21:36

Unionize against AI. I heard it

21:38

here first. Let's

21:41

dive into the adoption weeds

21:43

a little bit. So we talk about learning,

21:46

adopting, trying things.

21:48

What have you all found is particularly

21:52

beneficial today how

21:54

I would go about adopting and

21:56

things that let you down. For instance

21:58

I will get one because I writing elixir which makes

22:01

me a little bit weird. AI

22:03

does not know elixir very well.

22:06

So yes, it's here

22:08

but it's not evenly distributed. For

22:10

our more obscure technologies you're going to have worse

22:13

generations, you're going to have worse advice. It's

22:15

all good. So I use it less in that context.

22:18

When I'm writing the front end stuff it knows

22:20

JavaScript very well. So that's just an example

22:23

of what's good and what's not good. I've heard

22:25

the advice that you should use

22:27

it to generate your tests and then you write

22:30

the implementation. Maybe that's a good idea.

22:32

Maybe that's backwards. Maybe

22:34

I should write the, have

22:37

it write the implementation and I write the tests because

22:39

I am the verifier. So thoughts in the weeds of like

22:41

what's good at today, you don't have to go

22:43

into the future but like if I was actually going to go code

22:46

after this and I was going to adopt

22:48

or die, what would I do that would really

22:51

level me up. You

22:54

can probably speak more actually to how

22:56

good or bad in different scenarios or maybe I don't know. But

22:59

I can't do that. So I've used it. But

23:01

I also come from a perspective of I know nothing

23:03

about how AI works. And so it's interesting that you

23:06

were saying like you're learning about how it works

23:08

and what the underpinnings are and stuff like that. And I've taken

23:10

a different approach where it's like I'm just

23:12

a regular developer, like I have none of that

23:14

knowledge and I'm just seeing what it does for me. I think

23:16

there's a time where we continue to get better

23:18

and learn more. So I think the adoption

23:21

for me, and no specific advice of like how

23:23

well it does in different segments of the industry.

23:25

But just throwing it in there and seeing

23:27

because I think it's going to change from language to language,

23:29

framework to framework. And it's up to you to

23:32

kind of figure out what works for you and maybe

23:34

your team and just kind of figure that out for

23:36

yourself again, not super specific. So maybe you can

23:38

help me out there.

23:40

I think right now we see various

23:42

tools on the market. I

23:45

can think of about five that are sort of

23:47

leading the way. I think we're going

23:49

to see a lot more models be

23:51

developed and released and kind of see

23:53

where that goes and

23:55

experiment there. I think your point

23:58

about the languages is such a good one. you're

24:00

seeing a ton of JavaScript. Obviously,

24:03

I expect Python to be there. Python, yep. The

24:07

data people love Python, so I get

24:09

it. But I think as

24:11

we proceed, making

24:14

it an even playing field as far as code generation,

24:17

but also keep in mind that part

24:19

of the major issue with generative AI is

24:21

you take a prompt and it generates something based

24:23

on expectations. And so it produces

24:26

what we call hallucinations, right?

24:29

Gen AI is on drugs. And. And.

24:32

And.

24:32

And. And. And. Lots

24:34

of breaking news of this panel. Breaking news, yes.

24:37

And so what

24:39

happens is it will just hallucinate

24:41

something, and it kind of goes off on these tangents. And

24:43

you see this when it becomes really verbose

24:46

in its language, or it kind of goes off, or

24:48

if an image, someone's missing an ear, that

24:51

type of thing. And those

24:53

exist right now, and they're fairly common

24:56

in Gen AI. And I expect as

24:58

we kind of move closer and again

25:01

hone these models, that that

25:03

becomes better and better, and we have fewer

25:05

of those. But right now, that is one of the

25:07

major challenges with Gen AI.

25:11

If you have something, if you really

25:13

want to be entertained slash trigger

25:16

warning, very weird. I

25:18

had this video in a slide, and I took it out because it's

25:20

so weird. If you're interested, search

25:22

for the Toronto Blue Jays

25:27

AI-generated hype video. That's for the baseball

25:29

team. Fair

25:32

warning if you want to. It's very

25:34

entertaining, but also extremely weird, going back

25:36

to people missing ears and stuff. Check

25:38

it out if you want.

25:40

So when we talk about it being hallucinatory,

25:45

what that really is is it's wrong. It gave

25:47

the wrong answer, right?

25:48

And as an experienced developer, I'm sure many

25:50

of you here are experienced developers, I can look at

25:53

the wrong bit of code. Maybe I'll execute

25:55

it once, but I can be like, meh.

25:57

That's not right.

25:59

What does this do to people?

25:59

learning software because

26:02

they don't they can't do what we can do and say that's

26:04

not right they're just gonna be like all right let's

26:06

rock and roll and throw this into production

26:08

is that what you did when you were a junior because

26:10

I did not do

26:12

that okay well different paths I

26:14

appreciate the

26:17

Yolo approach to production there

26:19

no I think you bring up so many different

26:21

things so yes it's wrong it doesn't know

26:23

that it's wrong yet yeah and you

26:26

know when we go through and we're talking

26:28

about juniors someone on Twitter right after the keynote

26:31

mentioned that well Gen AI

26:33

is getting rid of juniors I don't believe that for

26:36

a moment and please please don't take

26:38

that approach into your companies that's

26:40

going to be bad I think

26:42

the same approach with juniors with Gen AI should

26:44

exist as we always have which is where

26:47

the more experienced senior and principal

26:49

engineers not only review that code

26:51

but also coach the juniors on what

26:53

works and what doesn't and why so

26:56

that we can all learn and progress together again

26:58

such an emphasis on learning and

26:59

evolving as a community I also

27:03

think this is where I know for Amazon code

27:05

whisper when it generates

27:07

code you have options so it will give you

27:09

a few options that you can scroll through and

27:12

read and decide which works best for you

27:14

and I love that approach because one

27:16

you can see multiple ways of solving the same problem

27:19

and two you still have some ownership

27:21

and direction that you can inject into

27:24

the code based on your again personal style

27:26

or approach or belief knowing the whole

27:28

system right from that one comment

27:31

no code sidekick is going to know exactly

27:34

what is actually happening at the large scale it can pick up

27:36

on things as it learns

27:38

but being able to see it as the whole

27:40

and not just that one piece of code is

27:43

is really one of the values of you

27:46

my initial reaction to

27:49

the impact our influence

27:51

on learning when you use AI

27:53

is several things

27:56

first and foremost is the

27:58

fact that you have to understand

28:00

what you're accepting, whether you're copying, pasting,

28:03

or pressing enter, or tab, or whatever to get that

28:05

code, you have to understand that, because you

28:07

have to be able to decide, is it gonna work? Hopefully

28:09

you're not just shipping directly to production,

28:12

although, you know. And

28:14

in some ways it's not that different than how we've always been,

28:17

right? Like Stack Overflow has been here for

28:19

years. We have memes about Control

28:22

C, Control V keyboards, because that's all we need, right?

28:24

Like we've done that for a long time, and

28:26

we've learned sometimes to be responsible

28:29

of how we do that. So I

28:31

think we have to take time,

28:33

especially for people that are early on, to

28:36

pay attention to what's there, maybe go and do

28:38

outside research about what's there, to really have

28:40

at least a decent understanding of what's there. But

28:42

I also got a different perspective from

28:45

Rizel, who was at

28:47

GitHub as a developer advocate, and now I forget the company

28:50

name that she's at now. But she had

28:52

a different take on the learning experience, and she

28:54

was kind of going the other way

28:56

of saying like, AI

28:58

enables us to move faster and learn

29:01

some things while obscuring other things. So

29:03

if you're intentional about like, I wanna learn

29:05

this piece, I can have AI generate other

29:08

pieces that I don't need that are then enablers

29:10

for me to build the thing while focusing

29:12

my learning journey on this one individual

29:15

piece or a few different individual pieces. So

29:17

that was kind of an eye-opening thought for me. I hadn't thought

29:19

about it in the reverse of like, it still is

29:21

enabling us to do more, but I

29:23

think you do have to use it intentionally about what

29:26

is it that you don't know that you're trying to learn? What

29:28

is it that you don't know that you don't need to know yet? And

29:31

then what is it maybe down the road that you're definitely gonna need

29:33

to learn at some point too? Well

29:37

said.

29:38

All right, stereotype warning, here comes

29:40

one. Software developers

29:43

are

29:44

generally speaking, this will be generally true

29:46

and specifically false.

29:47

We're pedantic. We like,

29:50

we think about the tiny, littlest

29:53

details,

29:54

because historically we've had to.

29:57

I mean, some of us are still writing machine code, right?

30:00

So like that's I know pedantics

30:02

a pejorative but if we just take

30:05

it literally we think about the little things and a lot

30:07

of times we take joy in those

30:09

little things right so we think

30:11

about the impact of AI on developers.

30:15

Is this stealing some of our joy like

30:18

will we continue to do what we do at a higher

30:20

level and be more productive

30:22

and make more money and all

30:24

the things that are great but actually what

30:26

we like to do was to write that function

30:29

to sort that array the exact way we want it to. I

30:32

think you have a point. Okay, I would

30:34

say pedantic

30:35

feels negative.

30:38

Is there a better word? Is there a better word? Jared

30:42

here in post. I thought of that

30:44

better word. Okay, chat GPT thought of

30:46

it meticulous. I should have said

30:48

meticulous. Pretty similar meaning. No,

30:50

that negative baggage. All right, let's get back

30:53

to it. Okay, focused

30:55

and specific on those types of issues

30:58

because I think we all carry those moments that

31:00

we saw something fail spectacularly

31:02

right or you know you're you're actually

31:05

looking at something and as an expert you can notice

31:07

you can notice right away what is

31:09

wrong with something and that pattern recognition is

31:11

something that makes us really powerful. I

31:15

think as we sort of proceed with

31:17

this. I think that's the joy

31:19

for some people. It's not the joy for others.

31:22

Sure. I'll speak for myself. I'm

31:24

I'm a second career in tech. I was a

31:26

writer and I worked in politics and

31:29

nonprofits. And so coming

31:32

from that into tech coding

31:35

was not necessarily the thing that brought me joy.

31:38

It's not to say that when you don't finally hit

31:40

that thing and then it runs and it's perfect.

31:42

It's like, oh, that feels so good. But

31:45

for me it was building tools that matter to people

31:48

and that is what

31:50

brings me joy. And I think that's going to the spark

31:52

of joy is going to be different for all of us and

31:55

finding joy in our work, no matter how

31:57

it evolves and changes. I think is important

31:59

for all of us.

31:59

of us as humans

32:02

and for our personal growth.

32:04

But I think it's, again, we set

32:06

the standards here. This is not happening to

32:08

us. It is happening with us. It is happening

32:11

by us. And taking ownership

32:13

of that and really kind of saying, OK, well,

32:16

these are the areas that we want to maintain

32:18

and grow and evolve with, and these are the areas

32:20

that we want to give up. I don't want

32:22

to write a CRUD service again. I just don't. I've

32:25

done it 1,000 times. We're good. That

32:28

can be done away with. I

32:30

want to solve the really complex problems. I

32:32

want to think about, OK, this hasn't been

32:34

done before. It's only been done at scale by a handful

32:36

of companies. How can I apply this to my

32:39

specific constraints and resources? That's

32:41

interesting. And I think it's that kind of problem

32:44

solving and looking higher up

32:46

in the stack and having that holistic view that

32:48

will empower us along the way.

32:50

Well said. You want to add? Yeah, I think

32:53

very similar. I can speak from just

32:56

my perspective of what I enjoy. I think it's the exact

32:58

opposite. This is what I've always said.

33:01

The exact same is what I meant. Sorry. I was trying

33:03

to bring Java, and I just don't naturally have it. Can

33:05

you disagree on something? I'll

33:08

try. On the next one, I'll come up with something. But

33:10

my favorite thing about being a developer is being

33:13

able to build. And with

33:15

code, we can solve

33:18

most problems. Now, there's other aspects, like

33:20

hardware and things that come with it.

33:22

But we solve the problems

33:24

of the world on a daily basis. And that's what's cool

33:26

for me. I can't remember if it was your talk or someone else's.

33:29

The way some people look down on no code, low code,

33:32

environments, or platforms, or whatever, I don't

33:34

care. I want to build the thing and see people

33:37

use it or just build a solution to a problem

33:39

I have. So I don't know. Same perspective.

33:42

On the next one, I'll come up with something controversial,

33:44

I promise.

33:46

A nice analogy might be stick shifts,

33:48

automatic cars, where no one's stopping

33:51

you from writing that function. Just go ahead and have fun. Write

33:53

it. But the rest of us are going

33:55

to use the thing to write the function for us. And if you

33:57

take joy from that, just go ahead and write

33:59

your fun.

33:59

There you go.

34:01

Got one. Don't know how to use one,

34:03

drive one. So boom, controversy. Hey,

34:10

they disagreed. All right,

34:12

let's get slightly

34:14

more philosophical and broader sweeping.

34:17

So we talked about the details. What about like

34:19

big picture changes? I'm thinking about open

34:22

source software. I'm thinking about

34:24

ownership of code. If an AI

34:26

writes 30% of my code, do I get 70% copyright

34:29

on that? Do I get 100%?

34:31

Does my employer get all the copyright probably? But

34:34

what about open source? Because this is like, you know,

34:37

these things are trained, you know, famously

34:39

and infamously on

34:41

publicly available source code. And so

34:43

that's our labor, whether we gift

34:45

it or not.

34:46

It is. And so what is this impact

34:48

of the lives of us developers who are either

34:51

working on open source or simply using

34:53

open source? It touches all of us. I

34:56

imagine some maintainers will

34:59

maybe think twice about having stuff be

35:01

truly open source. And I like, I think there's

35:04

a whole deeper conversation

35:06

about the impact of just like reading from people's code

35:08

and leveraging that to do other things and ownership

35:10

and stuff. So I could see some people

35:12

just kind of like bowing out of that and

35:15

kind of coming back into themselves, which

35:18

would be a shame, right? For that to not to be available.

35:20

I don't

35:22

know, there's there's so much that goes into it, like

35:24

from a political perspective, from an ethical perspective.

35:27

Honestly, if like you asked me that, and I'm overwhelmed, just

35:29

thinking about it, there was someone last night at the speaker's

35:32

sponsor dinner. And he talks about how

35:34

I think today, like he's worked on multiple

35:37

revisions of a pitch for

35:40

either ethics and AI or something like that over the

35:42

last like year, and it was giving another pitch

35:44

last night, and they were going to go through it. I

35:46

think we will have a lot to catch up on

35:48

to define that I have none of those answers.

35:50

And they drastically overwhelm me because

35:52

I can't begin to comprehend like the those implications.

35:55

But there has to be

35:57

like legally more

35:59

ethically, open-sourcedly,

36:02

like there has to be things that kind of catch up and

36:05

and give some sort of guidelines to the stuff

36:08

that we have going on.

36:09

Yes, and this is why I keep

36:11

pushing on responsible AI.

36:14

We have to have these conversations and they're

36:16

gonna be heard. There is an

36:19

economics, there's this concept of the tragedy

36:21

of the commons, it comes from a pamphlet of the

36:24

same title, and the focus

36:26

was really around the shared

36:28

common land that cow

36:31

herders or any kind of farmer

36:33

would utilize for their herds to

36:36

eat off of. And as individuals,

36:39

it benefits each herder to have

36:41

their cows graze the most, with

36:44

no limitations. But obviously

36:46

shared resources are finite

36:48

and and they are limited. My favorite

36:51

quote from that pamphlet is, ruin is the

36:54

destination toward which all men rush. And

36:57

I think we have to be

37:00

truly careful as we proceed here. A lot

37:02

of this is a common resource and it's

37:04

based off of a common resource. And

37:07

this is where I think communities around this is

37:09

really, really important and recognizing

37:12

our own power and influence on

37:14

pushing toward a holistic

37:17

and appropriate approach to

37:19

responsible AI.

37:21

That quote I thought you were talking about my code again

37:23

for a second. Yeah, I should

37:28

probably

37:28

go revert that comment. Um,

37:31

okay, have you guys seen this new thing you

37:33

can do? It's like robots.txt,

37:36

but it's for your, this is for website

37:38

copy. So I mean we're in the same realm, but

37:41

it's like no, no GBT.txt.

37:44

I can't, what's the actual technology you can do? No

37:46

crawl maybe. I

37:47

don't know, it's a brand new thing

37:49

they're working on where the

37:52

LLM crawlers will skip

37:55

your website, much like you can tell Google not to index your

37:57

website.

37:58

Is that something people

37:59

will do? Is that something that can

38:02

have an application into the world of open source?

38:04

I mean, maybe you said opting out of. Does

38:06

that mean not even publishing at all? Because

38:09

there's no guarantee that the

38:12

language model creators will necessarily

38:15

comply with a robots.txt, for instance.

38:18

What are your thoughts on that, the analogy there

38:20

and how it applies? I find it to

38:22

be unacceptable that

38:24

companies would push forward

38:27

with a profit only mentality and

38:30

not take these things into consideration.

38:33

And to some degree, between

38:35

our work and also where we spend our money, we

38:37

have to tell the

38:39

market that that is not acceptable. I

38:42

don't want to live in a world where we're trying to hide from

38:44

crawlers. I want to live in a

38:46

world where we have decided on standards and

38:48

guidelines that lead toward

38:51

responsible use of that information so that

38:53

we all have

38:55

some compromise around how we're

38:57

proceeding with this. I think it's super important.

39:01

Trusting people is a big ask. When I

39:04

said the thing about

39:06

people potentially retracting from open source,

39:09

as soon as I said that I kind of wanted to backtrack that in my

39:11

head and find out another way, and I immediately

39:14

thought about like a flag on GitHub that says don't

39:16

look at this code if you're an LLM. Something

39:18

like that could be useful. I think longer

39:21

term, having it

39:23

all figured out is definitely better. I could

39:25

definitely see that being a thing

39:27

that people would use, I imagine, if they

39:30

don't want their code to be used in LLMs

39:34

to just be able to opt out. That seems like a reasonable

39:36

intermediary step along the way.

39:39

I think we would have ‑‑

39:42

we would start to argue around definitions of open

39:44

source because the freely available ability

39:47

to use without restriction is

39:50

part of the tag line.

39:52

Maybe it's source available kind of

39:54

things where maybe in these starts to say

39:57

I'll put my source code out there, you can do everything except

39:59

this.

39:59

and we have a new license that's not open source,

40:02

but it's something else. I think time will

40:04

tell.

40:04

And it just gets so hard to prove too,

40:07

right? Like it's like cheating on a homework

40:09

assignment in college, which I never did, question

40:11

mark. Like they had these things that

40:13

would compare your code against other people's assignments

40:15

or whatever from previous years. I'm sure that's gotten more and more

40:17

sophisticated now. So that would

40:19

be one of those things where if you had a opt

40:21

out flag and then you come across a

40:24

repo that has code that looks like yours, like

40:26

there's no way you could prove that without diving into

40:28

like the logs from the AI that generated

40:31

that kind of like you just have, I don't know, that'd

40:33

be so hard to prove. Again, coming back to like ethically

40:36

and legally, we have a lot to

40:38

figure out, I think.

40:39

Okay, how much time do we have? I think, is it, is this 12 15?

40:43

I think so. We got five minutes.

40:45

Okay, anything that wasn't addressed that

40:47

you wanna make sure gets addressed here. I'll take the mic.

40:50

I'll run it to him.

40:51

You stand up here and answer. There's

40:56

been a lot of discussion about, you

40:58

know, how gen AI has been hyped or overhyped.

41:01

My question is, maybe this is a way for

41:03

you to disagree. What do you think is the most underhyped

41:06

technologies around AI? I

41:09

think I kind of agree with Emily that the trustworthiness

41:11

of AI is the most underhyped, but

41:14

what do you guys think? Especially

41:20

in the conversation here from a technical perspective,

41:22

I think the most underhyped

41:25

thing is how much it can be used to things

41:27

that are not just writing code. And I mentioned this earlier,

41:30

just from a spark of creativity, like I sometimes

41:33

limit myself mentally because I don't think I'm creative,

41:35

although like if you look for pieces

41:37

of things I do, like it's there, but like I can

41:40

use something to just give

41:42

me ideas for stuff when I'm stuck and it doesn't

41:44

have to be technical. And I think that's super,

41:46

super value. And thinking about like an onboarding of how

41:48

to incorporate it, what easier way

41:50

to incorporate some AI into your life and

41:53

to just like give me an idea for something

41:55

to do this weekend that would be fun with

41:57

my like partner's mouth or whatever, right? So I think just.

42:00

on a regular outside of code perspective, there's

42:02

so much that you could get out of it from a creativity

42:04

spark. And I think that's a lot of fun, and I think it's

42:06

easy to get started that way.

42:08

I keep coming back to the, for

42:11

me the hype is around the speed and scope

42:13

of AI. When

42:16

I quoted Marvin Minsky, bless him,

42:17

who believed by 1980 we'd have

42:19

a human analog. Obviously

42:22

that's not true. And when

42:24

you think about how quickly this kind

42:26

of came to market, it feels really fast,

42:29

but a lot of that had to do with 2018

42:30

transformers coming about and us

42:32

being able to actually proceed with this. But

42:35

when you look at all of artificial intelligence,

42:37

it's truly been eight decades

42:40

at a minimum.

42:41

And so we're kind of coming to a place where

42:44

there is that distribution, but

42:46

I fully expect it to still take some time

42:49

before widespread adoption, before

42:51

efficient uses, certainly

42:53

affordable uses, and where

42:56

we can actually apply this

42:58

to higher risk scenarios and industries.

43:01

Time for one more, I think. Yeah, and this

43:04

use of the term tools in a kind of a neutral

43:07

way to describe AI kind of broadly,

43:09

I think what's been left out maybe

43:11

is that different tools have different side

43:14

effects.

43:16

So for instance, video games

43:18

have certain characteristics, shovels

43:20

have other characteristics, and

43:23

still other characteristics. Where

43:26

do you see these tools right

43:28

now and maybe in the future where we have to

43:31

look at societally, are

43:34

they more like shovels or opiates?

43:37

Oh, I like that.

43:39

I like that last line there. Good question.

43:43

That last line took a hard left.

43:46

I think we don't know.

43:48

There's no way to know. I think we can sort of think

43:50

about the next three to five years and where we think

43:53

this will go, but I think anyone

43:55

who claims to be a sort of futurist or

43:57

believes that they can tell you in 50 years what this

43:59

is. looks like, they're just guessing.

44:02

You might as well throw a pin against the wall. We

44:05

just don't know. But I think, truly, I keep

44:07

coming back to this, we have ownership and responsibility

44:10

over this. And we can kind of determine what

44:12

this actually looks like in usage.

44:16

Shuffle versus Opiate is like

44:18

a t-shirt waiting to happen. It's

44:21

such a good and kind of easy call

44:23

out for people. It's kind of funny, but I think it's very serious.

44:27

All the ethical legal implications, we talked about that, like

44:29

there has to be catch up. I think we also just

44:32

have to acknowledge that this is also the same

44:34

as every other advancement that we've ever had. Like you think

44:36

about, I don't

44:38

know, people that want to use things for

44:40

nefarious ways, people that want to use things

44:43

for their own purpose that

44:45

hurts other people or affects other people in

44:47

negative ways. It exists,

44:50

unfortunately. And so I think it's even more

44:52

important for the concept

44:54

of responsible AI. But

44:57

also just acknowledging that there's probably

44:59

a point where we need to have limitations, like what that means

45:01

and what that looks like. I don't know. Do we get to a point

45:03

where we're in iRobot and that's where we're living

45:05

on a day to day basis and we have to prevent that? I

45:07

don't know. I

45:10

think with great, what is it, with great power

45:13

comes great responsibility. And I think that's absolutely

45:16

true here.

45:17

One more quick one.

45:18

So there's a lot of talk about AI

45:21

tools that help you write code, but as

45:23

a developer, a lot of my time was spent actually

45:25

supporting code or maintaining code. And

45:27

there isn't a lot of tools out there that helps

45:30

you fix bugs, or I don't

45:32

want to read someone else's code and fix their bugs,

45:34

but that's what I spend my time doing. So

45:36

why do you think we're in the state we

45:38

are now and what can we do to build

45:41

more tools that eliminate that

45:43

tedious part of coding?

45:48

So for my first, I think I have

45:50

seen at least people talking

45:52

about that use case. I don't disagree

45:54

that there's more tools focused on the generating

45:57

of code, but I have seen people post on Twitter

45:59

and things. of like give it a code snippet,

46:01

tell me what's wrong with this or explain this piece

46:03

of code. So I think that's starting to get into

46:05

what you're saying, although the toolage may not specifically

46:08

exist as much as we may want for that use case. What

46:11

I think is really cool, and I think this goes back to probably

46:13

the most undervalued aspect of AI,

46:16

is the fact that not only does AI exist, but AI

46:19

exists in a way that we as developers can consume

46:21

it to build other things. That means that

46:23

we see a gap in tooling to

46:25

address exactly what you're saying. We don't

46:27

have to build all of that logic from scratch. We

46:29

can build a nice UI on

46:31

top of an already existing LLM

46:34

and be able to start to provide the things that you're

46:36

looking for more specifically. Now eventually you get

46:38

into more custom trained LLMs and that sort of stuff.

46:41

But I think that's the beauty of having

46:43

it be accessible, at least in certain ways, for

46:46

us as developers to build on top and go and solve

46:48

those use cases.

46:51

That was well put, and I expect more tools

46:53

in the future. I think we we led with the thing

46:55

that we knew we could execute on as

46:57

an industry, and that seemed like the most

47:00

straightforward path. And as we

47:02

diverge from there, I think you'll see a ton of tooling

47:04

around solving those problems. But yeah,

47:07

I still believe that those kinds

47:09

of the fixes, the plugging

47:11

everything together, the integrations, that will be

47:14

probably something that takes a long time.

47:16

Okay, that is all the time we have. Thank

47:18

you all for coming and let's hear it for the panelists.

47:36

Special thanks to Todd Lewis

47:38

and his amazing team of organizers for bringing

47:40

us out to All Things Open. This panel

47:43

was just one of the many conversations that

47:45

we recorded from the show floor. Subscribe

47:47

to the changelog podcast if you haven't

47:49

already for more All Things Open

47:52

goodness. Thanks once again to our partners,

47:54

fastie.com, fly.io

47:57

and typesense.org and to our beat

47:59

freakin' residents, Breakmaster Cylinder.

48:02

Daniel and Chris return next week, and

48:04

they're joined by Nathaniel Samar, the

48:06

creator of a deep learning framework and Rust,

48:09

called Burn.