So modern technology is empowering.
It's amazing, and it's connected usin ways that, uh, we'd probably get
into trouble with our ancestors.
They would accuse us of beingsupernatural, but to many of us,
we owe our livelihoods to this newtechnologies, the new technologies.
And one of the biggest inventions ofour time was of course the internet.
And as of July, nearly 70% of theentire global population have some
form of access to the internet.
That's where five and a halfbillion people in Canada alone,
95% of the population has accessto the internet in some way.
And so in some ways, it's acrowning achievement of humanity.
Today when you reach into yourpocket, you can take out a device
that's, uh, literally millions oftimes more powerful than the original
computers that got us to space.
And, you know, that's,that's really incredible.
Think of all the things we can dowith, with these new tools and even our
access to the internet is substantiallygreater than just 10 years ago.
When, um, only 34%,37.4% had access in 2014.
But what about when thesetechnologies distance us from others?
Is that still valuable technology?
Does it make it evil?
Should we avoid it?
In 2023, the US Surgeon General issued anadvisory that explicitly said loneliness
and isolation is a public health crisis.
This was a pretty important momentbecause usually those advisories are
reserved for the most significantpublic health, uh, issues that we face.
Other organizations like the WorldHealth Organization followed up shortly
after that, and there were others thatproceeded that, that advisory as well.
And so more and more people are dedicatingresources and recognizing loneliness
as a severe issue for our generations.
And as technology evolves very quickly,it's becoming clear that these new
technologies don't come without a cost.
The physical distance isbeing broken down every day.
We can call relatives or friends anywhereon the planet, but despite being more
connected, where considerably more lonely,
AI is poised to interact, uh,impacts humanity at a similar
scale to that of the internet.
The internet recently turned 40 yearsold, and we still don't know the true
impact of the technologies that theinternet makes possible, but we have
a good idea of generally where tolook, and we're already noticing some
really severe negative impacts of ai.
Some recent studies, uh, specificallyone done by MIT found that.
With higher overall dailyuse across all modalities.
So conversation types, whether it'svoice or um, text, that they can be
correlated with higher loneliness,dependence, more problematic use,
and even lower socialization.
So while AI can increase our efficiencyand reduce, it also reduces the
number of opportunities for us to havemicro interactions with other humans.
And especially with children andum, people who are still developing,
this is extremely important forunderstanding how to work with others.
Have self-confidence, knowledge,personality, think for yourself.
So writing research papers.
You know, especially with young people,it doesn't actually require them to read
a book at the library in some cases ifthey use the technology incorrectly.
Um, or for me it was a CD with anentire encyclopedia replaced this
big, uh, you know, the need to havea big bookshelf with a whole row
of books on there that were thickand heavy and mostly just the dust.
But I mentioned in some cases peopledon't have to think critically at all.
They can just, uh, instead of plagiarizingsomeone directly, they can have.
Uh, some thoughtful questions and AI cancome up with something that they can use.
So how do we deal with these newbarriers that innovations create, and
how can we more carefully adopt theseexciting new technologies without
creating new pitfalls or falling behind?
Another remarkable achievementfor humanity was coordinating
distributed collaboration withouttraditional social structures, and
we call this open source today.
The open source movement is reallya testament to the power of human
generosity and our desire toshare and collaborate with others.
Human connections are such a criticalpart of the open source concept.
If we're more lonely and less likelyto interact as a society, how does this
impact our open source communities?
Will using AI amplify those largertrends like early research shows?
Uh, will it damage open source in general?
There's open source technologyon, uh, just like the
computer that was on the moon.
There were open source technologieson that and still power rockets and,
um, pioneering, uh, initiatives today.
If you spend any time participating inopen source, you quickly realize that
there can be many reasons why a projectsucceeds or fails, but there's usually
one in particular that is present in themost successful open source communities
as, uh, projects as the most successful,most important open source is ultimately
a place where people go to call home.
They come to collaborate part.
And at the heart of all successful opensource projects is a community that cares
deeply about that project, the values,the mission, and each other At some level.
We don't just want our problem solved.
We want to be seen as we're solvingthem and participate and create bonds
with those that we solve them with.
Specifically in WordPress, thiscommunity is comprised of thousands of
developers, designers, polyglots testers.
Educators, marketers, and even ourusers, each contributor is responsible
for one of the many pieces that make upthis massive puzzle that's WordPress.
So how do we retainthe open source spirit?
As we introduce yet another layer ofseparation between us and the software,
our users, the others we collaboratewith, AI certainly does not care about
the impact that it has on those things.
But we must be responsible fortaking, looking after these things.
We should ask questions like, where docontributors expect human interaction?
Where is, uh, theirnon-negotiable interactions
that need to happen with humans?
Uh, where can it be used toguide humans through situations
instead of replace them entirely?
And how can we use AI for,uh, AI tools for our own use?
But recognize when those tools are notnecessarily great for larger communities.
So this has been a little dark sofar, but I want to, let's come back.
I'm very excited about AI and I, I haveto say that it's, it's going, like I said,
it's going to impact us at a, at a largescale like the internet has in my opinion.
There's a few specific things thatI'm most excited about with it.
Um, and I'll get to those in a little bit.
But it's important that we keep in mindto balance and carefully think through
everything that we're considering.
So I found preparing for this slide,I was doing a little bit of research
in the form of just looking updefinitions and seeing what, um,
these tools are actually defined as.
And, uh, what, what are the acceptedstandardized definitions for what we have.
When I talk about AI today,I'm going to specifically be
referring to large language models.
Um, I kind of call thatpersonal use AI because it's
what we interact with the most.
Uh, other things that we interactwith are more seamless, you know,
like neural network type stuff.
Or maybe when you go to the doctor,they're using AI to analyze some imagery.
Um, but again, in the context of the toolsthat we use within open source right now,
those are mostly large language models.
It is easy to see AI as this magicalsolution, but what is AI as we
really know it deep down today?
So this is one definitionfor large language model
that I found was interesting,
and then I went a little bit further andI looked at what the generally accepted
definitions for just language model was.
Models must be pre-trained.
These are the parts of the definitionsthat I kind of stood out to me.
The second part that stood out is thatlanguage models are merely trying to
predict and generate plausible language.
They're not creating sentences.
They're, they're, they're justtrying to figure out what makes the
most sense from the data that theyhave and that they're trained by.
The entire human experience is notavailable as consumer consumable data.
So what about languagesthat are spoken only?
They're not available in writtenform because they don't actually have
characters to represent their their words.
What about emotional depth that we feelall the time in our human interactions?
What about cultures that are notwell documented or studied at all?
What about our consciousnessand our persistent self of
being the same person over time?
For model, I went a step further and therewere 11 definitions in the dictionary,
and it was interesting that many of themcould go home and do this exercise as
well, but I found that many of them couldbe applied to AI loosely, and there are
a few that I found the most interesting.
And then the other thing that stoodout to me is that many of them could
be applied to both human and ai.
And that's when it getsa little bit different.
Uh, interesting.
And what I found was that
I kept arriving at this.
Realization that the AI that we know,even though it's communicating to us
in a human way, essentially, is justsolving a series of math problems.
Their language models and humans are thestandard that is trying to be imitated.
Many of the concepts that wehave around our existence can
be boiled down to mathematicformulas, but most of them can't.
Again, morality, desires, conscience,all of these things we can't
represent with ones and zeros.
So how can AI accurately considerthese factors when they're
producing these plausible languages?
Perhaps for these cultures and languagesthat are undocumented entirely?
Um, they would see them astotally implausible and never be a
realistic way to perceive the world.
They could even denytheir existence entirely,
but in the end, the humansoul is not a math problem.
AI is only currently analyzinghuman history as it exists
in data, and it's not.
It's making new discoveries thatare shaping our future, but it's
not yet charting our future itself.
So when AI reads something and it'strying to perform mathematical analysis,
the same thing is true when humansread something, but they're also not
restricted to solely what has been.
They can also take into accountpersonal experiences, their culture,
their core beliefs, and all the thingsthat make us unique in who we are.
Communities at large also havethese beliefs and missions
and democratizing publishing.
Um, we have project philosophiesand again, AI cannot replace the
way that we personally analyzethose things, at least not yet.
And hopefully they, uh, see mytalk and know that, heard that
slide about they like, I like ai.
Um, in the context of software, I try tolook at AI as a new and really, really
good form of automation that's flexible.
This can be very helpful to frameit, uh, by framing it this way.
It's very helpful to, uh, guideyou into making decisions about
good versus bad, uh, AI usage.
Uh, there's a great book calledProducing Open Source that I
recommend anybody interested inopen source communities go read.
Um, it's by Carl Fogo and heintroduced a concept in one of the
chapters called the Automation Ratio.
And essentially it's that if someoneis, has to repeat, uh, a task, it's
worth at least 10 times the amountof effort to automate that task than
it is for someone to do it once.
He goes on to say that very frequentor complex tasks, that ratio could
easily go up to 20 or higher.
Sometimes individual developers aretrue wrapped up in the low level work
to see the big picture and realizethat by performing these automated
automatable tasks manually, frequently,or wasting considerable amount of time.
So here the term automation isused pretty broadly and it's any
repeatable action where one ortwo things could change over time.
Um, but any sort of technicalinfrastructure that assists humans
taking steps, eliminates notmerely waste, but it can also, uh,
eliminate the potential frustrationwhen someone makes a small mistake.
Especially when things ha have strictguidelines and are deterministic.
That's what computers were reallyinvented for, and that's what we
do as engineers and programmers.
We define those guidelines.
And even though this book was from overa decade ago, it's still very relevant,
um, in many aspects of open source.
But I found this section to berelevant specifically to AI because.
Um, AI again is solving deterministic,um, problems based on your prompts
that you write and the data that it hasavailable to it, and trying to accomplish
the tasks that you're asking of it.
Each and every time we proposechanges to the code base, they're
always examined carefully.
We'll, last questions like,what problems is this solving?
How prominent is this problem?
How many people is this problem affecting?
What is the demand for this feature?
How does it help our end users?
We also consider thingslike the opportunity cost.
That's a concept where if you putyour focus on any one specific
thing, in some way, you're drawingattention away from another problem.
So we experienced this duringthe lead up to WordPress 5.0 In
the form of the block editor.
There was a particularly high opportunitycost to draw anyone's attention away
from that effort to get that blockeditor ready for, uh, primetime.
And so there were very few otherfeatures that got attention in that
year leading up to the block editor.
So in that case, it was not worth theopportunity cost to draw people away.
And our tools can do the same thing.
By working on these tools, they maynot be solving an important enough
problem, and it might be distractingus from priorities for our release
or any other, um, initiativesthat can have a greater impact.
In general, the best ideas arealways well scoped and practical.
They're rooted in realworld user problems.
They're maintainable, testable,and ultimately compatible with the
project's, philosophies and roadmap.
The same should be true for any tools thatwe consider to help with our automation
and our, and even our communities In thesescenarios, the members of our community
are our users consuming or distracting.
Uh, our contributors are a fewof the opportunity costs here.
Implementing an AI bot or somethingthat, um, generally provides
not a high level of value.
It's essentially gonna just taketime away from contributors to
acknowledge that or review thecomment, make sure it's correct.
And while it's very tempting to choose allthese new, shiny tools and implement them
quickly, we need to resist that temptationand spend a bit more time building
consensus that it's a good change.
Be impartial about the tools that we'reevaluating, and again, determining
how it best solves that problem.
The other thing to consideris that no tool is free.
This can be monetary, but it can alsobe from a maintenance perspective.
When you introduce a new tool,what is the level of maintenance
required after considering that cost?
Is there even a net positive benefit?
Is it only that specific toolpresenting a net negative benefit,
or is solving that problem ingeneral, a net negative benefit?
And maybe that's not theright problem to solve.
Perhaps just wait untila couple more years.
The great thing is that, uh,no is not forever, but yes is.
So once you commit something, especiallyin WordPress with backwards compatibility,
uh, we say yes to something where, uh,we're committed to maintaining that
and not breaking sites by removingit or changing it in certain ways.
And so no is very easy to revisit.
But again, yes, is haslonger consequences.
Uh, another thing to consider iswhat are the greater factors at play?
What happens if the AIdemand skyrockets even more
exponentially than it has recently?
And our utility grids are stressedand the providers have no cha
no choice but to extremely hikerates in order to tame the demand.
If you are a hundred percentdependent on certain tools.
What does that mean for thereliability of your software,
the contributing experience?
Can people even contribute at all ifsomething is too expensive anymore?
Um, and what's the cost to spend thetime to disable that or remove that?
Despite being more lonely and moreavoidant, it's still our human nature
to long for interactions with others.
Participating in open sourcecan be really humbling.
You need to have awillingness to be vulnerable.
Uh, you're working inpublic, what if you're wrong?
Everybody will see that youwere wrong or made a mistake.
Imposter syndrome can be veryreal and sometimes it's even
more amplified in open source.
But I hate to tell this, tell you this,but in reality, nobody actually cares.
Nobody.
I can say that as I look atpatches and I find mistakes.
It's not, um, I don't, I don't view itas, um, it, it's not, it doesn't affect
the way I see someone in general, as longas those people are open to learning and
they are taking feedback open to feedback.
You can always know that they'regoing to improve, and that's
always the goal in good communitiesis to help everybody improve.
But nonetheless, it's very scary.
How would you feel if you observed.
Uh, an open source community for severalweeks, maybe even years, and it took
that long to finally understand howthings worked and work up the courage to
submit a bug request or submit a patch.
How would you feel if the firstinteraction you have is from an LLM?
Would you be disappointed?
I would be.
I feel very strongly that thefirst and the last interaction
should always be humans.
I don't feel that closing thingsusing AI or automated in an
automated way is, um, helpful.
While it might clean up your backlog orlower the number of tickets that you have,
ultimately it's not benefiting the peoplein your community that are participating.
As I mentioned, it's quite scary toparticipate, especially for the first
few times in open source, and so notonly engaging this person as a human
is respectful, it's an acknowledgementthat they receive and they feel
seen welcome, like they belong.
Automated responses can feel disingenuous.
We don't have time to respond to you, sowe've set up this LLM to do it for us.
In any healthy community,you will never feel.
Like you are unwelcome orlike you're an inefficiency
that, um, is being dealt with.
And also it won't fix the issue becauseif the ll if you don't have, uh, a reason
to implement that would be that tickets,new tickets are going a long amount of
time without receiving a response, butimplementing an AI to respond to that
doesn't really do anything to fix that.
It's still gonna sit there.
They're gonna get that disingenuousresponse, and they're gonna get
probably even more frustrated thatnobody circles back to answer them.
When you go into something expecting,uh, a specific outcome, it's
always disappointing to have anexperience that's the opposite.
Genuine interactions that meet ourexpectations are one of the most
important contributing factors tostrong relationships and communities.
So instead of forcing AI on members ofour community, maybe the best approach is
to allow them to configure the level ofAI that they are interested in receiving.
This allows them to cater andcommunicate their expectations
to shape their experiences with.
The community they're involved with andthe way that they would like it to be.
So maybe, um, you know, someonecould choose to ex uh, to enable
copilot on their pro requests or not.
They could choose to.
Um.
Maybe when their poor requests are drafts,they could receive AI feedback, but
once it's ready for review, they wouldswitch to only receiving human feedback.
All of those are just some, somesmall ideas that you could use
to shape how you, um, how your,your community is interacting with
the tooling that you implement.
While you shouldn't lose sight of thefact that most software, um, especially
WordPress is end user focused whenit comes to democratizing publishing.
This has meant humans for many years.
We usually expect our users to be humans,but robots and AI are also users too.
When you strip down a website tothe bare basics, you find HTML.
And HTML at the core is astructured markup language with a
defined syntax that computers cansystematically parse and intercept.
Um, it's predictable, it's semantic,and of course this has been true since
the very beginning of the internet.
Since then, many other technologieshave been introduced, like R-S-S-X-M-L,
rest, JSON, and as they're createdto solve specific problems.
Um, they each have their owngoals, but they all have been
done so in a standardized way.
They also do so in a way that machines canconsume that data and interact with it.
Um, and of course process it ina way that it can be displayed
to people and, and users.
In the case of ai, thisshould be no different.
The common approach currently is touse an MCP server, which at its core
uses the J-S-O-N-R-P-C protocol.
While this talk is focused on how weimplement AI tools in our contributor
workflows and communities, we shouldensure that our community processes
and history are also accessibleby both humans and machines.
Otherwise, M-C-M-C-Pservers and other AI tools.
May end up missing substantial chunksof history data that could be used to
produce more accurate, uh, results thatcan ultimately help us and be more useful.
It's pretty naive to say that contributorsnever churn out of open source projects.
Uh, contributors change jobs.
They change interests.
They have life situations that change.
Perhaps they have alwayscontributed in their free time,
and now they have a family thatrequires more of their attention.
Uh, companies change tech stacks,and while that's unfortunate, uh,
while it is unfortunate, contributorsdo burn out as a maintainer of any
code base, it's important to have.
The historical context readily available,uh, without having to spend hours
digging through history and conversations
in the WordPress project.
One of the main ways we do thatis through our commit messages.
Um, these are the guidelines as laidout in the WordPress core handbook.
Um, but basically the commit messagesare used to convey a, a handful of things
about specific changes that are made.
Um, they provide a lot of context and thatcontext can be very helpful in the future.
They also document any considerationsthat may have been made that
lead up to the given change.
And it's not just for the present,uh, users of the software and
people building the software,but it's also for the future.
As a committer, I spend a largeamount of time digging through
commit messages to understand whythe code I'm about to change is.
Uh, existing in the current state,what problems were solved, uh, on the
way to getting the code to the state?
What considerations were madebefore finalizing these changes?
Understanding these things help to ensurethat no regressions are introduced or
that we don't repeat past mistakes.
The most important, well, one of themost important sentences in this.
Uh, section to me is that theydescribe the what and the why of
the change set, and not necessarilythe how, the how is described in the
actual changes of the code itself.
AI is really great at figuring out thewhat part and explaining the how, but
frequently it struggles with the why.
Why is this being doneand why is it important?
And this for our humans tryingto understand things is arguably
the most important part of that.
The other piece I found thatwas interesting is it also
calls out multiple audiences.
Uh, future contributors andcomputers were two of those examples
by writing descriptive, thoroughcommit messages where, uh, we
were intending to help humans.
But even a decade plus ago,when this was put in place.
Since then, we've essentially been helpingto train AI models to be more efficient
without even realizing that that'swhat we would be doing in the future.
As I mentioned, uh, AI cannotreplace humans, and so naturally
it cannot fix people problems.
In general, AI shouldnot be making decisions.
Humans in the end aremaintainers and not ai.
And all of that is because of those,those aspects of, uh, humanity that
we can't actually present in data.
We can't ensure that the modelwill consider all of the necessary
aspects and perform the rightcritical thinking, because in
the end it's just math problems.
It can be used to provide summaries orpresent possible issues or compatibilities
that we can use to consider in ourdecision making, but humans should
always be performing that final analysis.
Of all the information available to testand confirm the strength of the presented
rationale in making the decision.
AI will not, uh, most importantly, notsolve any bottlenecks that may exist at
this stage of the change lifecycle thatmakes it even more important to implement
AI thoughtfully in our communities.
If AI is used in a way thatdamages the contributor pipeline.
It will eliminate ways that beginnercontributors can participate and grow.
It'll eliminate mentorship opportunitiesbetween senior and junior contributors.
We could end up slamming the door onthe faces of those people who are very
competent and interested and capable ofbecoming future maintainers potentially.
And I know it said it can't, but it canall, it can fix some human problems.
These are the instances that I'm mostexcited about that I mentioned with ai.
WordPress, uh, unfortunately is not easyto contribute to if you are non-English.
I think that 57% of all WordPresssites now are non-English, and so we
have an incredibly wide reaching, uh.
User base that's not necessarily fluentin English or understands English,
especially where they're even wherethey're needed, uh, to participate in
a multilingual way, like translations,you have to know English to be able
to use the translation interfaces.
It's a little, I know it seemssilly, but again, in general,
the WordPress project is, um, bydefault is an English US language.
But what if you could submit a bug reportin any language, and it was automatically
translated into the language that someoneelse has configured as their preference?
How many more contributors wouldparticipate if 1% of the users of
the software that powers 43% ofthe internet tried to contribute,
but were not fluent in English?
That's thousands of people.
How much greater could our softwarebe with their input and their help?
Consider word camps.
What if every word camp tookplace in the native local tongue?
How many more people would bedrawn to it from that local area?
With AI providing live translationslike the new Apple AirPod software
language doesn't even really matter.
You can participate in any language.
You can travel to anywhere and not haveto study with Duolingo, though you should.
And I, I aspire to, butdon't do great with that.
I, I struggle with picking upnew languages and so having these
tools available to, to me andothers is, is really, uh, has
high potential to be impactful.
What, what if anyone attended anyWord camp and just spoke whatever
language they wanted, even in thehallway tracks or, uh, in sessions.
And everybody would beable to just understand it.
Different culturescommunicate in different ways.
Um, some are more dry and direct,and others perceive that to be rude.
What if there is a way to haveAI translate our communication
styles into more neutral phrasing?
It could help prevent misunderstandings,um, better understand the intentions
behind our, our contributions.
All of these are ways that we canenhance the human experience by creating
new pathways for connections andallowing more people to participate.
When we implement, uh, these newtechnologies thoughtfully and
intentionally, we can strengthenour communities as well as
sustain them in ways that likethe, um, impacts of the internet.
We don't yet understandand can't anticipate.
We never hear, we have too manycontributors or maintainers.
And so the great thing aboutAI is we can make use of it
to get more people to help us.
When we look at these tools, also weshould consider, do they align with
our ideals, our philosophies, ourmission to democratize publishing
or open source ideals in general.
One of the main things that we considerwhen we are looking at libraries
that we should merge into core oruse for certain features is how they
align with this project's ideals.
And the same should be truefor the AI tools that we use.
Remember that in the end, AI is technologythat's just posing as a human, and our
brains are tricked to believing thatfacade by, in a similar way, to how we
lose, uh, sight of the fact that there arehumans on the other side of the screen.
These in, uh, these in-person events areextremely valuable in that sense that
it's a great way to rehumanize thosepeople and those connections that we have.
Going back to Carl Fogel's book, he alsosays another thing that we should be
aware of the temptation to over automatebecause that can, uh, it can, what makes
free software project work is the careand the intelligent expression of that
care by the humans that are involved.
Open source is a place where peoplecome to belong, to participate,
collaborate with others.
The technical infrastructureisn't really about giving humans
easy opportunities to apply care.
Open source may not be valuableor attractive to some if those
opportunities go missing.
You need to be able to see yourselfin community where you need to have
different representations present.
We need to take stock in what'simportant to us and our me,
um, to you and your peers.
What helped us achievethe success that we have?
How did we get where we areand how can we preserve that?
Things to think about as you implementAI in your daily projects and life are
all of these things that I've discussed.
Be sure that they're the right tools andthat you're willing to stand by them.
In most cases, you won't have to force atechnology, but there are instances where
you do need to force a change becauseyou believe it's the right thing to do.
It's also in our nature to resist change,and so you might encounter resistance
when adding new AI tools, but again, beconfident in why you're doing it and what
you're trying to accomplish and solve.
And don't be afraid or weary of ai in theend, embrace this new technology, but.
Firmly protect our communitieswhile we're doing so.
Thank you.
Alright, I made it.
We have a couple of minutes for questions.
Yes, it works for me.
Just a couple though.
That's okay.
Yep.
Thoughts about open source AIprojects, including the ones being
funded by the Mozilla Corporation?
Yes.
I think that open source projects.
Uh, open source AI projects area great, uh, potential way that
we can put, uh, AI into core.
And so those are runmostly in your browser.
They don't.
Rely on a centralizedservice for the most part.
And so to me that's a great way to find,um, opportunities to use tools that
align with our ideals within the softwareand make AI available to our users.
Yeah, so I'm, I'm definitelypro considering those.
Um, but that said, again, doesdoesn't mean we should close the
door on other non-op source versions.
Uh, perhaps we have, um, plugins,right, that they can submit to
the directory that they can.
Purchase their own access token.
Um, but generally I'm anti anythingthat requires a token or, uh, a
cost, a paid plan in core itself.
And so I think those are a great wayto make AI more accessible to the
43% of the web that users WordPress.
Yeah.
Is, do you think it's possible orAI is a threat to, uh, developers?
Um, yes.
So I was having some interestingconversations, uh, this, this week.
And one of them was someone that, uh,they helped mentor, uh, kids that are
interested in coding into how to preparethemselves for opportunities out there.
Uh, and so I,
I worry about them.
I also worry about.
And I'll come back to how we canaddress it, but I also worry about the
people that have already committed twodegrees in the field and those jobs
have dried up those entry level jobs.
Um, and so I think that we need to thinkmore carefully about what we're replacing
when we introduce these tools, becausethe result right now is we're, we're
replacing a lot of junior level positions,but there will come a time where.
All of a sudden there's no more seniorlevel people because they're not
starting off and learning and gettingexperience, or they will be there at
senior level, but they will have ahuge blind spot in their experience.
Um, and so I, I think that's, that'spart of what being thoughtful is
not just within your community,but as a whole in, in your trade
and, and things of that nature.
How are our decisions affecting that?
Um, and I think there will besome realization eventually that.
You know, AI is really great.
It can do some things really efficiently,but actually we're spending more time
reviewing this junior level code from AImodels than we are, uh, when we actually
have physical junior developers thatare being mentored by our senior staff.
Um, and in my eyes, it's a,um, it's a future risk and
liability to be cutting that out.
Uh, and so I hope that soon we getto a point where we can realize that.
Okay.
Um, and fix it.
The other aspect is that you can continueto learn great foundational skills like,
uh, analytical thinking, uh, how to makedecisions, how to communicate properly,
how to, um, all all of those things.
How to have good foundationalprogramming concepts.
Um, all those things will translate andeven when using ai, uh, being able to
express those things to the model couldhelp you have a better effect in the end.
So, um, you know, it'skind of kinda like writing.
Everybody learns to write and theymight use it differently, but those
are, those are great skills to haveanyway, even if you choose to pivot into
another trade or another job in the end.
So, so, yes.
But hopefully not for long, butalso it might be different in a
few years how those jobs fit in.
Yeah.
Thank you very much,
Jonathan.
I too am very excited
about the.