Speaker 1: Here we go another episode of Adventures in DevOps. Jillian,
Speaker 1: thank you for joining me as co host today. Hello,
Speaker 1: Warren is off on vacation getting some much needed rest
Speaker 1: and relaxation and also joining us today, Vernon Keenan from
Speaker 1: Salesforce DevOps.
Speaker 2: Welcome, Vernon, Thank you, thank you.
Speaker 3: It's great being here. I hope, like, I'm sure some insights.
Speaker 2: Dude, I'm pretty sure you can.
Speaker 1: Because I'm particularly excited about this because it's not very
Speaker 1: often that I get to hang out and talk with
Speaker 1: people who have been doing this longer than I have.
Speaker 2: So I'm not trying to like throw out your age
Speaker 2: or anything, but I feel like.
Speaker 1: You know, yeah, I take it as a badge of
Speaker 1: honor that I've been doing it this long, and so
Speaker 1: when i meet someone who's been doing it similarly, I'm excited.
Speaker 3: Well, thank you, yah. I've been doing it for forty
Speaker 3: five years now, that's a while. Started my career at
Speaker 3: the Northwestern University working in the medical school, and then
Speaker 3: had a great chance to work at Genentech in the early.
Speaker 4: Days, and that was what were we doing there.
Speaker 3: I was doing clinical research, so I was actually one
Speaker 3: of the first people to see the results of the
Speaker 3: clinical trials because I was doing data analysis and we
Speaker 3: used a product called SASS, and of course, because we
Speaker 3: were genetic and we thought we could do anything, we
Speaker 3: decided to write our own clinical research product. How hard. Yeah,
Speaker 3: that was. That was a lesson in humility, right because
Speaker 3: because we we we learned that Oracle did a much
Speaker 3: much better job at that particular product.
Speaker 4: Than we ever cracked down some hubrist So I'm sure
Speaker 4: it was all fine.
Speaker 3: Yeah, yeah, I mean it still happens all the time,
Speaker 3: you know. I talk to enterprises all the time, and
Speaker 3: people still waste their time doing custom projects they could
Speaker 3: buy out there.
Speaker 1: I think it's one of those It's one of those
Speaker 1: lessons that you can't teach anyone.
Speaker 2: They just have to learn it themselves.
Speaker 3: Yeah. Yeah, I mean, because you're so conceived, you know,
Speaker 3: you know that you think your requirements are so unique,
Speaker 3: You think your requirements are special, You think that your
Speaker 3: talents and your abilities are special. Well, it turns out
Speaker 3: they're not, generally, because usually what happens is a software
Speaker 3: company is going to find somebody who is much better
Speaker 3: at those qualities than you are, because they're going to
Speaker 3: produce it for ten times as many people and they're
Speaker 3: going to make ten times as much profit, so they
Speaker 3: have as much, you know, ten times as much motivation
Speaker 3: to find to find the right people. So but that's yeah,
Speaker 3: I got started there, and then I had a fascinating
Speaker 3: early career. I was that I was at Oracle and
Speaker 3: actually Mark Benioff himself hired me there and I was
Speaker 3: working for him, and I had the unique experience of
Speaker 3: going into the corporate visits center all the time and
Speaker 3: I was basically just lying my butt off all the time,
Speaker 3: drawing boxes on the board, putting putting arrows, talking to
Speaker 3: the CEO of various global companies, saying, yeah, we can
Speaker 3: do this, we can do that. We look at this
Speaker 3: application server. It puts everything together, and it was all
Speaker 3: It wasn't true. It wasn't true. That's that's what I
Speaker 3: call the first act of enterprise software. We basically said
Speaker 3: everything was gonna it was going to work. And then
Speaker 3: and then it didn't.
Speaker 1: Like first act like a Shakespearean tragedy where you know
Speaker 1: what acts too, and there you're going to be like.
Speaker 3: Well, yeah, I mean act too. I think was the
Speaker 3: data Lake data warehouse era. We tried to put everything
Speaker 3: into like a secondary storage area, and we still didn't
Speaker 3: get transformation and we still didn't get you know, new
Speaker 3: capabilities out of that. And hopefully we're in the third
Speaker 3: act now where maybe things will come.
Speaker 4: It is just going to do it for us, That's
Speaker 4: what I think. Well, my data anymore? Who who needs
Speaker 4: even Mango dB when I've got AI.
Speaker 3: We could delve into that a little later, I guess,
Speaker 3: but but yes, So my friendship with Mark Benioff is
Speaker 3: kind of interesting because I recently renewed it. It was
Speaker 3: fascinating because I wrote a blog post that got his
Speaker 3: attention that said why Salesforce trailblazers don't care about AI?
Speaker 3: And my phone started blowing up and I and I
Speaker 3: was have renewed my friendship with Mark. So so that
Speaker 3: is that that's interesting as well.
Speaker 2: So what's your take on that? Why don't they care?
Speaker 3: Well, the reason was because they didn't actually put it,
Speaker 3: make it available in the product. So the thing about
Speaker 3: Salesforce that I liked as a you know, like I
Speaker 3: got my first Salesforce account actually way back in nineteen
Speaker 3: ninety nine, and I've been using it, you know, on
Speaker 3: and off, and I actually built my own business on
Speaker 3: it about starting in twenty twelve created a whole enterprise
Speaker 3: product for telecom that I used in my business. And
Speaker 3: the reason why I thought that the Trailblazer community was
Speaker 3: so active and so forthcoming with chips and tricks and
Speaker 3: like techniques and sharing and things like that was because
Speaker 3: the SaaS pricing model basically gave you all you could
Speaker 3: eat for a fixed price. So any Trailblazer would be
Speaker 3: able to like go to the set up menu and
Speaker 3: search for a new feature, for example, and then they
Speaker 3: could just like start trying it out. So those capabilities
Speaker 3: were always in there. But because AI seems to be different,
Speaker 3: mainly in terms of the cost that the companies have
Speaker 3: to burden to provide it, they didn't do that. They
Speaker 3: made you order a product. So while they were all
Speaker 3: carping and you know, saying AI this and AI that,
Speaker 3: like ninety five percent of the Trailblazers out there couldn't
Speaker 3: get access to it. So that that was my point.
Speaker 3: And the thing that was a fascinating story actually is
Speaker 3: that what happened was Mark read that they sent me
Speaker 3: the keynote and I actually was able to like edit
Speaker 3: the keynote and tell them what they should fix. Oh wow,
Speaker 3: And this is like three days before Dreamforce, and and
Speaker 3: they I sent it back to them. They put all
Speaker 3: the changes in, They changed product timelines, accelerated timelines, and
Speaker 3: just you know, made a bunch of people, you know,
Speaker 3: you know what happens with the CEO says do things
Speaker 3: to a bunch of people they weren't expecting to do
Speaker 3: things like over the weekend and.
Speaker 4: Weekend that at all.
Speaker 3: That's right, it's gone. You know. It's like plus, you
Speaker 3: got all the stress of you know, Dreamforce coming up,
Speaker 3: all the prep and now they got to change all
Speaker 3: the products. So they changed it. They actually included a
Speaker 3: free version of their new Agent Force thing in a
Speaker 3: new go to market version of their product they call Foundations,
Speaker 3: which is kind of like you can just buy it
Speaker 3: with a credit card as opposed to dealing with one
Speaker 3: of their account executives. They so they actually changed the product.
Speaker 3: Not sure how effective that was, but kind of just
Speaker 3: like in any situation, when it did, it just peeled
Speaker 3: the onion a little bit and revealed another problem underneath,
Speaker 3: which is how are they going to charge for it?
Speaker 3: So they haven't really figured it out yet is the answer.
Speaker 3: So there's a lot of confusion out there. In the
Speaker 3: Salesforce world as to how they're gonna pay for it.
Speaker 3: The all this magical AI stuff. Sure it keeps talking
Speaker 3: about for sure, But so get back to the saastevops thing.
Speaker 3: I just tell my story a little bit more so,
Speaker 3: Like I said, I was in Telecom, I had this.
Speaker 3: I had built an actual tax engine on the Salesforce
Speaker 3: platform for Telecom, which is you can imagine, it's pretty complex.
Speaker 3: And I had an opportunity to kind of like leverage
Speaker 3: that tax engine outside of Telecom. And so I realized
Speaker 3: that Salesforce was kind of a bad platform for that
Speaker 3: because of its performance characteristics. You know, like if you're
Speaker 3: gonna have an API service, you don't want to rent
Speaker 3: it off as salesforceas it was just too much overhead,
Speaker 3: too many constraints. So I personally got into more of
Speaker 3: I think your world of DevOps kind of like the
Speaker 3: go Kubernetes world, and I implemented all of my stuff,
Speaker 3: you know, my new API, my new database everything with
Speaker 3: Go Kubernetes. It was beautiful scalables, you like, one hundred
Speaker 3: times faster than Salesforce. And so I had that, but
Speaker 3: you know, business wise, that project didn't go anywhere so
Speaker 3: I had all this wonderful new DevOps knowledge plus being
Speaker 3: the Salesforce expert, so I turned my attention back to Salesforce,
Speaker 3: and then I realized that they were in deep, deep,
Speaker 3: deep trouble when it came to release management. Basically what
Speaker 3: happened was Salesforce had an initiative in the late twenty
Speaker 3: tens was called the sfd initiatives where they essentially created
Speaker 3: a command line interface to their metadata API, and this
Speaker 3: enabled developers to pull configurations out of a Salesforce org
Speaker 3: and put them into a get repository. So now this
Speaker 3: is starting to sound a little bit more like a
Speaker 3: regular DevOps workflow, right where you have repository, you have
Speaker 3: a somewhat kind of a source of truth, and then
Speaker 3: you're able to deploy it again in some fashion, maybe
Speaker 3: to another org, or you're changing the deployment and you're
Speaker 3: redeploying it to add a capability, fix an error or
Speaker 3: something like that. So it turns out that the SFDX
Speaker 3: effort was noble and was good and actually was kind
Speaker 3: of sufficient to begin the DevOps movement within Salesforce. And
Speaker 3: so what happened was all these end users basically started
Speaker 3: to try to figure out how to use this SFDX
Speaker 3: tool to manipulate Salesforce. And then at the same time,
Speaker 3: a group of companies I'll name a few of them.
Speaker 3: The leaders are Capato and back then Flowsome, and another
Speaker 3: one that's come out is gear Set and all of
Speaker 3: these companies. What they did is they kind of operationalized
Speaker 3: that API or that CLI interface the Salesforce that provided
Speaker 3: end users and put a low code CLICKI interface on
Speaker 3: top of that capability, so that Salesforce admins and other
Speaker 3: folks who were accustomed to a low code interface could
Speaker 3: start to do release management in a more rigorous way
Speaker 3: using tools like get or vs code or things like
Speaker 3: that to you know, have a more kind of rigorous
Speaker 3: development effort. But at the same time, it was still
Speaker 3: constrained a lot by the way that Salesforce works. So like,
Speaker 3: here's here's a crazy thing. I mentioned this metadata API, right,
Speaker 3: and you think that this metadata API would love let
Speaker 3: you to actually pull all the information out of a
Speaker 3: Salesforce org so that you could reproduce it, like maybe
Speaker 3: copy it to another org or something like that. Turns
Speaker 3: out that there is neglect within Salesforce the company to
Speaker 3: implementing the metadata API, so they have they have definitely
Speaker 3: a priority to get the low code interfaces out there first,
Speaker 3: so they actually recognize that they've gone to the point
Speaker 3: now where it's a real problem. And some of these
Speaker 3: DevOps companies. Another one I'll mention is Elements Cloud, and
Speaker 3: they're interesting because they have all kinds of proprietary ways
Speaker 3: to go into the Salesforce Org and get out that
Speaker 3: metadata that's not available through the API. So this kind
Speaker 3: of gets into a central theme that I have all
Speaker 3: the time when I'm talking about SaaS stevops and Salesforce DevOps,
Speaker 3: which is that the way these things work is that
Speaker 3: you kind of have to treat the subject's system, you know,
Speaker 3: like the Salesforce Org that you're updating or the org
Speaker 3: that you're reading or copying. You have to kind of
Speaker 3: treat that thing like a living system where there's there's
Speaker 3: no source of truth really other than the state of
Speaker 3: the thing that it's running in now. And that's really
Speaker 3: quite problematic because you have to, like in order to
Speaker 3: understand if you can produce a deployment that's going to work,
Speaker 3: you know it's not it's going to go through and
Speaker 3: not have any errors. Essentially have to like the only
Speaker 3: way to do that is the is to submitted to
Speaker 3: the org and see if any errors come out. So
Speaker 3: you can imagine how slow that would be on an
Speaker 3: iterative basis and how frustrating. And this actually gets back
Speaker 3: to a complaint that Salesforce developers in the community have
Speaker 3: about working with Salesforce, which is that it's very slow.
Speaker 3: It can and like as somebody who went from goot
Speaker 3: Go to apex, you know, Apex is the is the
Speaker 3: development language, this jab alike language they have for Salesforce.
Speaker 3: So like with Go, I could just you known't compile things,
Speaker 3: you know, hit you know, recompile or whatever, go and
Speaker 3: I'd have like ten seconds between a coding change and
Speaker 3: being able to see if it worked. With Salesforce, that
Speaker 3: can go out to maybe two or three minutes sometimes, right,
Speaker 3: So when you submit a package to either your Scratch
Speaker 3: org or even you know, a Sandbox org for testing,
Speaker 3: it's still going to take you know, like ninety seconds
Speaker 3: two minutes that for that submission to go in. So
Speaker 3: I think Salesforce developers are always complaining about this this
Speaker 3: flow of work thing, and the way that you can
Speaker 3: fix that as a vendor is to do kind of
Speaker 3: what Elements is doing, which is to create what I
Speaker 3: call a very complete digital twin of your subjects SaaS
Speaker 3: system within the DevOps product that you're working with. So
Speaker 3: Elements has a separate like AWS thing running where they
Speaker 3: essentially ingest all of the metadata from an org and
Speaker 3: convert it into like a graph database or some other
Speaker 3: kind of representation that they can then manipulate. And then
Speaker 3: they can use that to do something which is very
Speaker 3: essential in Salesforce, which is called impact analysis. So like
Speaker 3: if the boss says, oh, we got to have another
Speaker 3: you know, shipping type in the shipping module or whatever,
Speaker 3: then that thing needs to be defined in what they
Speaker 3: call a picklist in Salesforce. And when you change the
Speaker 3: picklist though, you could actually impact a whole bunch of
Speaker 3: different things, you know, different screens all over the place,
Speaker 3: apex code, user interface mechanisms, and other things like that.
Speaker 3: So by having a digital twin, you're able to easily
Speaker 3: pick do what I call impact analysis or change intelligence
Speaker 3: is another word they use for that. My favorite term
Speaker 3: is blast radius for sure. You know, like like when
Speaker 3: you when you make a change, what's the blast radius
Speaker 3: potential of that particular change? And so that's a that's
Speaker 3: a critical and that's just one thing, one example that
Speaker 3: you can't get out of salesforce and that you do.
Speaker 3: You need a DevOps service provider to help you delve
Speaker 3: into that and to help you organize that stuff.
Speaker 1: So let me pause you real quick right there and
Speaker 1: like reach out the problem here for our listeners. So
Speaker 1: with these large enterprise style SASS, I think you're describing
Speaker 1: two problems here. One is you never know what the
Speaker 1: true state is. So someone with the appropriate permissions could
Speaker 1: go in make a change to the environment and you
Speaker 1: don't have any way of tracking that change to see
Speaker 1: what was actually impacted, aside from asking that person, hey,
Speaker 1: would you do and getting their typical response nothing.
Speaker 3: And then the.
Speaker 1: Other one, the other aspect of this is if you
Speaker 1: want to introduce new features or capabilities to your system,
Speaker 1: you don't have any way to create like a staging
Speaker 1: area and test your changes before you apply to production.
Speaker 3: Correct. Correct. So those are those are both capabilities that
Speaker 3: DevOps products, salesforce and SaaS stevops products that you do.
Speaker 3: And the most popular salesforce s deevops product is from
Speaker 3: a company called gear Set. They're in England and the
Speaker 3: simulated deployment is the most popular feature of that product.
Speaker 3: So that's and it's also affordable, so like for two
Speaker 3: hundred and fifty bucks a year or whatever to get
Speaker 3: a seat for that thing. Yes, yeah, it's pretty cheap,
Speaker 3: and it'll save you a ton of time. Basically, it's
Speaker 3: that iteration.
Speaker 1: Yeah, at that price, it doesn't even need to save
Speaker 1: you more than a few minutes per year.
Speaker 3: Yeah, yeah. No. And and gear sets easy to buy too.
Speaker 3: That's another reason why they're popular. They kind of have
Speaker 3: a you know, a PLG product led growth concept where
Speaker 3: they just try to make it easy to use, easy
Speaker 3: to buy, you don't have to talk to a sales rep,
Speaker 3: where with most of the other products, is more like
Speaker 3: an enterprise sales Yeah, sales loop where you got to
Speaker 3: kind of delve into dealing with somebody and then coming
Speaker 3: up with a license agreement.
Speaker 2: Jillian, you were about to say something, Yeah, I.
Speaker 4: Was just wondering who is kind of the target audience
Speaker 4: for this, because on the one hand, we have salesforce,
Speaker 4: which is you know, like a sales tool, right, and
Speaker 4: then on the other hand, we're talking about DevOps and
Speaker 4: from the you know places that I've been at the
Speaker 4: sales and marketing team is not necessarily going to know
Speaker 4: where I want to have anything to do with any
Speaker 4: type of DevOps project. Right if they could be running
Speaker 4: things off of their laptop and accel or whatever, they
Speaker 4: probably would and would have nothing to do with somebody
Speaker 4: like me. So I'm just wondering, what are kind of
Speaker 4: the target audiences of these different tools.
Speaker 3: Well, that's changed over the years, so I think that's
Speaker 3: important to realize. So the Salesforce has evolved over the
Speaker 3: last let's say eight or nine years into an enterprise platform,
Speaker 3: so it's more like an application delivery platform than a
Speaker 3: pure CRM than it was in the past. And also,
Speaker 3: if there are several customers out there, salesforce customers out
Speaker 3: there who are spending in excess of one hundred million
Speaker 3: dollars a year on Salesforce and kind of the minimum
Speaker 3: for a fortune five hundred type company, the minimum expenditure
Speaker 3: is in the tens of millions. So because of that,
Speaker 3: a lot of the responsibility for maintaining Salesforce has moved
Speaker 3: off of the departments and into the office of the CIA.
Speaker 3: So I think that that's part of the explanation for
Speaker 3: why people care about DevOps is in Salesforce now, and
Speaker 3: it's been it may have been taken out of the
Speaker 3: hands of some of the departmental because that they want
Speaker 3: to increase efficiency. But I think, Jillian, you're right that everybody,
Speaker 3: you know, there are lots of people out there who
Speaker 3: could care less about DevOps and really want to use
Speaker 3: Salesforce kind of like what they've been telling you. How
Speaker 3: they've been telling you.
Speaker 4: For marketing tool, I thought it was like a more
Speaker 4: robust like HubSpot or something.
Speaker 2: Yeah, yeah, yeah, it's.
Speaker 4: A contractor thing and I have like Harvest and HubSpot
Speaker 4: for emails. I thought that it was a fancier version
Speaker 4: of that. And now I'm finding out that I was
Speaker 4: so wrong.
Speaker 3: Is well, you're not, of course, are not wrong, but
Speaker 3: I mean, there's just the they it's more like they
Speaker 3: want it to be bigger. And the other thing to
Speaker 3: appreciate about salesforces is that when they're in a big
Speaker 3: company selling, their number one goal is to have multiple clouds,
Speaker 3: as they call it. So they have their sales cloud,
Speaker 3: their marketing cloud out, their commerce cloud. Now, they have
Speaker 3: data cloud, now, they have you know, all these other
Speaker 3: things that are kind of all designed to work well.
Speaker 3: Actually they're not well designed to work together, dirty little
Speaker 3: secret out there, but and they're trying to make them
Speaker 3: all work together. They're actually rewriting.
Speaker 4: Somebody doing their best.
Speaker 3: They are, you know, I'm a critic of them, and
Speaker 3: I always like to, you know, have a little empathy
Speaker 3: in my criticism. But they're, yeah, they're they're trying. They're
Speaker 3: trying to do that. But I think they definitely want
Speaker 3: the attention on their product to be at the CIO level.
Speaker 3: And a lot of vendors now are in the salesforce
Speaker 3: ecosystem are kind of like turning their sales pitches in
Speaker 3: that direction. Where before the sales pitches need to be
Speaker 3: used to be more in a land and expand kind
Speaker 3: of philosophy, so that they would be pitching to the trailblazers,
Speaker 3: would be pitching to the sales managers, would be pitching to,
Speaker 3: you know, the people who are actually using these products more.
Speaker 3: But the pitch has definitely turned more to the CEO
Speaker 3: CIO level pitch and like. And also let's look for
Speaker 3: a minute at where DevOps is most prominent in salesforce,
Speaker 3: and it's it's almost always in a critical application. So
Speaker 3: there's a salesforce partner out there called Encino and Capital
Speaker 3: ci n O and they are a multi billion dollar
Speaker 3: valuation public company that that runs on top of Salesforce
Speaker 3: and what they do is banking, so there will do
Speaker 3: financial transactions and banking service. So you can imagine that
Speaker 3: the people who are running and Sino installations definitely want
Speaker 3: DevOps right because they they definitely want to be able
Speaker 3: to have a record of all the changes they made
Speaker 3: to their system. They have validation protocols, they have q
Speaker 3: A protocols and they and they have to sustain them.
Speaker 3: And there's actually a DevOps company that's pretty much devoted
Speaker 3: to that one sector and it's called auto Rabbit. It's
Speaker 3: a cute name, huh yeah. The their annual conference is
Speaker 3: called dev hops.
Speaker 2: Yeah, good job.
Speaker 3: Yeah. I like auto Rabbit. They have some Greek people
Speaker 3: there and and they they're very rigorous in terms of
Speaker 3: the security aspects. It often gets folded into salesforce DevOps too,
Speaker 3: like static security analysis and and other things like that.
Speaker 3: So yeah, I think the reason why there's been a
Speaker 3: transition from Salesforce being kind of this this SaaS platform
Speaker 3: that you just use to being something that has to
Speaker 3: have like a change management process associated with it is
Speaker 3: mainly the introduction of critical applications into it. There was
Speaker 3: another product used to be on Salesforce called Viva. Made
Speaker 3: a heard of them. They're a big, another giant software
Speaker 3: company who services pharmaceutical industry. So you know, like I
Speaker 3: used to work at Genetic, and it totally reminds me
Speaker 3: of what we're doing. Is kind of like the software
Speaker 3: QA and validation that we had to do for the FDA,
Speaker 3: you know, like a Genetic we had to like have
Speaker 3: a protocol for for how we like did all the
Speaker 3: rat lab way, you know, so that we could produce
Speaker 3: that protocol to the FDA and say this is how
Speaker 3: we weight all the rats, and and the similar thing
Speaker 3: happens with software too, right, So they that that's where
Speaker 3: this kind of culture came from, I think, and it's
Speaker 3: it's now been extended more into Salesforce.
Speaker 2: So what are the.
Speaker 1: Like In my experience, very few people who really need DevOps.
Speaker 2: Know that DevOps is the thing they need.
Speaker 1: So what does a conversation look like for you when
Speaker 1: you're talking to people that clues you in to say, oh,
Speaker 1: here's what you're missing, here's here's what this problem is
Speaker 1: describing to me.
Speaker 3: I think it's release management problems. That's that's the other
Speaker 3: essentially equivalent description for what the field is in Salesforce
Speaker 3: because like I mentioned before, the there is so many
Speaker 3: speed bumps and roadblocks to developers to to get the
Speaker 3: is going. So if you're what a lot of these
Speaker 3: products do is they offer you cic D pipeline automation
Speaker 3: as well, so they kind of give you a clicking
Speaker 3: interface to let you do pipelines. And again it's it's
Speaker 3: more compatible with the Salesforce trailblazer kind of profile to
Speaker 3: have that. So I think it's it's a common pain
Speaker 3: point in almost every Salesforce shop that does customization is
Speaker 3: is this. And they also know that the vendor ecosystem
Speaker 3: is out there to service them because if you're part
Speaker 3: of the whole Salesforce, you know Dreamforce World Tour thing,
Speaker 3: you know all all of their outbound communication and their
Speaker 3: partnership programs and everything. There are companies like Capato and
Speaker 3: gear Set and flows some and all these companies are upfront,
Speaker 3: you know in terms of their partnership, and Salesforce actually
Speaker 3: has investment relationships with some of these like Capato, and
Speaker 3: they does the Sales Force frequently recommends them to solve
Speaker 3: problems for big people. So I think people realize that
Speaker 3: the release management in Salesforce is still broken, still a
Speaker 3: lot of problems with it, and you probably need some
Speaker 3: vendor help to help you get through it.
Speaker 2: Yeah, I'm sure.
Speaker 1: Just thinking about it from a Salesforce perspective, you know
Speaker 1: how they started and where they got to. Now you're
Speaker 1: dealing with thirty years of legacy code and now you're like, oh, hey,
Speaker 1: let's do this new thing. I would imagine that that's
Speaker 1: not an easy implementation.
Speaker 3: No, it's not. It's uh. I think you get a
Speaker 3: lot of some of these tools are bought and not used. Yeah. Uh,
Speaker 3: that shelfware is a big problem in Salesforce ecosystem. The
Speaker 3: I think they people are are always looking for solutions
Speaker 3: to this kind of thing. And especially if you have
Speaker 3: that external pressure of like uh, you know, a QA
Speaker 3: officer or somebody like that in your organization, who's going
Speaker 3: to you know, be looking down your shoulder, or if
Speaker 3: you have external regulatory concerns or things like that. I
Speaker 3: think that that really is the dividing line. I think
Speaker 3: I think of all these companies, like I would say,
Speaker 3: there's about it's something like about a billion dollar market
Speaker 3: I think for all the software and services for stev ops,
Speaker 3: So that might be a little bigger than the people
Speaker 3: have thought. I think about a quarter of that is
Speaker 3: software and about three quarters of that would be services
Speaker 3: from people like you know Accenture or whoever. You know
Speaker 3: global system integrators who are consultant houses that frequently come
Speaker 3: in and and and do this kind of thing. So
Speaker 3: I think the other thing that I think we want
Speaker 3: to talk about today, and we can kind of switch
Speaker 3: subjects a little bit here is is like three years
Speaker 3: ago I wrote this blog post where I said predicted
Speaker 3: that SaaS deevops was going to be a thing. And
Speaker 3: I recently was talking to one of my old customers,
Speaker 3: Op Sarah, and and they have they're out there really
Speaker 3: trying to make this saastevops thing work. And here's the
Speaker 3: thing that they've noticed talking to customers now, is that
Speaker 3: at the CIO level, or maybe at the Center of
Speaker 3: excellence level, you do have a lot of people now
Speaker 3: thinking about how to manage every business platform in their company.
Speaker 3: So you have what is I've heard some crazy numbers
Speaker 3: like if you're a fortune five hundred, you have maybe
Speaker 3: up to one thousand different applications running in your organization,
Speaker 3: and maybe if you're a department, you might have fifty
Speaker 3: different online apps or SaaS apps that you could be
Speaker 3: using for this kind of thing. So I think the
Speaker 3: same kind of momentum that we saw in Salesforce, where
Speaker 3: they become it becomes more critical, it becomes more widespread,
Speaker 3: it becomes harder to manage, so that it kind of
Speaker 3: rolls up to the CIO level for concern. This is
Speaker 3: happening with other products as well. Obvious ones like s
Speaker 3: A P four Hanna or or you know, like oracle
Speaker 3: ERP or something like that is one of them, but
Speaker 3: even things like Jira or things like HubSpot or things
Speaker 3: like Zendesk is a big one. So people, there's an
Speaker 3: expression there's a thing out there now that I think
Speaker 3: kind of goes hand in hand with the platform engineering
Speaker 3: movement actually that CIOs want some sort of universal business
Speaker 3: platform system that they can use to do that. And
Speaker 3: I've seen various salesforce DevOps companies, just a handful of
Speaker 3: them have been successful. Two of them I want to salto.
Speaker 3: Another one is up Sarah to kind of do this,
Speaker 3: to have like a code user interface to do SaaS
Speaker 3: DevOps on different application products, But I kind of have
Speaker 3: a feeling that it managers are looking for the solution
Speaker 3: right now that they want to have a universal application
Speaker 3: to be a digital twin manager for all of their
Speaker 3: different SaaS products.
Speaker 2: Yeah.
Speaker 1: For sure, there's a big risk factor there as well,
Speaker 1: because we pretty rapidly ran to the SaaS world and
Speaker 1: now in hindsight, you can look back and say, oh, wait,
Speaker 1: all of our business critical data is not ours. It's
Speaker 1: sitting in a SaaS somewhere, and so how do number one,
Speaker 1: how do I manage the control and permissions in that?
Speaker 1: And also what's the blast radius when that SaaS provider
Speaker 1: gets hacked?
Speaker 3: Oh right, Yeah, I mean it's all as of security
Speaker 3: and safety considerations and data governance and and retention problems there.
Speaker 3: I think I think the a lot of people are
Speaker 3: kind of over the idea of the SaaS data being
Speaker 3: stored in somebody else's computer being not your data, you know.
Speaker 3: I think that most people have an export capability, and
Speaker 3: I think that the success as SaaS is kind of
Speaker 3: like an indicator that people are are are getting over that.
Speaker 3: But I think the they definitely want to have some
Speaker 3: way to consolidate DevOps sprawl in their organizations, because this
Speaker 3: is I think something you're seeing that goes along with
Speaker 3: these separate business systems. So if you're going to have
Speaker 3: a salesforce DevOps team, you're going to have an SAP
Speaker 3: DevOps team, You're going to have maybe a Jura DevOps team.
Speaker 3: So I think that if you're a CIO and you're
Speaker 3: trying to consolidate tool usage and trying to get people
Speaker 3: to work together better, I think that the looking at
Speaker 3: how you now have release management processes and critical infrastructure
Speaker 3: processes associated with these SaaS products, that that there's a
Speaker 3: SAS DevOps discipline that could be developed around this that
Speaker 3: that would consolidate and systematize your ability to manage all
Speaker 3: these things.
Speaker 1: Yeah, it almost strikes me as very similar to back
Speaker 1: in the nineties when you were doing desktop configuring, Like
Speaker 1: when you were building, like if you had a salesforce
Speaker 1: of two hundred people, you know, you only made it
Speaker 1: through the first two or three computers before you were
Speaker 1: looking for some way to automate it, and then that
Speaker 1: took you into the world of like modifying the Windows
Speaker 1: registry and and all of that kind of stuff.
Speaker 2: It feels very similar to that.
Speaker 3: Oh yeah, like in other words, taking a bunch of
Speaker 3: crazy configurations to trying to manage them under one roof Yeah. Yeah, yeah, that's.
Speaker 4: Were there biolinics.
Speaker 1: Well, I think that's where we all ended up. But
Speaker 1: now here we are facing the same problem again.
Speaker 4: No, I just I just remember, like you know, a
Speaker 4: certain team trying so hard to get all the bioformatics
Speaker 4: applications bundled with one distro of Linux, and I don't
Speaker 4: know they really tried. Okay, you guys they tried was
Speaker 4: Biolinus and that was that was my job to manage
Speaker 4: that for like a.
Speaker 3: Year, BioLinux.
Speaker 4: BioLinux. Yeah, it was. It was like a I think
Speaker 4: a distribution of Hubantu that just had a lot of
Speaker 4: bioformatic software pre installed. So it had like R and
Speaker 4: Blast and all like the mixed off all the top
Speaker 4: general mix software at the.
Speaker 3: Time you could, I don't know, sounds like a project.
Speaker 4: Very small gene. Oh my gosh, I don't.
Speaker 3: Know that that was. That was a while ago.
Speaker 4: I think that was that was a while ago.
Speaker 3: Yeah, yeah, yeah.
Speaker 4: You're talking about desktop management. That was my job for
Speaker 4: a little bit was to install BioLinux on all the
Speaker 4: new Scientist computers.
Speaker 1: So do you think companies like Salesforce have a roadmap
Speaker 1: of taking this problem in house and bundling it as
Speaker 1: part of Salesforce or you think they're going to rely
Speaker 1: on the external vendors and support them and solving it.
Speaker 3: I think the solid answer is the external vendors are
Speaker 3: the ones to to to rely on. I think because
Speaker 3: of generative AI. I think that there will be disruption
Speaker 3: though in DevOps right now. And I think maybe a
Speaker 3: year ago there was a rumor going around or it
Speaker 3: might have been just a hope from the Copato people
Speaker 3: that Salesforce might buy Capato, and after they bought own
Speaker 3: back up recently that for over a billion dollars that
Speaker 3: so that possibility came up again. But if I was
Speaker 3: you know, look, if I was an advisor for Salesforce
Speaker 3: on this, I would say maybe try to hold off
Speaker 3: on that because the uh just dovops is going to
Speaker 3: be highly disrupted by AI. I think, like like like,
Speaker 3: For example, I was telling you the story about the
Speaker 3: digital twin for example, So that's so if what that
Speaker 3: required to create was to ingest all of the metadata
Speaker 3: from a salesforce Org and then create a structure around
Speaker 3: it so that you could then use it traverse it
Speaker 3: in some way like a graph database for example. And
Speaker 3: you can actually achieve that same functionality now by simply
Speaker 3: ingesting all of the XML metadata and just putting it
Speaker 3: in a giant blob or rag or into an organized
Speaker 3: semantic database is the better way to do it. And
Speaker 3: then you can use an LLM to get the same results.
Speaker 3: So you can use an LLM to find a blast
Speaker 3: radius for a chain proposed change without creating a graph database.
Speaker 3: So that means a new entrant in Salesforce DevOps can
Speaker 3: possibly have the same kind of capability that that you know,
Speaker 3: elements Cloud and Penia and few of these others have
Speaker 3: to find the blast radius with almost.
Speaker 2: No coding all right on.
Speaker 3: Okay, So so this is just one example of the
Speaker 3: revolutionary capabilities of of a I when it when it
Speaker 3: comes to two DevOps. So I have a like there
Speaker 3: was a company in y combinators current batch called s
Speaker 3: r dot a I. There's an intriguing r L and
Speaker 3: they're doing Salesforce DevOps with the natural language. So you
Speaker 3: would be able to uh give it a command like
Speaker 3: take uh a deployment from sandbox A and deploy it
Speaker 3: to user testing sandbox B just with a command like that,
Speaker 3: just with natural language. And I think that this crowd
Speaker 3: is the listeners here kind of understand how potent that
Speaker 3: would be because that that that would invoke a whole
Speaker 3: pipe line process. And also what this company claims they
Speaker 3: can do is do repair errors that occur in the pipeline,
Speaker 3: so you know, self healing kind of capabilities with that,
Speaker 3: which is the thing that AI seems to be really
Speaker 3: great at in terms of root cause analysis for errors.
Speaker 3: So I think to answer your question, I think that
Speaker 3: they may have been thinking about acquiring Capato or one
Speaker 3: of the other ones maybe a year ago, because it
Speaker 3: is an obvious thing and they're kind of moving out
Speaker 3: of this no acquisitions phase that they were in. But
Speaker 3: I think right now the field is up for grabs.
Speaker 2: Yeah, for sure, now I see that because.
Speaker 1: In the model you just described, like the the capabilities
Speaker 1: of using an LLLM to do that would just dwarf
Speaker 1: the capabilities of any team trying to do it by
Speaker 1: forcing people to follow procedures and policies.
Speaker 3: Yeah. Yeah, And I think also it's just the code
Speaker 3: generation aspect of of AI as well that I think
Speaker 3: that's considered to be part of Salesforce DevOps. Now, Salesforce
Speaker 3: has an agent let's or I should call it a
Speaker 3: copilot works kind of like it a co pilot. Even
Speaker 3: though market's copilots, they still got some they uh yeah,
Speaker 3: they still have the capability to generate code and and
Speaker 3: that kind of thing. But and that's part of DevOps.
Speaker 3: But I don't think that that they're going to be
Speaker 3: supporting it very much, honestly. And I try to get
Speaker 3: into that because like this the publisher of Salesforce DevOps
Speaker 3: dot net, it's kind of like my job to figure
Speaker 3: out for the community, you know, where the solutions are
Speaker 3: going to come from. And you know, like they have
Speaker 3: a product called Salesforce DevOps Center, and it's kind of terrible.
Speaker 3: It just it hasn't been updated. There's the they have
Speaker 3: a very sluggish pipeline of features that they're that they're
Speaker 3: putting in. If you're aware of how Salesforce operates internally politically,
Speaker 3: you kind of realize that this is a kind of
Speaker 3: like a group that's that's sitting in a non revenue
Speaker 3: position within Salesforce, so that they have no product that
Speaker 3: you could put a revenue number on. So if you
Speaker 3: don't have that in Salesforce, you're at a disadvantage.
Speaker 2: To making money.
Speaker 3: Yeah. Yeah, And I think that this like one thing
Speaker 3: I like to compare Salesforce and Microsoft in the in
Speaker 3: this respect. I think Microsoft for me as a developer,
Speaker 3: as as somebody who uses tools and was looking for
Speaker 3: things to put together all the time, Microsoft does it right,
Speaker 3: you know what They basically they're going to create an API,
Speaker 3: create an interface, and they're going to service the developers first.
Speaker 3: They're going to make sure that developers have all the
Speaker 3: tools in order to create these applications, and Salesforce does
Speaker 3: it kind of backwards. They're going to make sure that
Speaker 3: the trailblazers have all the tools to do the CLICKI
Speaker 3: thing first, but then then the the DevOps capabilities or
Speaker 3: the apex coders or even a flow coder capability is
Speaker 3: added later. You know, they got to get this functionality
Speaker 3: out the door that people can buy. And it's it's
Speaker 3: that mentality that you know, it's just kind of like
Speaker 3: a gigantic difference in the founders between Bill Gates and
Speaker 3: Mark Benioff. You know that you have, you know somebody
Speaker 3: who wants to create a tools that developers can use,
Speaker 3: and that's not the mentality at Salesforce. So the DevOps
Speaker 3: industry is basically compensating for that.
Speaker 2: Yeah, for sure. And that's been the.
Speaker 1: Pattern I've seen a lot in my career in startups.
Speaker 1: You you know, you have two types of startups from
Speaker 1: that perspective. You have the ones who are just like
Speaker 1: ship it, or the ones who think about the long term,
Speaker 1: you know, how do we support this, how do we
Speaker 1: configure out, how do we maintain it? And are they're
Speaker 1: a little more deliberate in there the delivery. But I
Speaker 1: tend to lean towards the former with just ship it,
Speaker 1: because odds are from a startup perspective, odds are your
Speaker 1: product's going to fail, So you want to fail as
Speaker 1: quickly as possible. And in the off chance that it
Speaker 1: doesn't fail, well, now you've got money, and with money
Speaker 1: you can pretty much solve all the bad decisions you
Speaker 1: made early on.
Speaker 3: Well, yeah, that's I tend to agree. I mean, I
Speaker 3: think my inclination as a developer is to kind of
Speaker 3: go down the wrong road here, which is to make it,
Speaker 3: make it perfect. Yeah, you know, I think I kind
Speaker 3: of have that O C D A D d uh
Speaker 3: uh thing that a lot of developers have, which is,
Speaker 3: you know, oh but if I just do that, get
Speaker 3: this one thing, get the speed going, you know, cut
Speaker 3: out this one thing, it'll it'll be perfect and everybody
Speaker 3: will buy it. And then the problem is you always
Speaker 3: find some other thing to fix, for sure. Yeah, after
Speaker 3: that you get into an now, yeah, always new problems.
Speaker 3: And I think you're right. Is you got to ship
Speaker 3: the thing. You got to You gotta get customers, You
Speaker 3: got to have your m VP out there. You gotta uh,
Speaker 3: you know, talk to people. And yeah, you can fix
Speaker 3: bad design design decisions.
Speaker 2: Later, for sure. So what is the what is the
Speaker 2: this changing landscape look for you? Where if we use the.
Speaker 1: Wayne Gretzky analogy of go, where the puck's gonna be?
Speaker 1: Where are you lining up for this?
Speaker 3: Oh well, I'm uh, I'm interested in cognitive DevOps. Now
Speaker 3: that's kind of the thing.
Speaker 2: I hadn't heard that term before that.
Speaker 3: Yeah, that's my term, cognitive DevOps.
Speaker 2: I like it.
Speaker 3: Uh, I like to I call it. That's what sr
Speaker 3: e dot Ai is doing, is cognitive DevOps. I think
Speaker 3: that we're gonna the other thing that's happening for sure,
Speaker 3: and I talked to all these companies. I talked to
Speaker 3: Salesforce is this agent concept is. I think it's a
Speaker 3: little more real than any other part of the generative
Speaker 3: AI revolution that we're now in the third year of.
Speaker 3: I guess the reason why is because there's some serious
Speaker 3: programming and development behind these things. It's not just the lllms.
Speaker 3: It's you've got multi stage lms. You've got a you know,
Speaker 3: an LM that does the planning, then you've got other
Speaker 3: lms that do the actions for example, and then you've
Speaker 3: got other ways to kind of conceive of this. And
Speaker 3: I think the most interesting way to conceive of this
Speaker 3: is what I call the virtual employee paradigm, and that
Speaker 3: I think that this is where it's going to go.
Speaker 3: I think that you're going to have the agents and
Speaker 3: this is going to happen in DevOps too, so so
Speaker 3: you're going to have be able to hire a virtual
Speaker 3: employee that functions like your Salesforce ADMIN. That you're going
Speaker 3: to be able to communicate with the VE like a
Speaker 3: business person, you know, like you are able to express
Speaker 3: your business needs to this your Salesforce admin VE. And
Speaker 3: then that Salesforce admin ve will actually use RPA or
Speaker 3: whatever it needs to do to actually operate the software
Speaker 3: to implement those changes and to manage manage it for you.
Speaker 3: So I believe that most of the DevOps companies have
Speaker 3: a project working on this right now.
Speaker 2: Yeah.
Speaker 1: I can see that being very realistic because when you
Speaker 1: think about the common hands on tasks that happen in develops,
Speaker 1: it's you know, create a Kubernetes pod with these images
Speaker 1: and configure a database and add that database connection stream
Speaker 1: to this parameter, which are all things that are very
Speaker 1: much within the capabilities of an agent like that, right.
Speaker 3: Yeah, it's it's exactly, it's essentially. I think the the
Speaker 3: way these ves are going to go is they're going
Speaker 3: to replace entry level employees first. So that's just the
Speaker 3: kind of thing you would give to your DevOps trainee,
Speaker 3: right right, and that uh so, so they're going to
Speaker 3: be a joy and a boon to senior people like us,
Speaker 3: you know that to know how to use all these
Speaker 3: know what needs to be done, and can just give
Speaker 3: out the instructions like you're like you're talking to a
Speaker 3: junior person on your team. And that, by the way,
Speaker 3: gets into the public policy aspect of of this AI businesses,
Speaker 3: you know, what's going to happen to all the entry
Speaker 3: level chops for sure, what's gonna happen to all all
Speaker 3: that kind of stuff. So, you know, I don't want
Speaker 3: to be just blight lead talking about virtual employees without
Speaker 3: mentioning that you know, there's obviously a public policy and
Speaker 3: human impact to this, and I think it's if you're
Speaker 3: a young DevOps person right now, it's you know, I
Speaker 3: have no other have nothing to say other than I'm
Speaker 3: kind of worried about that because I think that you
Speaker 3: look at this ve thing and something that you can
Speaker 3: associate with that is what I call VEE economics. And essentially,
Speaker 3: if you can hire let's say you needed twenty of
Speaker 3: these DevOps junior people in your giant company, well you're
Speaker 3: going to start experiencing some economies of scale that you
Speaker 3: won't experience with people. Right So on the twentieth one
Speaker 3: of this, you're going to get a big discount from
Speaker 3: whatever service provider that you're getting this from. So there's
Speaker 3: kind of like new economic laws that are that are
Speaker 3: that are happening here, and one of them is you
Speaker 3: know the law of infinite scale. The basically, you know
Speaker 3: you take away the profit margin, and you know, you
Speaker 3: get a service provider like Salesforce and they'll be happy
Speaker 3: to provide you all of these agents or virtual employees
Speaker 3: at a at a discount. So now you've got the
Speaker 3: prospect of being able to grow your head count without
Speaker 3: a linear increase in expenses. So this basic property of
Speaker 3: vee economics, I think is what's going to drive uh
Speaker 3: this forward, is that this is something that CEOs get
Speaker 3: immediately right and that you like, they're there. What is
Speaker 3: what does the CEO do? They manage their workforces, they
Speaker 3: manage resources, they they they take inputs and outputs, They
Speaker 3: think in terms of profit and laws. The they are
Speaker 3: extremely interested in this. Like I've talked to the Agent
Speaker 3: Force rollout from Salesforce in September was definitely changed the
Speaker 3: landscape in terms of their sales. Right now that I've
Speaker 3: been talking to system integrators and consultants and they're getting
Speaker 3: calls from their CIOs basically because their CEOs are saying, hey,
Speaker 3: you know, I saw what Mark's talking about. I get
Speaker 3: this ve economics thing. Get me some of these virtual
Speaker 3: employees as quick as possible. And so it's we're seeing
Speaker 3: a different shape of demand right now, And I was
Speaker 3: talking to another one of these cognitive DevOps companies and
Speaker 3: they're actually going in there making the sale based on
Speaker 3: what their customer is paying a salesforce admin. So this
Speaker 3: to me is kind of revolutionary because it implements what
Speaker 3: people are calling the service as a software model. And
Speaker 3: what that means for the software industry is that not
Speaker 3: only are you able to, let's say, get budget out
Speaker 3: of an existing IT budget, but now you're able to
Speaker 3: get budget out of an existing human resources budget.
Speaker 1: Yeah, for sure, that's crazy, and that just yeah, that
Speaker 1: gives you you know, you refer to it and sales
Speaker 1: a lot it. You know, it gives you stickiness because
Speaker 1: now you can bring multiple decision makers in and create
Speaker 1: compelling arguments for each of those.
Speaker 3: Yeah. Yeah, it's it is wild, I think. So, you know,
Speaker 3: where am I looking for things to go? I think
Speaker 3: I'm sticking with the DevOps thing. The cognitive DevOps, I
Speaker 3: think is going to be a huge disruptor. I think
Speaker 3: that they're going to slowly get into this area, and
Speaker 3: I think that we're going to have pretty soon you're
Speaker 3: going to have virtual employees. Let's say within two years.
Speaker 3: I'd say, who would be able to manage or release
Speaker 3: management process all completely on their own, so that that
Speaker 3: would be tremendous in terms of automation and time savings
Speaker 3: for the salesforce admins that are left to do that.
Speaker 4: Yeah, that is crazy disruptive when you think about kind
Speaker 4: of all the industries that could be applied for, Like
Speaker 4: it wasn't too long ago that we had you know,
Speaker 4: secon ferries and things to help with scheduling, and now
Speaker 4: we have virtual calendars that can do all that. And
Speaker 4: I think AI is on just a completely different scale
Speaker 4: than even these kind of revolutionary technologies that we've already seen,
Speaker 4: like virtual calendars and a word processor, you know, like
Speaker 4: being a word processor used to be people's jobs as well.
Speaker 4: For sure, I don't know, it's got to be scared
Speaker 4: to be a young person in like who's coming into
Speaker 4: the industry now or you know, or thinking about coming in.
Speaker 4: Sure it's scary for everybody else too, but I would
Speaker 4: be especially scared as the young people because of what
Speaker 4: you said about the entry level jobs like just being
Speaker 4: obliterated by AI.
Speaker 3: Yeah, I'm really concerned about that. You know, as a
Speaker 3: policy prognosticator, I definitely see a problem there. I also like,
Speaker 3: I see this ve economics is like a giant sucking sound,
Speaker 3: you know out there that CEOs are locked in. I
Speaker 3: think it only took him a few months to get
Speaker 3: locked in on this, on this thing. And like here
Speaker 3: in Silicon Valley, I couldn't think of a single young
Speaker 3: entrepreneur who isn't thinking about dream who was in dreaming
Speaker 3: about building their company this way as well. So and
Speaker 3: I think that they're getting tremendous encouragement from the venture capitalists. Also,
Speaker 3: this vee economics story, if you bring it to the table,
Speaker 3: if as a startup entrepreneur and you're and you are
Speaker 3: able to latch onto that, I think that that is
Speaker 3: a story that just instantly sells with investors as well.
Speaker 3: So I think we're about basically. Another thing I like
Speaker 3: to say is we have not reached the peak of
Speaker 3: expectations of generative AI. You know, there was a talk
Speaker 3: that maybe we had hit that trough of disillusionment for
Speaker 3: some referring to the Gartner HiPE cycle graph here and
Speaker 3: the people thought we'd hit the trophic disillusionment with the
Speaker 3: enterprise AI this past summer. And would I never felt
Speaker 3: that way because of the conviction that I have on
Speaker 3: the subject, which like, here's a simple reason why I
Speaker 3: have conviction. And I'm sure you've heard this example before.
Speaker 3: But let's say you've got a pile of ten legal
Speaker 3: briefs and you need a lawyer to kind of examine
Speaker 3: those in the context of a case you're working on.
Speaker 3: That would have taken you know, the cheapest lawyer you
Speaker 3: could have hired and the Philippines or whatever for like,
Speaker 3: you know, seventy five bucks an hour to do something
Speaker 3: like that. That would have cost you, you know, three
Speaker 3: or four hundred dollars, And now that costs you three
Speaker 3: or four cents to do the same thing. And that's
Speaker 3: actually a reliable application that I'm referring to here, and
Speaker 3: where the hallucinations are not that much of a problem
Speaker 3: and you can do things to manage it. So when
Speaker 3: you've got anything, it's like a three or for order
Speaker 3: of magnitude change in economics. To me, that's like an
Speaker 3: inevitable force. It's similar to like the distribution of paper catalogs.
Speaker 3: What happened to that in the nineties because it was
Speaker 3: literally a thousand times cheaper to send that stuff around
Speaker 3: the world as a PDF. Then you know, over the internet,
Speaker 3: then you actually print and distribute it. So I think
Speaker 3: this is why I have conviction on AI is that
Speaker 3: kind of basic cognitive change. And that's actually one of
Speaker 3: the second economic laws I've kind of been working on,
Speaker 3: which is, you know, this the ability to have cognitive
Speaker 3: scale that you can do things with AI that was
Speaker 3: previously not possible or was so expensive you couldn't do
Speaker 3: it all the time, that you can now do it
Speaker 3: with AI. So that's those that's where I think it's going,
Speaker 3: and it's I think it's it's generally good because I mean,
Speaker 3: like the abundance side of this equation of this of
Speaker 3: this idea is that if we make it easier to
Speaker 3: make to build software, more software will get built. Right two.
Speaker 3: So that's another thing. I mean, there's there's the market
Speaker 3: Andresen quote where he says software will eat the world. Well,
Speaker 3: according to Gartner, they're only about thirty or forty percent
Speaker 3: done really, so like if you look at the cloud migration,
Speaker 3: the we've still got more than half of corporate data
Speaker 3: is still on prem So I think it's you know,
Speaker 3: there's a long way to go with the stuff. And
Speaker 3: I'm pretty sure that cognitive DevOps is probably going to
Speaker 3: be one of those things that kind of like seeps
Speaker 3: into the background and we take for granted three or
Speaker 3: four years from there for sure.
Speaker 1: And I do want to, like, for all the young
Speaker 1: listeners listening to the show who are still early in
Speaker 1: their career, I want to give them some hope and
Speaker 1: not send them away from the episode going, well.
Speaker 2: Dan, that was a buzzkill.
Speaker 1: So, you know, we've seen this in the past, not
Speaker 1: exactly like this, but we have seen you know, like
Speaker 1: Jillian was mentioned, there used to be a career called
Speaker 1: word process or like you were mentioning Vernon, you know,
Speaker 1: you used to have people who ran the printing presses
Speaker 1: for printing paper catalogs.
Speaker 2: And we saw the outsourcing movements.
Speaker 1: I was a kid, yeah, and we had the outsourcing
Speaker 1: movement of the nineties and early two thousands of outsourcing
Speaker 1: the tech jobs in the US to other countries. So
Speaker 1: there's there's patterns. There's historical patterns you can look at
Speaker 1: if you're still early in your career and see what happened.
Speaker 2: Where did those.
Speaker 1: People who were displaced, where did they go? And then
Speaker 1: see if there's some parallels here in this type of movement.
Speaker 1: And you know, back to the Wayne Gretzky quote, start
Speaker 1: steering your career in that direction.
Speaker 3: Yeah, I think you got to look at the you
Speaker 3: got to move up the application stack. Essentially, you have to.
Speaker 3: I think the thing that folks like us are gifted
Speaker 3: at is to be able to understand capabilities and marry
Speaker 3: them to problems. Right, So you need to be I
Speaker 3: think we're going to have fewer people in it is
Speaker 3: definitely a thing, but I think that we're going to
Speaker 3: be doing more good work, and we're going to be
Speaker 3: doing more work that's actually tied to whatever the enterprise
Speaker 3: that you're working for does, because it's a I mean,
Speaker 3: we're all familiar with the Phoenix project, right. It's amazing
Speaker 3: how many dysfunctional IT organizations there are out there. You know,
Speaker 3: we have people who have no idea why they're doing something.
Speaker 3: You know, they have no idea that you know, like
Speaker 3: working on this weird salesforce problem is somehow going to
Speaker 3: help the company like they can't translate that into that.
Speaker 3: And I think what's got to happen in our profession
Speaker 3: is we have to become more aligned with business. For sure,
Speaker 3: it was and so I think that if we're able
Speaker 3: to use tools like AI and cognitive DevOps to remove
Speaker 3: us from some of the daily grind of this and
Speaker 3: some of the drudgery that goes along with it. Then
Speaker 3: I think we're making progress and we have the ability
Speaker 3: to expand out talent so that talent, young talent can
Speaker 3: can use their imagination and there are new ways of
Speaker 3: thinking and other gifts of youth to you know, participate
Speaker 3: in the economy more in terms of constructing solutions and
Speaker 3: working more where the rubber meets the road in a
Speaker 3: particular organization. I think we're just like, you know, don't
Speaker 3: have elevator operators, don't have buggy whip makers. You know,
Speaker 3: we might not have more DevOps engineers in the future.
Speaker 3: We might have few of those because of automation. But
Speaker 3: I think the people if you're looking to marry your
Speaker 3: love of technology, your ability to see solutions, your imagination
Speaker 3: to pull things together, I think that there's a lot
Speaker 3: of business people who would love to hear from you.
Speaker 1: For sure, there's always going to be problems that don't
Speaker 1: have solutions, and one way to look at this is
Speaker 1: you can shift your daily grind from solving the problem
Speaker 1: of why doesn't this doc or container build to a
Speaker 1: higher level problem of something that the customers of the
Speaker 1: company you're working for are going to value.
Speaker 4: Yeah, I always try to give that advice to, you know,
Speaker 4: whenever I'm working with students, are talking to young people,
Speaker 4: the very wary of putting yourself in a position where
Speaker 4: you don't know why you're doing what you're doing. Always
Speaker 4: try to, you know, kind of move up the ladder
Speaker 4: to the decision makers, talk to the people who are
Speaker 4: actually using the product you're creating, if that's what you're doing,
Speaker 4: or that kind of you know, the equivalent and sort
Speaker 4: of whatever job it is, do you have because if
Speaker 4: you can, if you can keep identifying problems, you can
Speaker 4: keep having a job. For the most part, is at
Speaker 4: least what I've found. And obviously you know that's not
Speaker 4: always a perfect strategy, but I think it's much better
Speaker 4: than kind of sitting in your corner and saying I'm
Speaker 4: going to be the best Python or Go developer of
Speaker 4: all time, right, Like that's that's maybe not the best goal.
Speaker 4: It should be instead, want to solve this problem, and
Speaker 4: then there are always new problems, you guys. Always they
Speaker 4: never end, like they just they never they never stop.
Speaker 4: So no uplifting advice. There's always new problems, always, right.
Speaker 3: And I think also it took a lot of resources
Speaker 3: and a lot of capabilities to solve some of these
Speaker 3: problems with it in the in the past, and now
Speaker 3: you could do it with less. So I agree. I
Speaker 3: think that there are more problems to be solved always,
Speaker 3: and I think that we're going to have a different
Speaker 3: kind of flatter world when it comes to doing this.
Speaker 3: I think there's going to be suer middle managers, fewer
Speaker 3: people trying to function as gatekeepers because we're going to have,
Speaker 3: you know, assistance to help us with some of the stuff,
Speaker 3: for sure. So that's where I think it's going. If
Speaker 3: you want to aim your puck in the right direction,
Speaker 3: I think it's it's for that.
Speaker 2: Awesome What do you think should we move on to picks.
Speaker 3: Us?
Speaker 4: So I'm going to go with the shameless self promotion
Speaker 4: this week. I am opening up I don't know, maybe
Speaker 4: five to ten spots for and actually an AI product
Speaker 4: that I have now that we've you know, had this
Speaker 4: nice end of the show on how AI is going
Speaker 4: to take all the jobs and things. Let me take
Speaker 4: some jobs away from your company. No, I'm just kidding.
Speaker 4: It's cool. Stuff to empower your scientists to do different tasks.
Speaker 4: The most frequent, one frequent one that I see is
Speaker 4: to be able to do literature text mining and throw
Speaker 4: you know, thousands of papers at it and then to
Speaker 4: be able to get some type of information. I work
Speaker 4: in drug discovery, so it's it's mainly drug discovery. I
Speaker 4: do have an article on that. It's called using LLMS
Speaker 4: to query PubMed knowledge bases for Biomedical research and kind
Speaker 4: of like what it says, you can query a PubMed
Speaker 4: you can throw all of your papers at THEAI, and
Speaker 4: then you can tell the AI you don't please summarize
Speaker 4: this for me. So it's a product that I have
Speaker 4: that gives you a chat GPT like interface that your
Speaker 4: scientists can use. But it's all self hosted on AWS,
Speaker 4: so none of your data gets out if you have
Speaker 4: proprietary data, if you have you know, pre clinical data,
Speaker 4: all that kind of stuff, or other data science companies
Speaker 4: that I don't know what you all are doing, but
Speaker 4: it might be useful for you too, I don't know.
Speaker 4: So anyways, it's got the chat GPT like interface, and
Speaker 4: then it's also got a programmatic interface that you can
Speaker 4: use wherever you have a terminal stage maker HPC wherever
Speaker 4: all the things are. That'll be on my website dabblodepops
Speaker 4: dot com, slash ai if anybody is interested in that
Speaker 4: and would.
Speaker 2: Like to try it out right on awesome vernon. What'd
Speaker 2: you bring for a pick?
Speaker 3: Well, I got my website so dot net and invite
Speaker 3: everybody to come by there. Like I said, I'm I'm
Speaker 3: also on LinkedIn vernon keenan all together is my is
Speaker 3: my thing on LinkedIn, and I would just my pick
Speaker 3: is I want people who are complaining about Salesforce ops
Speaker 3: or have complaining about the pricing models and things like
Speaker 3: that to contact me because I'm trying to gather.
Speaker 2: Input right on.
Speaker 4: It's not like a support group that could be, that
Speaker 4: could be.
Speaker 3: It is it is, you.
Speaker 4: Know, It's just we're gonna get all these people and
Speaker 4: we're all going to have like snacks and fuzzy blankeys and.
Speaker 3: Just it is. That's what I'm trying to create, is
Speaker 3: just a comfort group where we can all complain and
Speaker 3: and give each other let us know that Salesforce is
Speaker 3: not paying attention to us and this thing. So here's
Speaker 3: but it'll start out with a fine counseling session with
Speaker 3: me to get all your complaints. Yes, yes, yes, yes, yes,
Speaker 3: So trying to you know, be the trailblazer whisperer here.
Speaker 3: So the more trailblazers who contact me to tell me
Speaker 3: about their problems with data cloud and agent Force, the better.
Speaker 3: Right on?
Speaker 2: Awesome?
Speaker 1: All right, my pick this might be one of the
Speaker 1: wildest things I've ever picked. But with the holiday season
Speaker 1: coming up, if you're looking for a gift for someone.
Speaker 2: And they are a male, I'm going to suggest Shine
Speaker 2: sty underwear, which.
Speaker 1: All right, it's hard to get excited about underwear, and
Speaker 1: I was pretty skeptical at first, but I used these.
Speaker 1: I ended up with some and used them extensively a
Speaker 1: year or so ago when I was training to run
Speaker 1: a one hundred k Ultra marathon.
Speaker 2: So the ones I had, I was to say, that
Speaker 2: is crazy.
Speaker 4: Okay, anyways, carry on, carry on.
Speaker 1: So I'm just gonna say my shine Steeds are battle
Speaker 1: tested and they have performed well. So yeah, that's my pick,
Speaker 1: and that's probably the one that's gonna get me kicked
Speaker 1: off of this podcast. But you'll have a pair of
Speaker 1: Shinty to take it.
Speaker 3: Shinesty's uh boxers or briefs.
Speaker 1: I like the I like the long leg briefs.
Speaker 2: Just the the support factor. Mm hmm.
Speaker 3: Okay, we're going into the chafing aspect of Yeah, of
Speaker 3: the podcast. Absolutely, he will and Jillian, this is fantastic.
Speaker 2: I really appreciate have you on the show. This was great.
Speaker 1: Thank you so much for for joining us. And uh,
Speaker 1: feel free to to come back and chat with us
Speaker 1: again at any time.
Speaker 3: We can.
Speaker 2: We can do this later and see how our predictions went.
Speaker 3: Yes, yes, yes, we'll see how my little mission to
Speaker 3: h fixed agent force pricing goes.
Speaker 2: Right on.
Speaker 3: That's my current missioncause nobody knows how much.
Speaker 1: It costs right on, looking forward to good that's a
Speaker 1: big problem.
Speaker 2: Okay, great yep. To the listeners, thank you guys all
Speaker 2: for listening.
Speaker 1: Appreciate having you support the show, and we'll see you
Speaker 1: all next week.