AI Agents for SEO: Are They Replacing SEO Workflows?

AI Agents Are Replacing SEO Workflows Not SEOs explores how AI agents for SEO are transforming traditional workflows into autonomous and execution driven systems.

In this podcast, we break down how SEO automation powered by AI agents can analyze data, prioritize opportunities, and take action across content, technical SEO, and search strategy.

Whether you are a marketer, founder, or SEO professional, you will learn how to scale performance and adapt to AI driven search.

👉 Read the full guide: https://riseopp.com/blog/ai-agents-for-seo-the-ultimate-guide-to-seo-automation-and-growth

Transcript

SPEAKER_00 0:00

Imagine waking up tomorrow and uh you find out that two-thirds of your website traffic just vanished overnight.

SPEAKER_01 0:07

Yeah. That's a terrifying thought for anyone.

SPEAKER_00 0:09

Right. And not because your server's crashed or, you know, your site is broken, but simply because an artificial intelligence answered your customer's question before they ever had a reason to click your link.

SPEAKER_01 0:20

Exactly. And the crazy thing is that isn't some dystopian hypothetical for five years down the road.

SPEAKER_00 0:26

Aaron Powell No, it's really not. That is happening right now. And uh for the last couple years, the way we've been talking about AI and the marketing world has been surprisingly, I don't know, one-dimensional.

SPEAKER_01 0:38

Very much so. Yeah.

SPEAKER_00 0:39

We've largely treated it like this really, really fancy typewriter. You type a prompt into a box, it spits out a blog post, and we all sit around a table debating whether it sounds too robotic.

SPEAKER_01 0:48

Right. The whole is this AI or human debate.

SPEAKER_00 0:51

Exactly.

SPEAKER_01 0:52

Yeah.

SPEAKER_00 0:52

But today, we're completely ripping up that playbook. For this deep dive, we are shifting from thinking of AI as a passive prompt box to understanding it as a well, a junior operator. Yeah. Like a system that can independently run complex marketing workflows.

SPEAKER_01 1:08

Aaron Powell It really is a massive structural shift in how work gets done. I mean, we're transitioning from tools that just suggest things to systems that actually execute things completely autonomously.

SPEAKER_00 1:19

Aaron Powell And to guide you through exactly how this works, we've pulled together a really phenomenal stack of sources today. We are looking closely at the architect's guide to AI, SEO agents, and automation.

SPEAKER_01 1:31

This is a great breakdown, by the way.

SPEAKER_00 1:33

It's fantastic. And we are cross-referencing that guide with some incredibly heavy-hitting data. We've got global survey data from McKinsey. We're looking at the 2025 Gartner hype cycle. And we have a deeply fascinating research gate study on how AI is fundamentally rewiring human search behavior. Trevor Burrus, Jr.

SPEAKER_01 1:52

The behavioral shift is probably the most urgent part of all this.

SPEAKER_00 1:55

Oh, absolutely. So, okay, let's unpack this. If traditional search engine optimization tools were like a dashboard warning light telling you your car's engine is running hot, an AI agent is a mechanic that actually pulls the car over, diagnoses the radiator, orders the placement part, and then installs it while you're just sitting there looking at your phone.

SPEAKER_01 2:13

That analogy absolutely hits the nail on the head. Because the reality for anyone managing digital visibility right now is that the daily work has become incredibly uh operationally heavy. Yep. The search engine results pages, what we call the SERPs, they are shifting at a terrifying speed. And marketing teams are managing massive, sprawling content inventories.

SPEAKER_00 2:36

And dealing with like constantly rising technical complexity, too.

SPEAKER_01 2:39

Exactly. Plus, they are facing immense pressure to do much more with significantly fewer resources. I mean, static tools that just hand you an Excel spreadsheet of site errors once a quarter. They simply aren't cutting it anymore.

SPEAKER_00 2:51

Because knowing what is broken isn't really the bottleneck anymore, is it? It's having the hands-on keyboards to actually fix it.

SPEAKER_01 2:57

Spot on. The industry does not suffer from a lack of recommendations. We have endless bash boards telling us what's wrong. What the industry suffers from is a lack of reliable execution at scale.

SPEAKER_00 3:07

Aaron Powell Which is the exact gap these AI agents are designed to fill.

SPEAKER_01 3:11

Right. And I want to be clear here, this isn't about replacing human experts. It's about closing that massive gap between knowing your site has, say, a thousand decaying pages and actually having the operational throughput, the sheer labor hours, to go in and update them.

SPEAKER_00 3:26

Aaron Powell It's about taking the expert strategy you already possess and executing it at a scale that was previously physically impossible.

SPEAKER_01 3:34

Exactly.

SPEAKER_00 3:35

But to really wrap our heads around how these tools change the game, we first have to understand why they aren't just glorified chatbots. Because uh I have a real problem with the way this tech is being sold right now.

SPEAKER_01 3:46

Oh, I know exactly where you're going with this.

SPEAKER_00 3:48

Right. Let's be honest. Every vendor on the planet is slapping the word agent on their software right now. If I log into a tool, type give me 10 keywords, and it spits out 10 keywords, the marketing material calls it an AI agent.

SPEAKER_01 4:00

Yeah, the buzzword fatigue is real.

SPEAKER_00 4:02

So how do we separate a true functional agent from just a smart prompt box?

SPEAKER_01 4:07

Well, what's fascinating here is that the defining line between a chatbot and a true agent comes down to autonomy and architecture. The source material breaks down a true AI agent into five core components.

SPEAKER_00 4:19

Okay, lay them out for me.

SPEAKER_01 4:21

Yeah. So if the software you're using doesn't possess these five things, you are just looking at a smart assistant. The first component is perception. The system has to be able to read inputs entirely on its own.

SPEAKER_00 4:33

Aaron Powell Wait, what does read inputs on its own mean in practice? Like it's scanning my site.

SPEAKER_01 4:38

It's actively pulling data without you asking. It's hooking into your ranking data via APIs, it's monitoring crawl logs, it's parsing competitor pages, it's looking at your analytics. Wow. It perceives the environment continuously. It is not sitting idle waiting for you to paste a paragraph of text into a chat window.

SPEAKER_00 4:56

Aaron Powell So it's actively looking at the board, so to speak.

SPEAKER_01 4:58

Exactly. Then we move to the second component, which is reasoning. It has to interpret all those inputs it just perceived.

SPEAKER_00 5:04

Like figuring out what it all means.

SPEAKER_01 5:05

Right. It needs to ask the analytical questions. What just changed in the search results? Why does it matter to our bottom line? Which of our pages actually deserve our attention first based on this new data?

SPEAKER_00 5:15

Aaron Powell Okay, so perception, then reasoning. What's next?

SPEAKER_01 5:20

From there, we hit the third piece, planning. The agent has to be able to break a broader goal down into sequential, actionable steps.

SPEAKER_00 5:29

Give me an example of that.

SPEAKER_01 5:30

So if the goal you gave it is to improve visibility for a specific software product category, the agent plans out the technical audits, the internal linking restructures, and the content updates required to actually achieve that goal.

SPEAKER_00 5:43

Which brings us to the mechanic part of my analogy. How does it actually turn that plan into a reality?

SPEAKER_01 5:48

That is the fourth component, action. And this is where the mechanism really matters. The system must do something useful with the plan, physically.

SPEAKER_00 5:56

So it's not just like drafting copy in a sandbox somewhere.

SPEAKER_01 5:59

No, it is pushing technical rules via an API directly to your content management system. It's updating metadata on the back end, it's structuring the HTML and syncing it with an approval layer so it can go live.

SPEAKER_00 6:11

That is wild. And what's the final piece?

SPEAKER_01 6:13

The fifth component is memory and iteration. A true agent isn't a goldfish. It retains context from its past actions.

SPEAKER_00 6:21

Meaning it remembers what it did last week.

SPEAKER_01 6:24

Exactly. It remembers what metadata it changed, it monitors the analytics to see if that specific change actually improved traffic. And then it uses that historical outcome to decide what its next logical step should be.

SPEAKER_00 6:36

So for you listening, this represents the end of exporting 10,000 keywords into a massive CSV file and just staring at it until your eyes cross.

SPEAKER_01 6:45

Honestly, good riddance to that.

SPEAKER_00 6:47

Right. The agent doesn't just hand you a list of words, it proposes a structured architectural map. It identifies which pages should act as cluster hubs, which pages should act as supporting content, and it outlines the actual sequence of production priorities.

SPEAKER_01 7:00

It is doing the heavy lifting of organizations so you can just step in and make the high-level strategic decisions.

SPEAKER_00 7:05

And because these agents have that reasoning and action capability built in, the entire timeline of how marketing teams work fundamentally shifts. We move from episodic project-based work to continuous execution.

SPEAKER_01 7:19

It's a complete paradigm shift.

SPEAKER_00 7:20

It's the difference between uh hiring an auditor to visit your store once a quarter to hand you a list of what's broken versus having a 204-7 security guard who patrols the aisles, notices a broken shelf, and actually pulls out a hammer and fixes it right then and there.

SPEAKER_01 7:36

I love that framing.

SPEAKER_00 7:37

But hold on, I have to push back here. Because if a machine is scanning a massive enterprise site every minute of every day, won't this just completely overwhelm an engineering team?

SPEAKER_01 7:46

Ah, the alert fatigue problem.

SPEAKER_00 7:48

Yeah. Nobody wants an AI that just generates 5,000 tiny, irrelevant JIRA tickets every time it finds a missing comma.

SPEAKER_01 7:55

Aaron Powell Well, that is the exact trap traditional web crawlers fall into, and it's why developers absolutely hate them. A legacy crawler just yells, you have 14,000 duplicate title tags and leaves the humans to sort out the mess. Right. The magic of a true agentic system is prioritization by impact. The agent doesn't just flag the duplicate tags, it cross-references that technical error with your Google Analytics and your revenue data.

SPEAKER_00 8:20

Oh wow.

SPEAKER_01 8:21

Yeah, it performs the financial math before it ever bothers a human.

SPEAKER_00 8:24

So it's not just slapping a severity label on it, it's actually building a business case.

SPEAKER_01 8:29

It will tell your team, these 20 duplicate tags are on high-value product pages. They are competing with your canonical URLs, and this specific error is mathematically correlating with a 15% drop in organic revenue.

SPEAKER_00 8:43

Okay, just to clarify for anyone who doesn't live in the server room, a canonical URL is essentially the master copy of a page, right?

SPEAKER_01 8:49

Yep, that's exactly right.

SPEAKER_00 8:50

So the system isn't just saying, hey, duplicate, it's recognizing that the duplicate is actively stealing search credit from the master page, and it calculates the literal cost of that theft.

SPEAKER_01 9:01

Aaron Powell That is exactly the mechanism. It ties the technical signal directly to the business consequence. And the source highlights how different platforms handle this execution phase, too.

SPEAKER_00 9:10

Aaron Powell Like who?

SPEAKER_01 9:11

Well, you have platforms like Alley AI that focus heavily on automating those on-page fixes directly. They intercept the HTML and push optimizations before the page even renders to the user without needing a developer to schedule a full engineering cycle.

SPEAKER_00 9:26

That saves so much time.

SPEAKER_01 9:27

It does. But you also have advanced enterprise teams building custom agent stacks. They are using APIs to pull data from tools like Search Console and RFs to build intelligent cues.

SPEAKER_00 9:38

And I imagine this completely changes how we look at competitive intelligence too. We're no longer just getting a monthly report saying competitor X moved to position three.

SPEAKER_01 9:47

Far from it. It becomes continuous intelligence. An agent is constantly monitoring SRP feature volatility, meaning it's watching how the actual layout of Google's search page changes minute by minute. Okay. And more importantly, the agent attempts to calculate why a competitor is winning.

SPEAKER_00 10:05

Wait, how does it figure out the why?

SPEAKER_01 10:07

By analyzing the delta between their page and yours. Are they winning because they have broader subtopic coverage? Do they have a better schema structure that Google prefers?

SPEAKER_00 10:16

Yeah, just looking at the underlying architecture.

SPEAKER_01 10:18

Exactly. Is their page aligning better with the subtle shift in what the user actually wants? The agent surfaces the mechanical reasons behind the ranking shift, which saves a human analyst dozens of hours of manual digging.

SPEAKER_00 10:30

Okay, I hear all of this, but this incredible speed, this continuous autonomous execution, it has to come with the massive dark side, right? Especially when we start talking about content creation. Because I have a real problem with this part of the AI conversation. If I give an AI access to my CMS to quote unquote refresh my content, isn't my blog just going to turn into a lifeless Wikipedia clone?

SPEAKER_01 10:57

It's a very valid fear.

SPEAKER_00 10:59

I mean, I've read AI content out in the wild. A lot of it's just homogenized garbage.

SPEAKER_01 11:03

If we connect this to the bigger picture, you've just highlighted the single greatest risk marketing teams face right now. The source material warns heavily against a phenomenon called shallow pattern matching.

SPEAKER_00 11:13

Aaron Powell Shallow pattern matching. What does that look like?

SPEAKER_01 11:15

Agents, by their very nature, are fantastic at identifying surface level correlations. An agent might stand the web and notice that all the top ranking pages for a topic have a certain subheading structure or hit a specific word count. Right. And its immediate impulse is to recommend that you just blindly imitate that structure.

SPEAKER_00 11:33

Aaron Powell So it just reverse engineers the average of what's already out there. It just regresses to the meme.

SPEAKER_01 11:38

It does. And if a team blindly follows that recommendation without injecting original thought, you lose all brand voice. You lose your editorial distinctiveness. You just become part of the background noise of the internet.

SPEAKER_00 11:50

Aaron Powell That sounds like a fast track to irrelevance.

SPEAKER_01 11:53

It is. The other massive risk the author points out is de-skilling.

SPEAKER_00 11:58

De-skilling. Yeah. Meaning the humans actually get worse at their jobs.

SPEAKER_01 12:02

Precisely. When a team becomes overly reliant on AI suggestions, they stop asking why a pattern exists in the data. They just start asking what the tool wants them to do next.

SPEAKER_00 12:12

Wow. So they stop thinking strategically.

SPEAKER_01 12:14

They lose their analytical instincts because the machine is doing the thinking for them. They transition from being strategic marketers to simply being button pushers. And search engines do not care if low-quality derivative content was written by a human or a machine. Spam is spam.

SPEAKER_00 12:30

That makes total sense. So if having the AI write the final graft is a trap, where is the actual value in using AI for content?

SPEAKER_01 12:38

The highest value of an AI agent in the content workflow actually isn't in generating net new first draft articles. The real leverage exists entirely upstream and downstream from the actual writing process.

SPEAKER_00 12:52

Okay, break that down for me. What does the upstream workflow look like?

SPEAKER_01 12:55

Upstream, it's about generating incredibly strategic content briefs. Tools like Surfer SEO or Market Muse are incredibly powerful for this mechanism. An agent can analyze the live search results, extract the recurring entities.

SPEAKER_00 13:10

Wait, when you say entities or entity clarity, you mean making sure the machine knows we are talking about Apple the computer brand, not an Apple the fruit, right?

SPEAKER_01 13:18

Aaron Powell That's a perfect example. It identifies those entities, infers the underlying search intent, and builds a comprehensive architectural brief.

SPEAKER_00 13:26

Aaron Powell So it's basically building the skeleton.

SPEAKER_01 13:28

Yes. It tells a human writer exactly what subtopics, entities, and questions need to be covered to be mathematically competitive before the human ever types a single word.

SPEAKER_00 13:37

Aaron Powell That makes total sense. If the architectural framing of the article is wrong, the draft is going to fail regardless of how beautifully it's written. So what happens downstream then?

SPEAKER_01 13:46

Downstream, the massive opportunity is in something called decay management. Large enterprise sites sit on thousands of aging pages. Search intent changes over time, new competitors arrive, statistics from three years ago get outdated.

SPEAKER_00 14:00

Right. Content rots.

SPEAKER_01 14:02

Exactly. The mechanism here is brilliant. An agent continuously scans your massive inventory of URLs. It pulls the text from your aging page, cross-references it against the current top-performing pages in real time, and identifies exactly which semantic concepts are missing. Oh wow. It then proposes specific paragraph insertions to refresh that decaying asset.

SPEAKER_00 14:25

So for you listening, the core takeaway here is that AI scales bad SEO just as efficiently as it scales good SEO. You want to use these agents to increase your throughput and elevate the structural quality of your assets, not to lower your editorial standards just so you can publish a hundred pages a day.

SPEAKER_01 14:41

Differentiation is harder than ever. The organizations that win this era won't be the ones that publish the most volume. They'll be the ones that publish material genuinely worth trusting.

SPEAKER_00 14:49

Here's where it gets really interesting, though, because the risk of producing this homogenized average content is especially dangerous right now because the very nature of searching is radically changing underneath our feet.

SPEAKER_01 15:02

It's a complete evolution.

SPEAKER_00 15:04

We are seeing a massive behavioral shift toward voice search, AI-generated overviews, and conversational interfaces. If search engines are simply synthesizing answers for the user directly on the results page, isn't the traditional game of optimizing for the 10 blue links effectively dead for informational queries?

SPEAKER_01 15:24

It is undergoing a profound transformation. The source references a really illuminating study from ResearchGate. They tracked global search behavior and found that in 2025, over 66% of COVID-related queries globally were answered entirely by AI-generals. So the optimization target has fundamentally moved for those types of queries. You aren't just trying to rank a link anymore, you are optimizing for what we call answer extraction.

SPEAKER_00 16:03

Meaning we are literally formatting our text as data payloads for a large language model to scoop up. That completely flips how we structure a sentence.

SPEAKER_01 16:14

It absolutely does. You want your content to be the definitive source material that the AI model relies on to build its summary.

SPEAKER_00 16:20

Okay, so how do we do that?

SPEAKER_01 16:22

Well, that means teams have to focus intensely on that entity clarity we discussed earlier. They need to focus on factual density, removing fluff, and packing paragraphs with hard data.

SPEAKER_00 16:32

Right, getting straight to the point.

SPEAKER_01 16:33

And structuring the HTML so it is easily parsed by a machine's logic rather than just flowing well for a human reader.

SPEAKER_00 16:40

So we are writing for a dual audience. A human reader, yes, but first, the AI that's going to explain it to the human reader.

SPEAKER_01 16:46

And this necessity ties directly into another advanced capability the guide discusses, which is predictive and anticipatory SEO. Because the landscape is shifting this fast, you can no longer afford to react to traffic drops after they happen.

SPEAKER_00 17:01

You have to be ahead of it.

SPEAKER_01 17:02

Exactly. Agents can look for early signals, emerging keyword clusters, or subtle intent drift within a category.

SPEAKER_00 17:10

Let's decode intent drift real quick. That's when a user's goal changes over time. Right. Like five years ago, someone searching best CRM wanted to read a list of features to buy one, but today maybe they search that same phrase specifically looking for free trials. The words are the same, but the intent drifted.

SPEAKER_01 17:28

That is the perfect example. An agent can spot that subtle drift in the click data and flag it to your team before your page starts losing visibility.

SPEAKER_00 17:35

Oh, that's incredibly powerful.

SPEAKER_01 17:37

It tells you to update your CRM page with free trial links before Google demotes you. And the business impact of that foresight is very real. The guide cites the 2025 McKinsey Global Survey on the state of AI.

SPEAKER_00 17:48

What did that show?

SPEAKER_01 17:49

That survey showed that 64% of organizations currently using AI say it is actively enabling innovation, not just cutting operational costs, anticipating a shift in how people search for your product and adapting your content structure before your competitors even notice the shift that is a massive competitive advantage.

SPEAKER_00 18:08

So, what does this all mean for the people actually running these teams? We have these incredibly fast agents that can perceive, reason, plan, act, and continuously alter our websites to chase moving targets in real time. Right. Giving an AI agent direct access to publish and change code on your live site feels a bit like giving an over-caffeinated intern the master password to your server without ever checking their work.

SPEAKER_01 18:32

It's a recipe for disaster if not handled correctly.

SPEAKER_00 18:35

Right. If it's generating and updating pages that fast, my immediate fear is a completely breaking my site. How do we put a leash on this thing? What does governance actually look like when operating at this speed?

SPEAKER_01 18:44

This raises an important question, and it's one the original author emphasizes heavily. In this new era, governance is your new competitive moat.

SPEAKER_00 18:53

Governance is the moat. I like that.

SPEAKER_01 18:55

The ultimate winners won't just be the fastest adopters who plug AI into everything. They will be the organizations that build the best structural safeguards around it. Total unchecked automation is rarely the right answer for anything deeply strategic.

SPEAKER_00 19:10

So how do we build the brakes? What does a safeguard look like mechanically?

SPEAKER_01 19:14

It means building explicit approval checkpoints into the workflow. An agent can perceive a problem, reason through a solution, and recommend a complex technical fix or a massive content refresh, but a human expert reviews the proposal in a staging environment before it ever goes live.

SPEAKER_00 19:31

So there's always a human gatekeeper.

SPEAKER_01 19:32

Exactly. It also means maintaining rigorous automated change logs and having instant one-click rollback options if an automated update unexpectedly breaks your site's architecture.

SPEAKER_00 19:43

Thank goodness for rollbacks.

SPEAKER_01 19:44

And it means implementing automated factual validation layers because, as we've all seen, language models can hallucinate incredibly plausible sounding lies.

SPEAKER_00 19:53

So we're talking about selective autonomy. Let the machine automate the heavy, repetitive, measurable stuff. The auditing, the data polling, the HTML structuring, but keep humans firmly stationed at the control panel for strategy, brand voice, and risk evaluation.

SPEAKER_01 20:10

That's the ideal state. The source points to the rise up fractional CMO methodology as an example of doing this correctly. They approach AI agents as an execution multiplier.

SPEAKER_00 20:20

Execution multiplier, okay.

SPEAKER_01 20:21

But that multiplier is only effective because it is built on top of a rock solid SEO strategy, sharp editorial standards, and strict business priorities like pipeline generation and actual revenue.

SPEAKER_00 20:32

They aren't just letting an AI publish blindly to see what sticks.

SPEAKER_01 20:36

No. They are using the agent to forcefully scale an already highly disciplined system.

SPEAKER_00 20:41

Which is absolutely crucial because this technology is only accelerating.

SPEAKER_01 20:44

It is. If we look at the Gartner 2025 hype cycle mentioned in the text, AI agents are listed among the fastest advancing technologies globally. Gartner predicts they will reach mainstream, ubiquitous adoption within five years.

SPEAKER_00 20:57

Five years. That is right around the corner.

SPEAKER_01 20:59

We are moving rapidly toward a reality where entire systems of execution will completely replace isolated AI tools.

SPEAKER_00 21:07

And that really brings us full circle on everything we've covered today. We started by throwing out the old paradigm, the idea of AI as just a prompt box, a passive typewriter, and we've reintroduced it as a junior operator. Yes. A mechanic capable of active perception, complex reasoning, and physical action on your website. We've seen how this radically shifts our daily work from episodic quarterly audits to continuous 247 monitoring and execution.

SPEAKER_01 21:34

And we've honestly confronted the very real traps along the way. The profound risk of de-skilling your marketing team, the danger of falling into shallow pattern matching and losing your brand voice.

SPEAKER_00 21:44

Yeah, nobody wants to read a Wikipedia clone.

SPEAKER_01 21:46

And of course, the absolute non negotiable necessity of building strong governance and human in the loop safeguards.

SPEAKER_00 21:52

Because ultimately, for you listening, human judgment is your ultimate moat. AI is dramatically lowering the cost of doing acceptable. Average work. Anyone can spin up average content now.

SPEAKER_01 22:03

It's commoditized.

SPEAKER_00 22:04

Exactly. But when average becomes hyperabundant, expert judgment, knowing why we are doing something, knowing how to interpret intent drift, and knowing how it connects to the actual business revenue, that judgment becomes more valuable than ever. You aren't being replaced by these agents. Your leverage is just being multiplied.

SPEAKER_01 22:24

It certainly creates a higher bar for practitioners, but it's an incredibly exciting one. It frees you up from the spreadsheet misery to do the strategic thinking that actually differentiates a brand in the market.

SPEAKER_00 22:35

I want to leave you with a final thought to mull over as you go about your day. The source material touched briefly on the concept of multi-agent workflows. Oh, this is fascinating. It's the idea that you don't just deploy one AI, but a team of specialized interacting AIs. Imagine a researcher agent, an auditing agent, and an editorial agent all talking to each other, debating, and passing work back and forth.

SPEAKER_01 22:58

Like a virtual department.

SPEAKER_00 22:59

Right. If we extrapolate this just a bit further, think about what this means for your daily reality in the very near future. How do you manage a team where your highest performing employees are algorithms collaborating with each other in the background?

SPEAKER_01 23:12

It's mind-bending.

SPEAKER_00 23:14

In a world where your AI marketing agents are actively negotiating and countermaneuvering for search visibility against your competitors' AI agents in real time, your job transforms completely. You are no longer just a marketer. You are the governor of a digital ecosystem. You're the one setting the rules of engagement for the machines.

SPEAKER_01 23:34

It's a profound shift in professional identity.

SPEAKER_00 23:36

It really is. So keep asking the big questions. Keep those analytical instincts razor sharp. And whatever you do, don't let the over caffeinated intern loose on your server without checking their work. Thanks for joining us on this deep dive.