SaaS 애플리케이션의 종말: AI 에이전트와 소프트웨어 개발의 미래

### 소프트웨어의 미래: 앱에서 AI 에이전트로의 전환
* 🤖 Microsoft의 CEO 사티아 나델라는 **기존 애플리케이션이 붕괴 직전에 있으며, 소프트웨어 개발을 재정의할 AI 에이전트에 자리를 내줄 것**이라고 대담하게 선언했습니다.
* 📉 나델라가 이러한 애플리케이션이 **CRUD(생성, 읽기, 업데이트, 삭제) 데이터베이스 위에 얇은 UI 계층**에 불과하다고 제안하면서 **SaaS(서비스로서의 소프트웨어)의 개념이 도전**을 받고 있습니다.
* 🔍 미래에는 AI 에이전트가 데이터베이스와 직접 상호 작용하여 **복잡한 애플리케이션의 필요성을 없애고 잠재적으로 SaaS 분야의 개발자 수요를 줄일 수 있을 것**입니다.
* 📊 이러한 변화는 비즈니스 로직이 AI에 의해 처리되어 사용자가 하드코딩된 로직 없이도 **상담원에게 보고서 생성이나 이메일 전송**과 같은 작업을 수행하도록 간단히 지시할 수 있게 된다는 것을 의미합니다.
* 💻 지능형 AI 에이전트를 만들기 위한 플랫폼인 Chatbase는 **기업이 고급 AI 기능**을 통해 운영을 간소화하고 개인화된 상호 작용을 제공할 수 있도록 지원함으로써 이러한 변화를 잘 보여주고 있습니다.
* ⚙ AI가 백엔드 로직을 대신함에 따라 에이전트가 여러 데이터베이스 유형과 원활하게 상호 작용할 수 있는 **데이터베이스의 선택**이 중요해질 것입니다.
* 📈 Excel과 같은 도구에 AI를 통합하면 사용자가 원하는 결과를 간단히 설명하고 **AI가 필요한 분석을 생성**할 수 있기 때문에 그 필요성에 대한 의문이 제기될 수 있습니다.
* 🚀 전반적으로 소프트웨어 환경은 큰 변화를 맞이하고 있으며, 기업들은 **AI 기반 솔루션이 지배하는 시대**에 적응하지 않으면 도태될 위험을 감수해야 합니다.

AI 에이전트는 비즈니스 애플리케이션을 대체하여 기존 SaaS의 필요성을 없애고 소프트웨어 개발에 큰 변화를 가져올 것입니다.

I think the notion that business applications exist, that's probably where they'll all collapse, right in the agent era. Microsoft's CEO Satya Nadella said apps as we know them are going away in favor of agents, and this is a huge statement. He basically put a flag in the

ground showing where the future of software development is going. No more applications, which means no more SaaS, which also means likely far fewer developers. So let's watch the video, and I'm going to break it down for you. So this is on the BG Squared podcast. I'll

drop a link to the full interview down below. SaaS applications or biz apps. So let me just speak of our own Dynamics thing. The approach, at least we're taking, is I think the notion that business applications exist, that's probably where they'll all collapse right in the agent era because

if you think about it right, they are essentially CRUD databases with a bunch of business logic. Okay, I'm going to pause there because what he just said might sound like no big deal, but it is actually a stunning proclamation of the future. What he essentially said is that SaaS, and that

means Software as a Service, is essentially just a thin UI layer on top of a database. And when he says CRUD, that means Create, Read, Update, Destroy; those are the base units of interactions between an interface and a database. So create, create a new record, read, extract information from the

database, update, make a change to an existing record, and destroy, delete. So all he's saying is there's going to be the underlying database, the fundamental data of what you need, and then it's going to be agents that are interacting directly with the database, and if you've

I've been watching this channel; you know, I've been talking about this for a long time. I truly believe the entire application stack is going to disappear. There just really is no need for it when you have artificial intelligence interacting with the core, grounded data that sits within a database. And again,

what does that actually mean for the entire SaaS industry? What does that mean for application developers? I don't know exactly, but I have a feeling it's going to look vastly different than it looks today. And I've been in SaaS my entire career. I have built multiple SaaS

companies. I've worked for SaaS companies, and if I'm being transparent, I probably wouldn't start another SaaS company right now, and I probably wouldn't invest in any SaaS companies right now either. It's just too unknown. Now, that isn't to say there won't be software companies in the

future; it's just going to look drastically different. Let's keep watching. Crowd databases with a bunch of business logic—the business logic is all going to these agents, and these agents are going to be multi-repo CRUD. Right? So they're not going to discriminate between uh,

what the backend is; they're going to update multiple databases, and all the logic will be in the AI tier, so to speak. I'm so excited to show you this video. This 3 1/2-minute video might be the clearest depiction of what

the future of software engineering is going to look like. Now, when he's talking about business logic, he basically means taking that core data found in a database and actually doing things with it, whether it's updating a CRM record or sending out emails based on different criteria found in the database or

Anything, any single piece of software that sits on top of a database—that's what he's talking about. All of that business logic is going to be compressed into the agent. The agent will be able to accomplish anything, and all you need to do is tell it what you want.  Give me a

graph of my top five customers by revenue. Okay, now write emails to all five of those customers telling them I want to do business with them in 2025. All of this will just automatically be done where previously it would take hard-coded business logic on top of the

database. Now that's not necessary. You just tell the agent what you want, and it will either know how to accomplish it or write tools to go accomplish it on your behalf. And when I say tools, I just mean it's going to write its own code to

interact with the database, to send an email, and so on.

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they're customized for your business and know to give the right answers at the right time. And they just launched a brand new feature: AI actions. And if you watch this channel at all, you know I'm all about agents taking actions as the future of agentic workflows, so now

Chatbase allows these agents to not only respond to your customers on your behalf, but actually take real-time actions based on what they're looking for. Some of these actions include getting real-time data from their account or even allowing them to update things in their account

based on the conversation they're having with that agent. So check out Chatbase today. Thank you again to Chatbase for sponsoring this video, and now back to the video. Once the AI tier becomes the place where all the logic is, then people start replacing the

back ends. Right? We, people, you know, that's what, you know... In fact, it's interesting, as we speak, I think we are seeing pretty high rates of wins on Dynamics backends and the agent use, and we are going to go pretty aggressively and try to collapse it all

right, whether it's in customer service, whether it is in... By the way, the other fascinating thing that's increasing is just not CRM, but even our what we call finance and operations, because people want more AI-native biz apps. Right? Another thing that he clearly

says is the backend doesn't matter; the agents aren't specialized in one type of database; they really don't care. So really, it's about building the database that works most efficiently with the agent, is cheapest, is the right one for the right use case. So as an engineer or a

data provider, you really just need to figure out what's the best database to use, and then the agents do not care. And so it's going to be interesting how companies choose the database that they decide to use. That means the biz, the logic tier, can be orchestrated by AI and

AI agents, so, in other words, Copilot, agent to my business application, should be very seamless. Now, in the same way, you could even say, "Hey, why do I need Excel?"  Interestingly enough, one of the most exciting things for me is Excel with

Python is like GitHub with Copilot, right? That's essentially... So what we've done is, when you have Excel like this—by the way, this will be fun for you guys—which is, you should just bring up Excel, bring up Copilot, and start playing with

it, because it's no longer like, "Oh, you know..." It is like having a data analyst. Uh, and so it's no longer just making sense of the numbers that you have; it will do the plan for you, right? It will literally... How Get Up Copilot workspace creates the plan and

then it executes the plan. It... This is like a data analyst who is using Excel as a sort of ad-hoc visualization tool to do analysis. Scratch that. So he is saying, "Why do you even need Excel?" And he probably has thought a lot about this because, really, what is Excel? It is a

thin UI layer on top of a database. And, of course, you can add a bunch of business logic and analytics. But here's the thing: What he's describing is essentially, if AI can write Python code to analyze the data, why do you need Excel at all? And he might be right; he

probably is right. Why do you need Excel? If I need an analysis of a huge amount of data, I just say what I need. I just need to describe the end product: I need a graph, I need a chart, I need a 3D visualization—whatever it is, you just

Describe the end result. You have the core data, the raw data, and then the agent writes the Python code to actually extract the right data and put it in the right format for what you asked. Now let's keep watching, so it's got a tools—you so the co-pilot is using Excel as a

tool with all of its action space because it can generate, and it has a Python interpreter that is, in fact—and by the way, when he says Python interpreter, that just means the ability to execute Python code—in fact, a great way to reconceptualize Excel. At some

point you could say, 'Hey, I'll generate all of Excel,' uh, and that is also true. After all, there's a code interpreter, right? So therefore, you can generate anything. Um, and so yes, I think there will be disruption, but so the way we are approaching, at least our M365 stuff, is

one: build Copilot as that organizing layer UI for AI, get all agents including our own agents. You can say Excel is an agent to my Copilot; Word is an agent. It's kind of specialized canvases. Which is, I'm doing a legal document; let me

take it into Pages and then to Word and then have the Copilot go with it; uh, go into Excel and have the Copilot go with it. This is a fundamental change in how Microsoft applications work and really any software-as-a-service business. This

is a complete restructuring of the entire industry, and for somebody who has been in SaaS for so long, it is so fascinating to watch. And companies are either going to adopt it and kind of evolve with the times, or they're going to die. There is no in-between, and it's

Clear that Satya Nadella from Microsoft is thinking well ahead; he is already very invested in OpenAI. He already has the best model; he's already thinking about Copilot. Whatever you think about Copilot and its quality today, at least the structure, the architecture of how

it's going to work in the future is clear and right, in my opinion. And so that's the whole video, and it's again only 3 1/2 minutes, but clearly lays out what the future of software will look like. All he's talking about is

enterprise software, business software, but at the same time that can be applied to consumer as well. What's the difference? Where a consumer, it's just a database and you're getting a different type of interface on top of it. And so if you had an agent, why do you need the interface

at all? The future of software development, the future of application development, the future of interaction with data is going to be drastically different than it is today, and I'm so excited for it. If you enjoyed this video, please consider giving it a like and subscribe, and I'll see you in the next

Microsoft CEO’s Shocking Prediction: “Agents Will Replace ALL Software"

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AI 에이전트로 인해 기존 비즈니스 애플리케이션의 노후화가 임박했습니다.

사티아 나델라는 우리가 알고 있는 앱이 에이전트로 대체될 것이라고 예측했습니다.

SaaS로부터의 전환과 잠재적인 개발자 수요 감소.

비즈니스 로직이 있는 CRUD 데이터베이스로 설명되는 비즈니스 애플리케이션.

SaaS는 데이터베이스 위에 얇은 UI 계층으로 간주됩니다.

AI의 직접적인 데이터베이스 상호 작용으로 애플리케이션 스택이 사라질 것이라는 믿음은 사라질 것입니다.

비즈니스 로직을 처리하고 데이터베이스와 상호 작용하는 AI 에이전트의 역할.

여러 데이터베이스에서 멀티 리포지토리 CRUD 작업을 관리하는 AI 에이전트.

애플리케이션에서 AI 에이전트로 전환하는 비즈니스 로직.

상담원이 사용자 요청에 따라 직접 작업을 수행합니다.

에이전트는 데이터베이스 및 기타 시스템과 상호 작용하는 코드를 동적으로 생성합니다.

소프트웨어 산업과 Microsoft의 전략에 미치는 영향.

에이전트 사용 시 Dynamics 백엔드에서 높은 승률이 관찰되었습니다.

AI 네이티브 비즈니스 애플리케이션에 대한 수요 증가.

상담원 상호작용에 최적화된 데이터베이스 선택으로 초점을 전환합니다.

AI 기반 데이터 분석 시대에 Excel의 필요성에 의문을 제기합니다.

AI 에이전트를 애플리케이션에 통합하는 Microsoft의 접근 방식입니다.

코파일럿을 AI 에이전트를 위한 구성 UI 레이어로 사용합니다.

Excel 및 Word와 같은 애플리케이션은 Copilot을 위한 특수 캔버스 역할을 합니다.

이는 서비스형 소프트웨어 산업의 근본적인 구조조정을 의미합니다.

소프트웨어 개발과 데이터 상호 작용의 미래.

상담원과 데이터베이스가 직접 상호 작용하는 사용자 인터페이스의 잠재적 노후화.

소프트웨어 개발, 애플리케이션 개발 및 데이터 상호 작용의 중요한 변화를 예측합니다.