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launched its next generation of OpenSearch Serverless, a fully managed search and vector database — essentially a system for storing and retrieving information at scale — that’s designed specifically for agentic workloads. AWS says the new system can instantly scale up when agents trigger tasks and scale back down to zero when idle.

The launch reflects a growing realization across the tech industry: Infrastructure originally designed for a human-driven internet doesn’t work as well in a world increasingly populated by agents.

While AI agents still represent a relatively small portion of internet activity, machine-generated traffic is already significant, and poised to grow. Cloudflare says bots accounted for 31% of overall HTTP traffic over the last six months. AI crawlers, search engines, and assistants made up roughly a quarter of all bot requests during that period. 

“Non-human traffic will exceed human traffic sometime in the first half of 2027,” said Lai Yi Ohlsen, senior product manager at Cloudflare, to TechCrunch.

At Google’s I/O developer conference last week, the company said users will be able to start delegating tasks to AI systems, like researching purchases, booking travel, browsing the web, and interacting with apps. But the buck doesn’t stop at consumer-focused AI agents. Enterprises are increasingly deploying agents internally and for their customers, creating new kinds of machine-generated traffic behind the scenes. 

As a result, cloud providers and infrastructure companies have been reckoning with how to adapt systems built for humans to a world of agents that are constantly and autonomously retrieving information, invoking tools, and generating machine-to-machine traffic. 

That’s where AWS’s new OpenSearch Serverless comes in. 

“The timing is straightforward. Agents are moving from experimentation into production, and they create traffic patterns that previous infrastructure simply wasn’t designed for,” Tia White, general manager for Amazon OpenSearch Service, told TechCrunch. “They spike without warning, they go idle without notice, and enterprise needs search that keeps up without paying for empty or idle compute.”

The key technical change with this new generation is that it decouples compute from storage, allowing compute to scale up in seconds to accommodate agent traffic bursts and to scale down to zero, so customers pay $0 when agents are idle.

“Previously, even in our prior Serverless version, you had to have at least one instance operational and running because storage and compute were coupled,” White said. “You couldn’t just automatically spin up [compute] at the rate you needed to, so you always had idle compute reserved for your workload, whether you were using it or not.”

Think of it like always paying for a parking space, even when you’re not using it. With AWS’s upgraded Serverless, it’s more like paying for a metered parking spot.

At launch, OpenSearch Serverless will integrate natively with AI development platforms like Vercel and Kiro, so developers can deploy production-ready search and vector backends for agents without managing infrastructure. 

The shift is emerging across the cloud industry. Databricks and Snowflake are repositioning themselves as AI memory and retrieval systems for enterprise data. Microsoft has rolled out updates to Azure designed to handle AI agent bursts and share memory between agents. Cloudflare, in a similar vein to Amazon, last month introduced infrastructure aimed at giving agents persistent environments and instant scalability. 

The more companies deploy AI agents, the more pressure there will be to redesign infrastructure around machine-generated workloads, which in turn could make agents cheaper and easier to deploy at larger scales.

 

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#internet #rebuilt #machines #TechCrunchagentic search,AI agents,AWS,aws opensearch serverless"> The internet is being rebuilt for machines | TechCrunch Cloud infrastructure has long been designed around humans who search, click, scroll, and stream in a steady and predictable fashion. AI agents behave differently. They can unleash a swell of activity, spinning up multiple sub-agents that query hundreds of databases, search documents, and call APIs in seconds and then disappear as quickly as they arrived.  Under that premise, Amazon is redesigning a core piece of its cloud infrastructure. On Thursday, AWS launched its next generation of OpenSearch Serverless, a fully managed search and vector database — essentially a system for storing and retrieving information at scale — that’s designed specifically for agentic workloads. AWS says the new system can instantly scale up when agents trigger tasks and scale back down to zero when idle. The launch reflects a growing realization across the tech industry: Infrastructure originally designed for a human-driven internet doesn’t work as well in a world increasingly populated by agents. While AI agents still represent a relatively small portion of internet activity, machine-generated traffic is already significant, and poised to grow. Cloudflare says bots accounted for 31% of overall HTTP traffic over the last six months. AI crawlers, search engines, and assistants made up roughly a quarter of all bot requests during that period.  “Non-human traffic will exceed human traffic sometime in the first half of 2027,” said Lai Yi Ohlsen, senior product manager at Cloudflare, to TechCrunch. At Google’s I/O developer conference last week, the company said users will be able to start delegating tasks to AI systems, like researching purchases, booking travel, browsing the web, and interacting with apps. But the buck doesn’t stop at consumer-focused AI agents. Enterprises are increasingly deploying agents internally and for their customers, creating new kinds of machine-generated traffic behind the scenes.  As a result, cloud providers and infrastructure companies have been reckoning with how to adapt systems built for humans to a world of agents that are constantly and autonomously retrieving information, invoking tools, and generating machine-to-machine traffic.  That’s where AWS’s new OpenSearch Serverless comes in.  “The timing is straightforward. Agents are moving from experimentation into production, and they create traffic patterns that previous infrastructure simply wasn’t designed for,” Tia White, general manager for Amazon OpenSearch Service, told TechCrunch. “They spike without warning, they go idle without notice, and enterprise needs search that keeps up without paying for empty or idle compute.” The key technical change with this new generation is that it decouples compute from storage, allowing compute to scale up in seconds to accommodate agent traffic bursts and to scale down to zero, so customers pay alt=
Tech-news

launched its next generation of OpenSearch Serverless, a fully managed search and vector database — essentially a system for storing and retrieving information at scale — that’s designed specifically for agentic workloads. AWS says the new system can instantly scale up when agents trigger tasks and scale back down to zero when idle.

The launch reflects a growing realization across the tech industry: Infrastructure originally designed for a human-driven internet doesn’t work as well in a world increasingly populated by agents.

While AI agents still represent a relatively small portion of internet activity, machine-generated traffic is already significant, and poised to grow. Cloudflare says bots accounted for 31% of overall HTTP traffic over the last six months. AI crawlers, search engines, and assistants made up roughly a quarter of all bot requests during that period. 

“Non-human traffic will exceed human traffic sometime in the first half of 2027,” said Lai Yi Ohlsen, senior product manager at Cloudflare, to TechCrunch.

At Google’s I/O developer conference last week, the company said users will be able to start delegating tasks to AI systems, like researching purchases, booking travel, browsing the web, and interacting with apps. But the buck doesn’t stop at consumer-focused AI agents. Enterprises are increasingly deploying agents internally and for their customers, creating new kinds of machine-generated traffic behind the scenes. 

As a result, cloud providers and infrastructure companies have been reckoning with how to adapt systems built for humans to a world of agents that are constantly and autonomously retrieving information, invoking tools, and generating machine-to-machine traffic. 

That’s where AWS’s new OpenSearch Serverless comes in. 

“The timing is straightforward. Agents are moving from experimentation into production, and they create traffic patterns that previous infrastructure simply wasn’t designed for,” Tia White, general manager for Amazon OpenSearch Service, told TechCrunch. “They spike without warning, they go idle without notice, and enterprise needs search that keeps up without paying for empty or idle compute.”

The key technical change with this new generation is that it decouples compute from storage, allowing compute to scale up in seconds to accommodate agent traffic bursts and to scale down to zero, so customers pay $0 when agents are idle.

“Previously, even in our prior Serverless version, you had to have at least one instance operational and running because storage and compute were coupled,” White said. “You couldn’t just automatically spin up [compute] at the rate you needed to, so you always had idle compute reserved for your workload, whether you were using it or not.”

Think of it like always paying for a parking space, even when you’re not using it. With AWS’s upgraded Serverless, it’s more like paying for a metered parking spot.

At launch, OpenSearch Serverless will integrate natively with AI development platforms like Vercel and Kiro, so developers can deploy production-ready search and vector backends for agents without managing infrastructure. 

The shift is emerging across the cloud industry. Databricks and Snowflake are repositioning themselves as AI memory and retrieval systems for enterprise data. Microsoft has rolled out updates to Azure designed to handle AI agent bursts and share memory between agents. Cloudflare, in a similar vein to Amazon, last month introduced infrastructure aimed at giving agents persistent environments and instant scalability. 

The more companies deploy AI agents, the more pressure there will be to redesign infrastructure around machine-generated workloads, which in turn could make agents cheaper and easier to deploy at larger scales.

 

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#internet #rebuilt #machines #TechCrunchagentic search,AI agents,AWS,aws opensearch serverless">The internet is being rebuilt for machines | TechCrunch

Cloud infrastructure has long been designed around humans who search, click, scroll, and stream in a steady and predictable fashion. AI agents behave differently. They can unleash a swell of activity, spinning up multiple sub-agents that query hundreds of databases, search documents, and call APIs in seconds and then disappear as quickly as they arrived. 

Under that premise, Amazon is redesigning a core piece of its cloud infrastructure. On Thursday, AWS launched its next generation of OpenSearch Serverless, a fully managed search and vector database — essentially a system for storing and retrieving information at scale — that’s designed specifically for agentic workloads. AWS says the new system can instantly scale up when agents trigger tasks and scale back down to zero when idle.

The launch reflects a growing realization across the tech industry: Infrastructure originally designed for a human-driven internet doesn’t work as well in a world increasingly populated by agents.

While AI agents still represent a relatively small portion of internet activity, machine-generated traffic is already significant, and poised to grow. Cloudflare says bots accounted for 31% of overall HTTP traffic over the last six months. AI crawlers, search engines, and assistants made up roughly a quarter of all bot requests during that period. 

“Non-human traffic will exceed human traffic sometime in the first half of 2027,” said Lai Yi Ohlsen, senior product manager at Cloudflare, to TechCrunch.

At Google’s I/O developer conference last week, the company said users will be able to start delegating tasks to AI systems, like researching purchases, booking travel, browsing the web, and interacting with apps. But the buck doesn’t stop at consumer-focused AI agents. Enterprises are increasingly deploying agents internally and for their customers, creating new kinds of machine-generated traffic behind the scenes. 

As a result, cloud providers and infrastructure companies have been reckoning with how to adapt systems built for humans to a world of agents that are constantly and autonomously retrieving information, invoking tools, and generating machine-to-machine traffic. 

That’s where AWS’s new OpenSearch Serverless comes in. 

“The timing is straightforward. Agents are moving from experimentation into production, and they create traffic patterns that previous infrastructure simply wasn’t designed for,” Tia White, general manager for Amazon OpenSearch Service, told TechCrunch. “They spike without warning, they go idle without notice, and enterprise needs search that keeps up without paying for empty or idle compute.”

The key technical change with this new generation is that it decouples compute from storage, allowing compute to scale up in seconds to accommodate agent traffic bursts and to scale down to zero, so customers pay $0 when agents are idle.

“Previously, even in our prior Serverless version, you had to have at least one instance operational and running because storage and compute were coupled,” White said. “You couldn’t just automatically spin up [compute] at the rate you needed to, so you always had idle compute reserved for your workload, whether you were using it or not.”

Think of it like always paying for a parking space, even when you’re not using it. With AWS’s upgraded Serverless, it’s more like paying for a metered parking spot.

At launch, OpenSearch Serverless will integrate natively with AI development platforms like Vercel and Kiro, so developers can deploy production-ready search and vector backends for agents without managing infrastructure. 

The shift is emerging across the cloud industry. Databricks and Snowflake are repositioning themselves as AI memory and retrieval systems for enterprise data. Microsoft has rolled out updates to Azure designed to handle AI agent bursts and share memory between agents. Cloudflare, in a similar vein to Amazon, last month introduced infrastructure aimed at giving agents persistent environments and instant scalability. 

The more companies deploy AI agents, the more pressure there will be to redesign infrastructure around machine-generated workloads, which in turn could make agents cheaper and easier to deploy at larger scales.

 

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#internet #rebuilt #machines #TechCrunchagentic search,AI agents,AWS,aws opensearch serverless

Cloud infrastructure has long been designed around humans who search, click, scroll, and stream in…

Notion is stepping into the agentic era.

In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database.

By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases.

In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says.

However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure.

“It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.”

Notion just turned its workspace into a hub for AI agents | TechCrunch Productivity software maker Notion is stepping into the agentic era. In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database. By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases. In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says. However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure. “It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.” Image Credits:Notion Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure. You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you. The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment. Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current. Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.” Image Credits:Notion Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough. Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more. There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs. Image Credits:Notion Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans. The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure. It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms. “Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion
Image Credits:Notion

Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure.

You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you.

The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment.

Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current.

Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.”

Image Credits:Notion

Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough.

Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more.

There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs.

Image Credits:Notion

Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans.

The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure.

It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms.

“Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion"> Notion just turned its workspace into a hub for AI agents | TechCrunch Productivity software maker Notion is stepping into the agentic era. In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database. By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases. In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says. However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure. “It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.” Image Credits:Notion Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure. You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you. The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment. Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current. Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.” Image Credits:Notion Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough. Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more. There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs. Image Credits:Notion Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans. The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure. It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms. “Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion
Tech-news

Notion is stepping into the agentic era.

In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database.

By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases.

In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says.

However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure.

“It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.”

Notion just turned its workspace into a hub for AI agents | TechCrunch Productivity software maker Notion is stepping into the agentic era. In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database. By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases. In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says. However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure. “It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.” Image Credits:Notion Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure. You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you. The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment. Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current. Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.” Image Credits:Notion Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough. Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more. There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs. Image Credits:Notion Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans. The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure. It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms. “Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion
Image Credits:Notion

Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure.

You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you.

The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment.

Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current.

Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.”

Image Credits:Notion

Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough.

Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more.

There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs.

Image Credits:Notion

Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans.

The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure.

It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms.

“Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion">Notion just turned its workspace into a hub for AI agents | TechCrunch

Productivity software maker Notion is stepping into the agentic era.

In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database.

By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases.

In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says.

However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure.

“It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.”

Notion just turned its workspace into a hub for AI agents | TechCrunch Productivity software maker Notion is stepping into the agentic era. In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database. By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases. In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says. However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure. “It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.” Image Credits:Notion Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure. You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you. The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment. Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current. Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.” Image Credits:Notion Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough. Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more. There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs. Image Credits:Notion Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans. The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure. It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms. “Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion
Image Credits:Notion

Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure.

You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you.

The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment.

Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current.

Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.”

Image Credits:Notion

Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough.

Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more.

There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs.

Image Credits:Notion

Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans.

The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure.

It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms.

“Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Notion #turned #workspace #hub #agents #TechCrunchAI,AI agents,Notion

Productivity software maker Notion is stepping into the agentic era. In a live-streamed product announcement…