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AI power users are here and the case for agent-friendly software is materializing. Aaron Levie on agents outnumbering people 1000x: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as...

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a16z

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42,152 Aufrufe • vor 18 Tagen •via X (Twitter)

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28 Kommentare

Profilbild von suqitah
suqitahvor 18 Tagen

coding its way through whatever task it needs is exactly the line that should make security teams nervous

Profilbild von Ehsan Azish
Ehsan Azishvor 18 Tagen

an agent using apis through whatever task it needs is just a script with worse error handling

Profilbild von Nico
Nicovor 18 Tagen

Agent friendly usually means an API you already had, documented properly

Profilbild von Anton Viborniy
Anton Viborniyvor 18 Tagen

The interesting part is that agents may kill the UI moat. If an agent interacts with every SaaS through APIs, the product with the best interface no longer necessarily wins. The product with the best infrastructure does.

Profilbild von elian
elianvor 18 Tagen

sure, aaron, whatever you say

Profilbild von The AI Therapist
The AI Therapistvor 18 Tagen

Aaron Levie wants software built for agents. The real bottleneck isn't building it, it's the average human tolerance for being managed by a bot that hallucinates your name twice before lunch.

Profilbild von Phong Designs AI Systems
Phong Designs AI Systemsvor 18 Tagen

The 1000x number changes what a feature costs, not just who uses it. Human traffic follows attention, so a rough edge on a rare path stays cheap because few people ever reach it. An agent reads the docs and exercises every path uniformly. The long tail stops being a tail.

Profilbild von Dave Burrells
Dave Burrellsvor 18 Tagen

If agents outnumber people 1,000 to 1, what do they do after they can call an API? Talking to software is coordination. An economy starts when they can price a job, settle it, and carry a reputation for the outcome. That’s the piece after “more agents.” 👇

Profilbild von Adel Bucetta
Adel Bucettavor 17 Tagen

the honest answer is, most companies still haven't figured out how to design for human-machine collaboration. till then, agent-friendly interfaces will keep being a kludge

Profilbild von EKOS _ AGI 🦊 🇮🇷
EKOS _ AGI 🦊 🇮🇷vor 18 Tagen

This is where the agent economy gets interesting. When agents become the primary software users, reliable machine-readable context becomes infrastructure. @ekosproject is building exactly that layer for enterprise knowledge.

Profilbild von Dave Mellish
Dave Mellishvor 18 Tagen

So are we still bearish on knowledge work replacement at scale?

Profilbild von Rory Bernier
Rory Berniervor 18 Tagen

damn

Profilbild von Ella Tech & Tool
Ella Tech & Toolvor 18 Tagen

Agents humans soon 🔥 1000x scale is wild

Profilbild von broadfield-dev
broadfield-devvor 18 Tagen

If you are still using other peoples software, you are not an AI power user. Entry level at best.

Profilbild von EKOS _ AGI 🦊 🇮🇷
EKOS _ AGI 🦊 🇮🇷vor 18 Tagen

@ekosproject

Profilbild von EVR
EVRvor 18 Tagen

If agents outnumber people 1000x, they cannot share one laptop, one filesystem, and one set of credentials. Isolated compute is the actual interface. A VM per agent, or the blast radius scales with the agents.

Profilbild von AiClaw
AiClawvor 18 Tagen

The API, CLI and MCP point is the practical tell: when agents become the main users, documentation stops being a nice-to-have and becomes part of the product.

Profilbild von AscendCapital
AscendCapitalvor 18 Tagen

Most product teams are still treating APIs as an afterthought while building for human UI. If agents are outnumbering users 1000x, your API and context layer are your primary product surface area.

Profilbild von Doug
Dougvor 18 Tagen

This is the bigger shift: software won’t just need a good human interface. It’ll need a good interface for machines that can actually use it.

Profilbild von Leo Lu
Leo Luvor 18 Tagen

Agent interfaces may end up looking more like API contracts than UIs.

Profilbild von Voriq Network
Voriq Networkvor 17 Tagen

Would love to collab by providing an infrastructure for your agents and the proper tools and SDKs Is this something we can discuss with the right person at a16z ?

Profilbild von TriDung.sol 🐬TermMax
TriDung.sol 🐬TermMaxvor 18 Tagen

the ui for humans is becoming the legacy layer, api is the new focus

Profilbild von Macro Bombastic
Macro Bombasticvor 18 Tagen

yeah the api is becoming the real frontend for agents

Profilbild von OctoOps - Agent Ops inPublic
OctoOps - Agent Ops inPublicvor 18 Tagen

1000x agents means 1000x rate limits and quota fights. agent-friendly software mostly means idempotent writes and a spend ceiling per caller, not a prettier API.

Profilbild von Bobby
Bobbyvor 18 Tagen

The future is bright for America and her allies. Semper Fidelis

Profilbild von Jay Dev
Jay Devvor 18 Tagen

Building the agent interface as a co-equal to the human interface is the part most teams still bolt on last. At 1000x the agent count, does that ratio flip which interface gets the primary design pass first?

Profilbild von dhinna ship .ico
dhinna ship .icovor 18 Tagen

Implies separate schemas and action endpoints, not a wrapped human UI

Profilbild von mcdeezy
mcdeezyvor 18 Tagen

was built for agents I had never built a CLI before but it was obvious that agents would interact with the opensource code via CLI very fun coding and architecting for agents instead of the normal human which color should i make the button hmmm 🤔🤔🤔

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Y Combinator

38,133 Aufrufe • vor 7 Monaten

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:
2:49

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 Aufrufe • vor 1 Jahr

.Lassie co-founder and CEO Steijn Pelle says small businesses like doctors' offices should run themselves: "The busy work is done by agents." "We want to build agents for the business that then will interface with the personal agent of a consumer." "It needs to really work, and the onboarding needs to be as simple as onboarding on Coinbase or Stripe." "All small businesses at an abstract level have a system of record they need to read and write into. They all have customers... it's interacting and transacting around payments. You need to book appointments." "The end goal is if we served all the doctor offices, that we help all the small businesses across the world." steijnpelle
1:40

.Lassie co-founder and CEO Steijn Pelle says small businesses like doctors' offices should run themselves: "The busy work is done by agents." "We want to build agents for the business that then will interface with the personal agent of a consumer." "It needs to really work, and the onboarding needs to be as simple as onboarding on Coinbase or Stripe." "All small businesses at an abstract level have a system of record they need to read and write into. They all have customers... it's interacting and transacting around payments. You need to book appointments." "The end goal is if we served all the doctor offices, that we help all the small businesses across the world." steijnpelle

a16z

34,504 Aufrufe • vor 1 Monat

The ceo of Box says if you're not building for agents, you won't exist as a software company in 2-3 years. Aaron Levie recalled how in the 90s, it was mainframes built for institutions. If you didn't build for the CIO or IT org, you didn't exist. You could build software for users, but no one cared. Similarly, in the mid 2000s, it was software built for end users. If you didn't take that route, you got completely trounced. The likes of Yammer, Slack, Zoom, etc., ripped through enterprises with viral adoption. Bottom-up and completely user driven. And now it's software built for agents. We're going to have trillions of agent runs. The systems that optimize for agents the most will win. - lower latency - better API exposure - better system intelligence - serves the right information when called Agents will eventually choose their own tools on the fly and make purchasing decisions at runtime. All based on past experiences/online reviews/performance, sans any procurement process. The more pragmatic version is companies swapping out bad tools / tech that don't work well with agents. - crm doesn't expose the right APIs - auth can't handle agent scale requests - database has too much latency for agent workloads Being good enough for humans won't work because they have to pass the litmus test for agents to make the cut.
2:15

The ceo of Box says if you're not building for agents, you won't exist as a software company in 2-3 years. Aaron Levie recalled how in the 90s, it was mainframes built for institutions. If you didn't build for the CIO or IT org, you didn't exist. You could build software for users, but no one cared. Similarly, in the mid 2000s, it was software built for end users. If you didn't take that route, you got completely trounced. The likes of Yammer, Slack, Zoom, etc., ripped through enterprises with viral adoption. Bottom-up and completely user driven. And now it's software built for agents. We're going to have trillions of agent runs. The systems that optimize for agents the most will win. - lower latency - better API exposure - better system intelligence - serves the right information when called Agents will eventually choose their own tools on the fly and make purchasing decisions at runtime. All based on past experiences/online reviews/performance, sans any procurement process. The more pragmatic version is companies swapping out bad tools / tech that don't work well with agents. - crm doesn't expose the right APIs - auth can't handle agent scale requests - database has too much latency for agent workloads Being good enough for humans won't work because they have to pass the litmus test for agents to make the cut.

Ivan Burazin

22,655 Aufrufe • vor 5 Monaten

Today we open the Zapier SDK to everyone. If you're building with AI agents, this is for you. I've been using this for 2 months. It's totally changed how I do my job. You install it in your coding agent. Cursor, Claude Code, Codex, whatever you use. Now that agent has access to 8,000+ apps through Zapier and can do anything those APIs can do. I think it’s the most powerful thing we’ve launched in years. Now in open beta. Just give this link right to your agent:
2:47

Today we open the Zapier SDK to everyone. If you're building with AI agents, this is for you. I've been using this for 2 months. It's totally changed how I do my job. You install it in your coding agent. Cursor, Claude Code, Codex, whatever you use. Now that agent has access to 8,000+ apps through Zapier and can do anything those APIs can do. I think it’s the most powerful thing we’ve launched in years. Now in open beta. Just give this link right to your agent:

Wade Foster

175,178 Aufrufe • vor 5 Monaten

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.
1:47

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,591 Aufrufe • vor 1 Jahr