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Software > Systems > Societies As 2025 comes to a close, we’re all moving from isolated software tools to agentic systems coordinating those tools to emerging “societies” of autonomous agents that can research, generate, QA, and ship with minimal (to zero) human intervention. Dan Batten and I spent the...

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Emmett

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13,505 次观看 • 6 个月前 •via X (Twitter)

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Today, we’re introducing Spawnlabs We built it to push the limits of what software can be spawned, from simple tools to complex systems Software has always been a way to extend what we can do and create. and now we're building spawnlabs to automate the ability to spawn software that solves harder problems and builds deeper systems. live now
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Today, we’re introducing Spawnlabs We built it to push the limits of what software can be spawned, from simple tools to complex systems Software has always been a way to extend what we can do and create. and now we're building spawnlabs to automate the ability to spawn software that solves harder problems and builds deeper systems. live now

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Palantir is ditching traditional systems integrators and disrupting the software-as-a-service (SaaS) industry. Companies may now leverage AI tools and a few engineers to handle tasks previously managed by SaaS teams. Watch Cathie Wood in the August Fund Webinar to learn more.

ARK Funds

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Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

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We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens

Y Combinator

67,145 次观看 • 1 个月前

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The SaaSpocalypse narrative is starting to make less and less sense. Software companies like $PLTR, $NOW, and $CRM are getting punished because investors believe AI will replace SaaS. Jensen Huang disagrees. “Claude can write software.” That’s true. But Jensen argues that enterprises aren’t going to build their own software. They’re going to deploy AI agents that use software tools to get work done. “Agents won’t replace tools. Agents will use tools.” NVIDIA is already seeing this happen. According to Jensen, the company has deployed so many AI agents that tool usage is actually increasing. That’s the exact opposite of the SaaSpocalypse thesis.

Daniel

119,760 次观看 • 16 天前

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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

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Ambition is timeless. Tools are not. Today Nominal is announcing an $80M fundraise at a $1B valuation, led by Trae Stephens and delian at Founders Fund. Since our Series B 10 months ago: 7x revenue growth. 2x team growth. Hardware engineers are stuck between 1980s-era tools and .com software built to be replaced. We're fixing the data supply chain so the industrial sector can adopt AI and enter the next era of ambition. We’re also releasing Volume 1 of the Nominal Product Catalog: "Tools for Progress." We're grateful for continued participation from Sequoia Capital, General Catalyst, Lux Capital, Lightspeed, Redglass.vc, Avenir, and Haystack. All Systems Nominal.

Nominal

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2026 is the year of the robot, but developer tools are stuck in workflows similar to 2009 pre-GitHub software workflows. We’re changing that at Tnkr, building workflows so developers can, build, fork, mod/remix, and deploy more robots in the real world! Happy new year !

Ayo

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Launching AI Discovery And Communication DeepAgent discovers other AI agents and software tools on the fly and communicates with them to perform complex tasks. Here is how it works - - DeepAgent searches for other AI agents and tools - Finds the right tool for the job - Establishes contact using MCP and handles auth - Collaborates with the other tool to get the job done! - Remembers this tool for future colabs! Much like humans, it can create a team of AI agents or software tools to perform tasks. Here it is, learning about MindMaps, communicating with another server, and creating a Mindmap!!
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Launching AI Discovery And Communication DeepAgent discovers other AI agents and software tools on the fly and communicates with them to perform complex tasks. Here is how it works - - DeepAgent searches for other AI agents and tools - Finds the right tool for the job - Establishes contact using MCP and handles auth - Collaborates with the other tool to get the job done! - Remembers this tool for future colabs! Much like humans, it can create a team of AI agents or software tools to perform tasks. Here it is, learning about MindMaps, communicating with another server, and creating a Mindmap!!

Bindu Reddy

13,598 次观看 • 1 年前

Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.
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Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.

Bret Taylor

1,059,458 次观看 • 3 个月前

Infrastructure defines what scales. Electricity enabled industry. The internet enabled software. Now AI is moving toward systems that run continuously, across data, execution, and feedback. 💡At OptimAI, we’re building that infrastructure. A decentralized search layer for real-time data. A network of nodes powering continuous retrieval and validation. Agents that execute tasks directly on your device. This is not theoretical - we’re already seeing it in production, with millions of nodes and growing usage across the network. We’re putting together a short documentary to show how this shift is happening, and where it leads next. If you’re building, exploring, or just getting started - this is the layer to pay attention to. Welcome to OptimAI.
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Infrastructure defines what scales. Electricity enabled industry. The internet enabled software. Now AI is moving toward systems that run continuously, across data, execution, and feedback. 💡At OptimAI, we’re building that infrastructure. A decentralized search layer for real-time data. A network of nodes powering continuous retrieval and validation. Agents that execute tasks directly on your device. This is not theoretical - we’re already seeing it in production, with millions of nodes and growing usage across the network. We’re putting together a short documentary to show how this shift is happening, and where it leads next. If you’re building, exploring, or just getting started - this is the layer to pay attention to. Welcome to OptimAI.

OptimAI Network

17,426 次观看 • 2 个月前

General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.
5:06

General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.

Future Stacked

52,003 次观看 • 2 个月前

Sam is absolutely right. The moment AI agents get full access to a computer and the web, we cross a threshold from “tools we use” to “systems that act.” This is not just another upgrade. It is the beginning of autonomous productivity at scale. Research, execution, iteration, all happening in parallel while we focus on higher level thinking. The interface era is ending. The agent era is beginning.
0:40

Sam is absolutely right. The moment AI agents get full access to a computer and the web, we cross a threshold from “tools we use” to “systems that act.” This is not just another upgrade. It is the beginning of autonomous productivity at scale. Research, execution, iteration, all happening in parallel while we focus on higher level thinking. The interface era is ending. The agent era is beginning.

VraserX e/acc

11,102 次观看 • 4 个月前

I'm excited to share my talk on building Agentic RAG systems at last week's event with Arize AI and Google! 🥳 My talk covered: 1. The differences between Vanilla RAG and Agentic RAG 2. The agent ecosystem and how you can build agents today 3. How Weaviate AI Database is building agents with Generative Feedback Loops (GFLs) This snippet presents the multi-agent paradigm for Agentic RAG. I hope you find this talk interesting and would love to know what you think! The slide deck and full video links are below.
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I'm excited to share my talk on building Agentic RAG systems at last week's event with Arize AI and Google! 🥳 My talk covered: 1. The differences between Vanilla RAG and Agentic RAG 2. The agent ecosystem and how you can build agents today 3. How Weaviate AI Database is building agents with Generative Feedback Loops (GFLs) This snippet presents the multi-agent paradigm for Agentic RAG. I hope you find this talk interesting and would love to know what you think! The slide deck and full video links are below.

Erika Shorten

61,317 次观看 • 1 年前

Sat down with Kari Ann Briski, VP of Generative AI Software for Enterprise @ NVIDIA, to discuss NVIDIA’s Nemotron open models, how training data can be used for building agentic systems, and scaled AI enterprise adoption. Thank you to Kari NVIDIA AI Developer for taking the time!
10:17

Sat down with Kari Ann Briski, VP of Generative AI Software for Enterprise @ NVIDIA, to discuss NVIDIA’s Nemotron open models, how training data can be used for building agentic systems, and scaled AI enterprise adoption. Thank you to Kari NVIDIA AI Developer for taking the time!

amit

65,120 次观看 • 5 个月前

Parker Conrad on AI’s Role in B2B Software "The fact that these systems can read and the context windows are so large is much more powerful for B2B software than the fact that they can write. 'Generative AI' is a misnomer. It's the ability to ingest all of this information." Parker Conrad in conversation with Y Combinator's Garry Tan
3:11

Parker Conrad on AI’s Role in B2B Software "The fact that these systems can read and the context windows are so large is much more powerful for B2B software than the fact that they can write. 'Generative AI' is a misnomer. It's the ability to ingest all of this information." Parker Conrad in conversation with Y Combinator's Garry Tan

Overlap: Business & Tech

29,675 次观看 • 1 年前

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.
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I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.

Santiago

82,074 次观看 • 1 年前

This is awesome for those learning to build AI Agents: It's a challenge where you'll need to build an autonomous agent to survive in a world full of zombies. It's super fun, and it's 10x better than reading yet another tutorial. Here, you'll need to write code if you want to solve the problem. This challenge is sponsored by OutSystems, a platform for building and deploying enterprise-grade software. They have the Agent Workbench that you can use to build agentic systems. To join the challenge, you can visit:
3:05

This is awesome for those learning to build AI Agents: It's a challenge where you'll need to build an autonomous agent to survive in a world full of zombies. It's super fun, and it's 10x better than reading yet another tutorial. Here, you'll need to write code if you want to solve the problem. This challenge is sponsored by OutSystems, a platform for building and deploying enterprise-grade software. They have the Agent Workbench that you can use to build agentic systems. To join the challenge, you can visit:

Santiago

22,466 次观看 • 8 个月前