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Agents are a wild west right now. Unstandardized, complex setups, huge vulnerabilities, and not institutional-grade. The Lucid Agent will be: > 1 click deployal > highly encrypted > Multi-Model (kimi, GPT, etc) > Cloud/ DePin compute enabled. Bye agents.

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Lucid - Internet of AI (IoAI)

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11,147 Aufrufe • vor 7 Monaten •via X (Twitter)

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199,793 Aufrufe • vor 5 Monaten

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Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!

Avi Chawla

110,057 Aufrufe • vor 4 Monaten

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JUMPERZ

34,181 Aufrufe • vor 7 Monaten

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The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 Aufrufe • vor 8 Monaten

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1:29

Stripe's Will Gaybrick says AI agents will navigate the internet like hummingbirds, and that's what will make microtransactions work: "If you're trying to sell an article, you're always gonna be squeezed between the subscriber business model and the free business model... I think that was probably true in the past." "As you give agents more complex tasks, you want them to be these little hummingbirds, going around the internet, just slurping up a little data here... doing a little compute over here... You don't want the individual human to have to create accounts everywhere." "I think microtransactions will just be necessary for that economy to exist, the agentic economy." "On the flip side, they're now eminently possible because of stablecoins... If you just give an agent a budget, they can easily take dollars, move into stables, and find a way to check out. They don't mind the back and forth." Will Gaybrick Stripe

a16z

75,363 Aufrufe • vor 1 Monat

What happens when there are more agents than eyeballs browsing the internet? How will the economics of the internet be reinvented? Parag Agrawal thinks Shapley values may hold the answer. Parag built Twitter over a decade, eventually becoming CEO and selling the company to Elon. He's spent the last three years building Parallel Web Systems, a search engine built for agents instead of humans. His core argument: 1) human click data is a bug. Agents aren't just a new technology, they're a distinct customer – and the feedback loop that made Google great is the wrong signal for the thing actually doing the work; 2) the ad-funded web assumed scarce human attention. If agents show up instead of eyeballs, the business model underneath the internet has to be rebuilt, or good content stops being published. The conversation covers: — why he shipped a search agent before a search engine, and how that let him grow the index incrementally instead of buying a full web crawl up front — the billion-to-billion matching problem: pull the right 1,000 tokens out of a trillion web pages, and your agent uses under half the tokens — going from a 3-second compute budget to 200 milliseconds — why he doesn't think Parallel is a neo-lab: "our output is a complement to a model" — the Google Cloud deal — on GCP, your grounding options are now Google Search or Parallel Search — reinventing the economics of the internet, Shapley values as a payment rail for publishers, and why the company was originally incorporated as Shapley Inc — why routing 2-10% of inference spend to web data would dwarf every content business outside the walled gardens — the web going from pull to push: "call me if this happens" 00:00 Introduction 03:25 What Is Web Search 05:17 Why Start a New Index 07:52 Search Agents First 10:17 Not a Neolab 13:14 Agents vs Google Search 19:38 Inside the Search Stack 28:59 Search Multipliers With Agents 30:21 Meeting Prep Agent Workflows 31:46 Quality Cost Latency And Turbo 32:42 Are Agents Overtaking Humans 34:28 Ads Model Meets Agent Web 37:20 New Incentives For Content 40:48 Shapley Values Attribution 47:46 Parallel Web And Future Vision Hosted with my very unwilling co-host Andrew Reed and Sequoia Capital
55:18

What happens when there are more agents than eyeballs browsing the internet? How will the economics of the internet be reinvented? Parag Agrawal thinks Shapley values may hold the answer. Parag built Twitter over a decade, eventually becoming CEO and selling the company to Elon. He's spent the last three years building Parallel Web Systems, a search engine built for agents instead of humans. His core argument: 1) human click data is a bug. Agents aren't just a new technology, they're a distinct customer – and the feedback loop that made Google great is the wrong signal for the thing actually doing the work; 2) the ad-funded web assumed scarce human attention. If agents show up instead of eyeballs, the business model underneath the internet has to be rebuilt, or good content stops being published. The conversation covers: — why he shipped a search agent before a search engine, and how that let him grow the index incrementally instead of buying a full web crawl up front — the billion-to-billion matching problem: pull the right 1,000 tokens out of a trillion web pages, and your agent uses under half the tokens — going from a 3-second compute budget to 200 milliseconds — why he doesn't think Parallel is a neo-lab: "our output is a complement to a model" — the Google Cloud deal — on GCP, your grounding options are now Google Search or Parallel Search — reinventing the economics of the internet, Shapley values as a payment rail for publishers, and why the company was originally incorporated as Shapley Inc — why routing 2-10% of inference spend to web data would dwarf every content business outside the walled gardens — the web going from pull to push: "call me if this happens" 00:00 Introduction 03:25 What Is Web Search 05:17 Why Start a New Index 07:52 Search Agents First 10:17 Not a Neolab 13:14 Agents vs Google Search 19:38 Inside the Search Stack 28:59 Search Multipliers With Agents 30:21 Meeting Prep Agent Workflows 31:46 Quality Cost Latency And Turbo 32:42 Are Agents Overtaking Humans 34:28 Ads Model Meets Agent Web 37:20 New Incentives For Content 40:48 Shapley Values Attribution 47:46 Parallel Web And Future Vision Hosted with my very unwilling co-host Andrew Reed and Sequoia Capital

Sonya Huang 🐥

127,791 Aufrufe • vor 25 Tagen

EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod The Startup Ideas Podcast (SIP) 🧃. Thanks to Vinny for jumping on and clearly explaining jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch Curious what you think
38:43

EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod The Startup Ideas Podcast (SIP) 🧃. Thanks to Vinny for jumping on and clearly explaining jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch Curious what you think

GREG ISENBERG

558,824 Aufrufe • vor 1 Monat

Jensen Huang says the next internet is not for humans. It is for agents. "AI has become agentic, meaning that it can actually do work by itself." "One agent can communicate with another agent and say, 'I have some work to do. Let's team up together and let's do some work.'" "Inside our company... we have hundreds of thousands of agents probably running around right now that are doing work and they're talking to each other and they're solving problems." "All guardrailed, all sandboxed... but they're all working with each other." Then the part most people are not ready for: "The internet that we use today for a billion people will likely mostly be several billion, call it a hundred billion agents working around the clock." Companies talking to companies. Employee agents talking to employee agents. Self-driving cars, robots, manufacturing systems, buildings. "The world is going to be this layer of computing that's going to cocoon the earth, and it's going to be generating intelligence all the time."
1:38

Jensen Huang says the next internet is not for humans. It is for agents. "AI has become agentic, meaning that it can actually do work by itself." "One agent can communicate with another agent and say, 'I have some work to do. Let's team up together and let's do some work.'" "Inside our company... we have hundreds of thousands of agents probably running around right now that are doing work and they're talking to each other and they're solving problems." "All guardrailed, all sandboxed... but they're all working with each other." Then the part most people are not ready for: "The internet that we use today for a billion people will likely mostly be several billion, call it a hundred billion agents working around the clock." Companies talking to companies. Employee agents talking to employee agents. Self-driving cars, robots, manufacturing systems, buildings. "The world is going to be this layer of computing that's going to cocoon the earth, and it's going to be generating intelligence all the time."

Karl Mehta

17,974 Aufrufe • vor 2 Monaten

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.
0:43

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Aaron Levie

17,543 Aufrufe • vor 5 Monaten