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Today we’re rolling out Zipline's March software update—1,100 changes to make deliveries faster, smarter, and more reliable. Key improvements include: • Deliveries in higher wind tolerance • Brighter droids that emit a cool blue glow at night • Customers can now order when stores are closed (Thread 🧵👇)

Keller Rinaudo Cliffton

15,161 subscribers

28,037 次观看 • 1 年前 •via X (Twitter)

健康养生科学技术新闻政治

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11 条评论

Keller Rinaudo Cliffton 的头像

Keller Rinaudo Cliffton1 年前

Other updates in this release included: • In-app waitlist sign-ups • Real-time capacity tracking • Tighter Zip-to-Zip deconfliction (simultaneous deliveries can now be made as close as 35m instead of 58m) • Smarter battery intelligence • More reliable line cutter - If the droid can't be properly stowed after a delivery, the Zip now safely unspools the tether and then flies away

Keller Rinaudo Cliffton 的头像

Keller Rinaudo Cliffton1 年前

Before rolling out any update, we put it through the wringer. This release was battle-tested with over 9,500 test deliveries and over 1,000 edge case flight tests.

Deals Finder 的头像

Deals Finder1 年前

Huge deals dropping daily, just like this one 🚨 Follow for more & turn on alerts.... they go fast!

Nick Foley 的头像

Nick Foley1 年前

Begging you all to do something creative with the fact that the aesthetics of your drone delivery are pure deus ex machina of a 1-stage high school play

Keller Rinaudo Cliffton 的头像

Keller Rinaudo Cliffton1 年前

Haha, it kind of is like that...

Michael 的头像

Michael1 年前

The future sees me taking delivery of items from my apartment balcony 👀 awesome work!

Mario Esposito 的头像

Mario Esposito1 年前

why @amazon is not using this awesome product is beyond me!

Ryan Bijoy 的头像

Ryan Bijoy1 年前

Doesn't the drone wobble too much? Adding a second string should improve balance, right? Have you tried it?

Keller Rinaudo Cliffton 的头像

Keller Rinaudo Cliffton1 年前

I agree. We're working on pitch stability.

algorusty — (Christ/acc➟✞) 的头像

algorusty — (Christ/acc➟✞)1 年前

Will a solution be made for apartments? Maybe a landing pad on the balcony rails?

Keller Rinaudo Cliffton 的头像

Keller Rinaudo Cliffton1 年前

We are working on something new on this front, will announce soon

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Jeff Bezos on how to build a business strategy “I very frequently get the question: ‘What’s going to change in the next 10 years?” And that is an interesting question… But I almost never get the question: ‘What’s not going to change in the next 10 years?’ And I submit to you that that second question is actually the more important of the two.” Jeff argues: “You can build a business strategy around the things that are stable in time. In our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery. They want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, ‘Jeff I love Amazon, I just wish the prices were a little higher.’ Or, ‘I love Amazon, I just wish you’d deliver a little slower.’ Impossible. And so we know the energy we put into these things today will still be paying dividends for our customers 10 years from now.” He gives AWS as another example. It’s impossible to imagine AWS customers asking for a less reliable or more expensive service. ”When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it… The big ideas in business are often very obvious, but it’s very hard to maintain a firm grasp of the obvious at all times. But if you can do that and continue to spin up those flywheels and put energy into those things, over time, you build a better service for your customers on the things that genuinely matter to them.” Video source: Amazon Web Services (2012)

Jeff Bezos on how to build a business strategy “I very frequently get the question: ‘What’s going to change in the next 10 years?” And that is an interesting question… But I almost never get the question: ‘What’s not going to change in the next 10 years?’ And I submit to you that that second question is actually the more important of the two.” Jeff argues: “You can build a business strategy around the things that are stable in time. In our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery. They want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, ‘Jeff I love Amazon, I just wish the prices were a little higher.’ Or, ‘I love Amazon, I just wish you’d deliver a little slower.’ Impossible. And so we know the energy we put into these things today will still be paying dividends for our customers 10 years from now.” He gives AWS as another example. It’s impossible to imagine AWS customers asking for a less reliable or more expensive service. ”When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it… The big ideas in business are often very obvious, but it’s very hard to maintain a firm grasp of the obvious at all times. But if you can do that and continue to spin up those flywheels and put energy into those things, over time, you build a better service for your customers on the things that genuinely matter to them.” Video source: Amazon Web Services (2012)

Startup Archive

22,420 次观看 • 3 个月前

Jeff Bezos on how to build a business strategy “I very frequently get the question: ‘What’s going to change in the next 10 years?” And that is an interesting question… But I almost never get the question: ‘What’s not going to change in the next 10 years?’ And I submit to you that that second question is actually the more important of the two.” Jeff argues: “You can build a business strategy around the things that are stable in time. In our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery. They want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, ‘Jeff I love Amazon, I just wish the prices were a little higher.’ Or, ‘I love Amazon, I just wish you’d deliver a little slower.’ Impossible. And so we know the energy we put into these things today will still be paying dividends for our customers 10 years from now.” He gives AWS as another example. It’s impossible to imagine AWS customers asking for a less reliable or more expensive service. ”When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it… The big ideas in business are often very obvious, but it’s very hard to maintain a firm grasp of the obvious at all times. But if you can do that and continue to spin up those flywheels and put energy into those things, over time, you build a better service for your customers on the things that genuinely matter to them.” Video source: Amazon Web Services (2012)

Jeff Bezos on how to build a business strategy “I very frequently get the question: ‘What’s going to change in the next 10 years?” And that is an interesting question… But I almost never get the question: ‘What’s not going to change in the next 10 years?’ And I submit to you that that second question is actually the more important of the two.” Jeff argues: “You can build a business strategy around the things that are stable in time. In our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery. They want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, ‘Jeff I love Amazon, I just wish the prices were a little higher.’ Or, ‘I love Amazon, I just wish you’d deliver a little slower.’ Impossible. And so we know the energy we put into these things today will still be paying dividends for our customers 10 years from now.” He gives AWS as another example. It’s impossible to imagine AWS customers asking for a less reliable or more expensive service. ”When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it… The big ideas in business are often very obvious, but it’s very hard to maintain a firm grasp of the obvious at all times. But if you can do that and continue to spin up those flywheels and put energy into those things, over time, you build a better service for your customers on the things that genuinely matter to them.” Video source: Amazon Web Services (2012)

Startup Archive

61,775 次观看 • 1 年前

Excited to announce UtilitySat, the world’s first multi-mission geostationary satellite, that we're launching at the end of this year. This is a first of its kind. And a new product line-- providing on-demand connectivity for disaster relief, bridge capacity, and other missions. We started Astranis to build something new: small communications satellites that provide dedicated broadband capacity for our customers. At the end of this year we’re launching four more of them on a dedicated Falcon 9 rocket, with many more to come after that. That launch of four satellites includes one satellite for Peru, two satellites for in-flight connectivity, and a fourth satellite that had been previously kept under wraps. Until now. Introducing UtilitySat, the Swiss Army Knife of satellites This is a new product— the world’s first multi-mission commercial GEO satellite, capable of conducting multiple fully-operational broadband connectivity missions. And it is just the first of many. We’ll plan to launch many UtilitySats in the years to come. UtilitySat can provide connectivity on standard Ku, Ka, and Q/V bands, and has the flexibility to dial in exact frequencies using Astranis’s proprietary ultra-wideband software-defined radio. It can also relocate dozens of times around the GEO belt over its lifetime. It does this using our unique on-board dual-propulsion architecture, which includes both a chemical monopropellant system and an electric ion thruster. A new mission every year, or every month When we first began development of UtilitySat almost 2 years ago, we had many different missions in mind. UtilitySat can serve as bridge capacity for a customer that is waiting for a dedicated satellite, as an on-orbit spare, or as extra, surge capacity that can be brought in to supplement the broadband service we’re providing to one of our customers. There are acute needs as well — a natural disaster can wipe out terrestrial connectivity over a huge geographic area. One of the top priorities for first responders and during disaster relief is reliable comms on the ground. With multiple UtilitySats on orbit, Astranis can bring in extra capacity on incredibly short notice. Capacity that is compatible with existing, low-cost GEO ground terminals. In initial conversations with customers for UtilitySat, we’ve seen huge demand — these customers often want to lease the entire capacity of the satellite once they learn what UtilitySat can offer. Customers need all the capacity they can get, and new capacity that can be deployed on short notice is a huge deal and a huge departure from traditional GEO satellites. We see a future where customers will be able to call up extra capacity on demand to augment their existing capacity needs, and we’re making that future a reality. US Government applications The first UtilitySat mission will be a commercial one, but we are seeing enormous demand from both from commercial companies and from our government customers. The US Government has unique needs — Combatant Commanders need to be able to task dedicated satellites to specific AORs at a moment’s notice — and surge communications would give them a new tool in their toolbox, helping them win even in a contested environment. And more broadly speaking our military leaders have said the one priority in national security space is to add resiliency to our fleets, using larger numbers of smaller, flexible, and maneuverable satellites so we’re not dependent on just a handful of huge satellites in GEO. UtilitySat shows that Astranis can do just that. Not traditional GEO satellites UtilitySat is only possible because of Astranis’s unique technology — including our proprietary software–defined radio. The flexibility of having on-board digital signal processing allows us to build a standardized satellite design, and move a lot of what used to be done in hardware, into software. UtilitySat uses the standard Astranis MicroGEO platform, adding more frequency bands and some new software capabilities to make maximum use of the available spectrum, no matter where the satellite is on orbit. Traditional geostationary satellites are designed to sit in one orbital slot for up to 20 years, with a set of frequency bands that is hardwired in at the factory. Their single mission must be predetermined many years before they are launched. Astranis does not build traditional GEO satellites. From day one we knew there had to be a better way, and we’re doing it.

Excited to announce UtilitySat, the world’s first multi-mission geostationary satellite, that we're launching at the end of this year. This is a first of its kind. And a new product line-- providing on-demand connectivity for disaster relief, bridge capacity, and other missions. We started Astranis to build something new: small communications satellites that provide dedicated broadband capacity for our customers. At the end of this year we’re launching four more of them on a dedicated Falcon 9 rocket, with many more to come after that. That launch of four satellites includes one satellite for Peru, two satellites for in-flight connectivity, and a fourth satellite that had been previously kept under wraps. Until now. Introducing UtilitySat, the Swiss Army Knife of satellites This is a new product— the world’s first multi-mission commercial GEO satellite, capable of conducting multiple fully-operational broadband connectivity missions. And it is just the first of many. We’ll plan to launch many UtilitySats in the years to come. UtilitySat can provide connectivity on standard Ku, Ka, and Q/V bands, and has the flexibility to dial in exact frequencies using Astranis’s proprietary ultra-wideband software-defined radio. It can also relocate dozens of times around the GEO belt over its lifetime. It does this using our unique on-board dual-propulsion architecture, which includes both a chemical monopropellant system and an electric ion thruster. A new mission every year, or every month When we first began development of UtilitySat almost 2 years ago, we had many different missions in mind. UtilitySat can serve as bridge capacity for a customer that is waiting for a dedicated satellite, as an on-orbit spare, or as extra, surge capacity that can be brought in to supplement the broadband service we’re providing to one of our customers. There are acute needs as well — a natural disaster can wipe out terrestrial connectivity over a huge geographic area. One of the top priorities for first responders and during disaster relief is reliable comms on the ground. With multiple UtilitySats on orbit, Astranis can bring in extra capacity on incredibly short notice. Capacity that is compatible with existing, low-cost GEO ground terminals. In initial conversations with customers for UtilitySat, we’ve seen huge demand — these customers often want to lease the entire capacity of the satellite once they learn what UtilitySat can offer. Customers need all the capacity they can get, and new capacity that can be deployed on short notice is a huge deal and a huge departure from traditional GEO satellites. We see a future where customers will be able to call up extra capacity on demand to augment their existing capacity needs, and we’re making that future a reality. US Government applications The first UtilitySat mission will be a commercial one, but we are seeing enormous demand from both from commercial companies and from our government customers. The US Government has unique needs — Combatant Commanders need to be able to task dedicated satellites to specific AORs at a moment’s notice — and surge communications would give them a new tool in their toolbox, helping them win even in a contested environment. And more broadly speaking our military leaders have said the one priority in national security space is to add resiliency to our fleets, using larger numbers of smaller, flexible, and maneuverable satellites so we’re not dependent on just a handful of huge satellites in GEO. UtilitySat shows that Astranis can do just that. Not traditional GEO satellites UtilitySat is only possible because of Astranis’s unique technology — including our proprietary software–defined radio. The flexibility of having on-board digital signal processing allows us to build a standardized satellite design, and move a lot of what used to be done in hardware, into software. UtilitySat uses the standard Astranis MicroGEO platform, adding more frequency bands and some new software capabilities to make maximum use of the available spectrum, no matter where the satellite is on orbit. Traditional geostationary satellites are designed to sit in one orbital slot for up to 20 years, with a set of frequency bands that is hardwired in at the factory. Their single mission must be predetermined many years before they are launched. Astranis does not build traditional GEO satellites. From day one we knew there had to be a better way, and we’re doing it.

John Gedmark

122,069 次观看 • 2 年前

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.

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.

Aaron Levie

91,863 次观看 • 10 个月前

At HumanLayer, we’re on a mission to solve the AI slop code problem. In 2025 we open-sourced our Research, Plan, Implement framework, now deployed inside fortune 500s like Block and Uber - places where shipping slop is just not an option And that was just the beginning. Today, we’re opening access to HumanLayer - an Agentic IDE, collaboration platform, and building blocks for your software factory. HumanLayer enables engineers solving hard problems in complex codebases to: > move 2-3x faster across the entire SDLC (not just coding) > maintain rigorous standards for system architecture and program design Hundreds of engineers at companies of all sizes are already using HumanLayer to ship fast without sacrificing quality. I'm excited to invite you to try humanlayer today at and I'm even more excited to see what you build. Kyle Mistele 🏴‍☠️ and I are deeply grateful to our team, our customers who give us so much incredible energy and feedback, our investors who have always been in our corner, and our friends and family who have supported us along this crazy journey if you're a staff or principal engineer trying to make AI coding work at scale for your team, we'd love to hear from you as swyx likes to say - let's make this the year of no more slop

At HumanLayer, we’re on a mission to solve the AI slop code problem. In 2025 we open-sourced our Research, Plan, Implement framework, now deployed inside fortune 500s like Block and Uber - places where shipping slop is just not an option And that was just the beginning. Today, we’re opening access to HumanLayer - an Agentic IDE, collaboration platform, and building blocks for your software factory. HumanLayer enables engineers solving hard problems in complex codebases to: > move 2-3x faster across the entire SDLC (not just coding) > maintain rigorous standards for system architecture and program design Hundreds of engineers at companies of all sizes are already using HumanLayer to ship fast without sacrificing quality. I'm excited to invite you to try humanlayer today at and I'm even more excited to see what you build. Kyle Mistele 🏴‍☠️ and I are deeply grateful to our team, our customers who give us so much incredible energy and feedback, our investors who have always been in our corner, and our friends and family who have supported us along this crazy journey if you're a staff or principal engineer trying to make AI coding work at scale for your team, we'd love to hear from you as swyx likes to say - let's make this the year of no more slop

dex

343,493 次观看 • 27 天前

Marc Andreessen: “I’m always urging founders to raise prices, raise prices, raise prices.” “We spend a lot of time working with our companies on pricing,” a16z co-founder Marc Andreessen explains. “It’s really this magical art and science that a lot of companies don’t take seriously enough.” Marc continues: “A core principle of pricing is that you don’t want to price by cost if you can avoid it. You want to price by value. Especially when you’re selling to businesses, you want to price as a percentage of the business value you’re creating.” He gives the example of building an AI that can do the job of a programmer, a lawyer, or a radiologist: “Can you price by value and get a percentage of what otherwise would’ve literally been a person? Or equivalently can you price by marginal productivity? If you can take a human doctor and make them much more productive because you give them AI, can you price as a percentage of the productivity uplift?” Marc argues that high prices are under-appreciated by founders: “The naive view on pricing is the lower the pricing, the better it is for the customer. The more sophisticated way of looking at it is that higher prices are often good for the customer because the higher price means the vendor can make the product better, faster. Companies with higher prices and higher margins can actually invest more in R&D and make the product better. Most people who buy things aren’t just looking for the cheapest price. They want something that’s going to work really well.” Marc also emphasizes this point in an interview in Elad Gil’s High Growth Handbook: “What I hear from companies is, ‘Oh, we have an awesome moat, and we’re still going to price our product cheap, because we think that’s somehow going to maximize our business.’ I’m always urging founders to raise prices, raise prices, raise prices. I’m always urging founders to raise prices, raise prices, raise prices. First of all, raising prices is a great way to flesh out whether you actually do have a moat. If you do have a moat, the customers will still buy, because they have to. The definition of a moat is the ability to charge more. And so number one, it’s just a good way to flesh out that topic and really expose it to sunlight. And then number two, companies that charge more can better fund both their distribution efforts and their ongoing R&D efforts. Charging more is a key lever to be able to grow. And the companies that charge more therefore tend to grow faster. That’s counterintuitive to a lot of engineers. A lot of engineers think there’s a one-dimensional relationship between price and value. They have this mental model of commerce like they’re selling rice or something. It’s like, “My product is magical and nobody can replicate it, and I need to price it like it’s a commodity.” No, you don’t. In fact, quite the opposite. If you price it high, then you can fund a much more expensive sales and marketing effort, which means you’re much more likely to win the market, which means you’re much more likely to be able afford to do all the R&D and acquisitions you’re going to want to do. And so we always try to snap people into a two-dimensional mindset, where higher prices equals faster growth.” Video source: a16z (2026)

Marc Andreessen: “I’m always urging founders to raise prices, raise prices, raise prices.” “We spend a lot of time working with our companies on pricing,” a16z co-founder Marc Andreessen explains. “It’s really this magical art and science that a lot of companies don’t take seriously enough.” Marc continues: “A core principle of pricing is that you don’t want to price by cost if you can avoid it. You want to price by value. Especially when you’re selling to businesses, you want to price as a percentage of the business value you’re creating.” He gives the example of building an AI that can do the job of a programmer, a lawyer, or a radiologist: “Can you price by value and get a percentage of what otherwise would’ve literally been a person? Or equivalently can you price by marginal productivity? If you can take a human doctor and make them much more productive because you give them AI, can you price as a percentage of the productivity uplift?” Marc argues that high prices are under-appreciated by founders: “The naive view on pricing is the lower the pricing, the better it is for the customer. The more sophisticated way of looking at it is that higher prices are often good for the customer because the higher price means the vendor can make the product better, faster. Companies with higher prices and higher margins can actually invest more in R&D and make the product better. Most people who buy things aren’t just looking for the cheapest price. They want something that’s going to work really well.” Marc also emphasizes this point in an interview in Elad Gil’s High Growth Handbook: “What I hear from companies is, ‘Oh, we have an awesome moat, and we’re still going to price our product cheap, because we think that’s somehow going to maximize our business.’ I’m always urging founders to raise prices, raise prices, raise prices. I’m always urging founders to raise prices, raise prices, raise prices. First of all, raising prices is a great way to flesh out whether you actually do have a moat. If you do have a moat, the customers will still buy, because they have to. The definition of a moat is the ability to charge more. And so number one, it’s just a good way to flesh out that topic and really expose it to sunlight. And then number two, companies that charge more can better fund both their distribution efforts and their ongoing R&D efforts. Charging more is a key lever to be able to grow. And the companies that charge more therefore tend to grow faster. That’s counterintuitive to a lot of engineers. A lot of engineers think there’s a one-dimensional relationship between price and value. They have this mental model of commerce like they’re selling rice or something. It’s like, “My product is magical and nobody can replicate it, and I need to price it like it’s a commodity.” No, you don’t. In fact, quite the opposite. If you price it high, then you can fund a much more expensive sales and marketing effort, which means you’re much more likely to win the market, which means you’re much more likely to be able afford to do all the R&D and acquisitions you’re going to want to do. And so we always try to snap people into a two-dimensional mindset, where higher prices equals faster growth.” Video source: a16z (2026)

Startup Archive

422,712 次观看 • 6 个月前

Snow + ice just exposed how fragile our systems still are. At the peak of this storm, more than 1,000,000 homes and businesses lost power across multiple states. As of early Wednesday (Jan 28, 2026), ~400,000+ customers were still without electricity in the hardest-hit areas. Add dangerous cold (down to about -4°F in parts of Texas) plus major travel disruption (thousands of flight cancellations), and you get a direct hit to fuel access, food deliveries, and basic safety. This is exactly why the energy grid + supply chain need transformation: distributed resilience, faster restoration, and logistics that don’t collapse when power fails. NASDAQ: $NXXT matters here. Solutions like EzFill’s mobile fuel delivery can help keep generators, fleets, and critical operations fueled (where service is available), especially when gas stations can’t pump due to outages. Please share this and check on neighbors—and if you’re using a generator, use it safely (CO risk is real). Not financial advice—just reality in a crisis.

Snow + ice just exposed how fragile our systems still are. At the peak of this storm, more than 1,000,000 homes and businesses lost power across multiple states. As of early Wednesday (Jan 28, 2026), ~400,000+ customers were still without electricity in the hardest-hit areas. Add dangerous cold (down to about -4°F in parts of Texas) plus major travel disruption (thousands of flight cancellations), and you get a direct hit to fuel access, food deliveries, and basic safety. This is exactly why the energy grid + supply chain need transformation: distributed resilience, faster restoration, and logistics that don’t collapse when power fails. NASDAQ: $NXXT matters here. Solutions like EzFill’s mobile fuel delivery can help keep generators, fleets, and critical operations fueled (where service is available), especially when gas stations can’t pump due to outages. Please share this and check on neighbors—and if you’re using a generator, use it safely (CO risk is real). Not financial advice—just reality in a crisis.

Victor Renard

3,996,049 次观看 • 5 个月前

Debugging agents shouldn’t feel like detective work. Today, we’re excited to release two new AI agent interfaces that make agent observability & evaluations even more effective. 🔎 Timeline View – See execution flow and bottlenecks at a glance. No more guessing where your agent gets stuck. 💬 Conversation View – Experience exactly what your users see. Debug from the user's perspective, not just the system's. Combined with last week's Graph View, you now have three complementary ways to debug your agents: → Graph: Visualize decision paths and tool usage → Timeline: Spot performance bottlenecks instantly → Conversation: See the user experience end-to-end AI evaluations + observability are crucial to building reliable AI. These interfaces make it simpler to identify blockers and improve your agents faster. See all three views in action, and try it free with the link below 👇

Debugging agents shouldn’t feel like detective work. Today, we’re excited to release two new AI agent interfaces that make agent observability & evaluations even more effective. 🔎 Timeline View – See execution flow and bottlenecks at a glance. No more guessing where your agent gets stuck. 💬 Conversation View – Experience exactly what your users see. Debug from the user's perspective, not just the system's. Combined with last week's Graph View, you now have three complementary ways to debug your agents: → Graph: Visualize decision paths and tool usage → Timeline: Spot performance bottlenecks instantly → Conversation: See the user experience end-to-end AI evaluations + observability are crucial to building reliable AI. These interfaces make it simpler to identify blockers and improve your agents faster. See all three views in action, and try it free with the link below 👇

Galileo, now part of Cisco

499,475 次观看 • 1 年前

[Trans] WIN WITH KAWS HOLIDAY (1) 🎤: Let’s talk about your #souri macarons that have been selling out every single day! 🐰: Thank you to everyone for your interest. At the stores, we’ve been trying our best to manage things because, honestly, we weren’t prepared for this level of demand and didn’t expect it. Both our front-of-house and back-of-house teams have been working really hard together. 🎤: It’s become a market sensation now. 🐰: Yes, we can’t produce enough in time. The orders came in unexpectedly, and we didn’t forecast it. I really feel for the production team because they’ve had to work late nights. We truly want everyone to get a chance to try them.🩷 🎤: So what are you doing to meet the demand? 🐰: We’re already ramping up production, but it’s not something that can be done instantly. There are processes involved, and we also have to order more ingredients. Some of those take months to arrive. 🎤: Did you ever think it would become this big? 🐰: Never. All of us have been working at our fullest from the beginning to make the best product possible, something that makes people happy when they eat it. When people enjoy it and spread the word, that’s the biggest reward for us. 🥹 🎤: What do you say to customers who complain about the wait? 🐰: Our inbox is overflowing right now. I just got off a call with the team that they can’t keep up with the messages. We’re adding overtime to get through every message. Usually, we work in shifts, but we’ve had to call in extra help. We’re also trying to get orders out as fast as we can. 🎤: No one’s about to pass out from the workload, right? 🐰: We’re close! 😅 #CentralEmbassyXWinMetawin #winmetawin

[Trans] WIN WITH KAWS HOLIDAY (1) 🎤: Let’s talk about your #souri macarons that have been selling out every single day! 🐰: Thank you to everyone for your interest. At the stores, we’ve been trying our best to manage things because, honestly, we weren’t prepared for this level of demand and didn’t expect it. Both our front-of-house and back-of-house teams have been working really hard together. 🎤: It’s become a market sensation now. 🐰: Yes, we can’t produce enough in time. The orders came in unexpectedly, and we didn’t forecast it. I really feel for the production team because they’ve had to work late nights. We truly want everyone to get a chance to try them.🩷 🎤: So what are you doing to meet the demand? 🐰: We’re already ramping up production, but it’s not something that can be done instantly. There are processes involved, and we also have to order more ingredients. Some of those take months to arrive. 🎤: Did you ever think it would become this big? 🐰: Never. All of us have been working at our fullest from the beginning to make the best product possible, something that makes people happy when they eat it. When people enjoy it and spread the word, that’s the biggest reward for us. 🥹 🎤: What do you say to customers who complain about the wait? 🐰: Our inbox is overflowing right now. I just got off a call with the team that they can’t keep up with the messages. We’re adding overtime to get through every message. Usually, we work in shifts, but we’ve had to call in extra help. We’re also trying to get orders out as fast as we can. 🎤: No one’s about to pass out from the workload, right? 🐰: We’re close! 😅 #CentralEmbassyXWinMetawin #winmetawin

◡̈ ✿〜*:.｡. ꕤ M a R y ꕤ*･.｡.*･*✿.

30,470 次观看 • 1 年前

Marc Benioff just exposed the biggest hypocrisy in the AI boom. The companies building the AI that’s supposed to kill software are some of Salesforce’s largest customers. Benioff: “The AI companies love our products and they can’t buy enough of them. They’re some of our largest customers now: Anthropic, OpenAI, Google, Amazon, you name it.” Let that land. The most advanced AI labs on earth. The companies with more engineering talent and compute than anyone. The ones building the technology that analysts say will make traditional software obsolete. Still buying traditional software. At scale. Benioff: “No one has a company that’s running entirely on a large language model because it’s not real.” Not because they haven’t tried. Because an LLM is not a foundation. It’s a feature. Benioff: “Yeah, Minority Report, I watched the movie. Great guys, fantastic. But I’m in the present-moment reality right now. We’re living in this world. This is 2026.” The analysts writing reports about fully autonomous AI companies have never had to run one. Benioff is running one of the largest enterprise software companies on earth. The gap between those two perspectives is where billions of dollars are being misallocated. Benioff: “How are we doing our financials, our HR, our customer information? How are we doing all of these aspects of our business?” A neural network that hallucinates cannot execute a financial transaction that has to be right every single time. Cannot secure customer data with zero tolerance for error. Cannot provide the determinism that every real business runs on. Benioff: “We need the determinism, and the programmability, and the security, and the sharing.” AI doesn’t replace those requirements. It sits on top of them. Benioff: “I think the software industry is going to be bigger and broader and do more this year than ever before.” The future isn’t AI replacing software. It’s AI making software exponentially more powerful. The smartest people building the future already know this. They’re the ones still buying the software.

Marc Benioff just exposed the biggest hypocrisy in the AI boom. The companies building the AI that’s supposed to kill software are some of Salesforce’s largest customers. Benioff: “The AI companies love our products and they can’t buy enough of them. They’re some of our largest customers now: Anthropic, OpenAI, Google, Amazon, you name it.” Let that land. The most advanced AI labs on earth. The companies with more engineering talent and compute than anyone. The ones building the technology that analysts say will make traditional software obsolete. Still buying traditional software. At scale. Benioff: “No one has a company that’s running entirely on a large language model because it’s not real.” Not because they haven’t tried. Because an LLM is not a foundation. It’s a feature. Benioff: “Yeah, Minority Report, I watched the movie. Great guys, fantastic. But I’m in the present-moment reality right now. We’re living in this world. This is 2026.” The analysts writing reports about fully autonomous AI companies have never had to run one. Benioff is running one of the largest enterprise software companies on earth. The gap between those two perspectives is where billions of dollars are being misallocated. Benioff: “How are we doing our financials, our HR, our customer information? How are we doing all of these aspects of our business?” A neural network that hallucinates cannot execute a financial transaction that has to be right every single time. Cannot secure customer data with zero tolerance for error. Cannot provide the determinism that every real business runs on. Benioff: “We need the determinism, and the programmability, and the security, and the sharing.” AI doesn’t replace those requirements. It sits on top of them. Benioff: “I think the software industry is going to be bigger and broader and do more this year than ever before.” The future isn’t AI replacing software. It’s AI making software exponentially more powerful. The smartest people building the future already know this. They’re the ones still buying the software.

Dustin

203,575 次观看 • 4 个月前