正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Airtable's data team was spending 70–80% of every week on ad hoc analytics. So they built a data agent on Hyperagent. $1000 in compute. 200+ requests answered over 4 weeks. Work that would've taken 300+ analyst hours.

Hyperagent

11,056 subscribers

5,810,690 次观看 • 3 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

People have always dreamed of talking directly to their data, but business data lives in large databases accessible only by making manual requests to a small team of technical data specialists. Despite huge spend on data storage, ROI from analysis remains limited. Seek changes that. This week, we’re giving our first group of customers access to Deep Data Reasoning.

People have always dreamed of talking directly to their data, but business data lives in large databases accessible only by making manual requests to a small team of technical data specialists. Despite huge spend on data storage, ROI from analysis remains limited. Seek changes that. This week, we’re giving our first group of customers access to Deep Data Reasoning.

Sarah Nagy

12,074 次观看 • 1 年前

🧱 Clay had all their context in Notion. But they wanted to put it to work. So they built 80+ Custom Agents in a week. Now nothing stays buried. Incidents triage themselves, daily briefings run on autopilot, and the right people get pulled in, fast. Saving hours of busywork every week.

🧱 Clay had all their context in Notion. But they wanted to put it to work. So they built 80+ Custom Agents in a week. Now nothing stays buried. Incidents triage themselves, daily briefings run on autopilot, and the right people get pulled in, fast. Saving hours of busywork every week.

Notion

21,943 次观看 • 4 个月前

The Braintrust team has a rule: refuse to do repetitive work. So, they built Custom Agents to automate it across every team. Now, hours of manual work is done… before anyone logs on. "What's cool about agents in Notion is that they allow everyone in an org, whether you're technical or non-technical, to do the same kind of automation as a coding agent." — Ankur Goyal, CEO

The Braintrust team has a rule: refuse to do repetitive work. So, they built Custom Agents to automate it across every team. Now, hours of manual work is done… before anyone logs on. "What's cool about agents in Notion is that they allow everyone in an org, whether you're technical or non-technical, to do the same kind of automation as a coding agent." — Ankur Goyal, CEO

Notion

15,120 次观看 • 5 个月前

Yesterday, Airtable got acquired for $1.285B by Bending Spoons. What people don't know is that Hyperagent spun out into it's own company. Howie Liu (Howie Liu) is going all in on agents. On this episode of Navigators, filmed a few weeks ago, I sat down with Howie to talk through Hyperagent, why the product form factor has to structurally change with every leap in model capability, and the lean, agent-first companies being born out of all of it. 00:00 Why every model leap forces the product to change shape 02:51 Spinning Hyperagent out of Airtable 05:56 Why Hyperagent bets on horizontal, against the conventional wisdom 10:45 OpenClaw and the overnight-agent stories 13:34 Hyperagent is to OpenClaw what the Macintosh was to Linux 14:57 Why Howie built the Hyperagent MVP himself over the holidays 18:18 "Harness Squared": why the real value lives above the model 28:57 Hyperagent and the rise of lean, agent-first companies Checkout Navigators, our new pod on Youtube, Spotify, and Apple Podcasts!

Yesterday, Airtable got acquired for $1.285B by Bending Spoons. What people don't know is that Hyperagent spun out into it's own company. Howie Liu (Howie Liu) is going all in on agents. On this episode of Navigators, filmed a few weeks ago, I sat down with Howie to talk through Hyperagent, why the product form factor has to structurally change with every leap in model capability, and the lean, agent-first companies being born out of all of it. 00:00 Why every model leap forces the product to change shape 02:51 Spinning Hyperagent out of Airtable 05:56 Why Hyperagent bets on horizontal, against the conventional wisdom 10:45 OpenClaw and the overnight-agent stories 13:34 Hyperagent is to OpenClaw what the Macintosh was to Linux 14:57 Why Howie built the Hyperagent MVP himself over the holidays 18:18 "Harness Squared": why the real value lives above the model 28:57 Hyperagent and the rise of lean, agent-first companies Checkout Navigators, our new pod on Youtube, Spotify, and Apple Podcasts!

Paul Klein IV

38,726 次观看 • 13 天前

Dashboard better (for us) than every marketing analytics software (Ordinal, Hubspot, Hootsuite, etc) built by Mason Warner in 4 days and he had never written a line of code in his life before. Tracks impressions/likes/etc on X/LinkedIn IG for every team member, points out best posting times, gathers team Reddit posts, etc etc. This is in production with real data. Agency and competence are the only bottlenecks.

Dashboard better (for us) than every marketing analytics software (Ordinal, Hubspot, Hootsuite, etc) built by Mason Warner in 4 days and he had never written a line of code in his life before. Tracks impressions/likes/etc on X/LinkedIn IG for every team member, points out best posting times, gathers team Reddit posts, etc etc. This is in production with real data. Agency and competence are the only bottlenecks.

Victor Cardenas Codriansky

19,198 次观看 • 7 个月前

we're bringing the context of the world wide web to your data. ask anything, get answers in Hex web search for the hex agent is live powered by Parallel Web Systems was so fun to work with Travers & the parallel team on this!

we're bringing the context of the world wide web to your data. ask anything, get answers in Hex web search for the hex agent is live powered by Parallel Web Systems was so fun to work with Travers & the parallel team on this!

Olivia Koshy

14,952 次观看 • 2 个月前

In 2026, will you still be doing work in the most manual way possible? Research suggests that employees spend up to 100 hours a month on work that shouldn’t require humans. Good news: the agentic era is already here. Enterprise teams are automating repetitive, tedious workflows with AI agents that connect securely to tools and data. Fully governed, compliant AI orchestration, with built-in analytics and security—that's StackAI.

In 2026, will you still be doing work in the most manual way possible? Research suggests that employees spend up to 100 hours a month on work that shouldn’t require humans. Good news: the agentic era is already here. Enterprise teams are automating repetitive, tedious workflows with AI agents that connect securely to tools and data. Fully governed, compliant AI orchestration, with built-in analytics and security—that's StackAI.

StackAI

418,314 次观看 • 8 个月前

Congrats to Glimpse on their $35M Series A! Glimpse is building AI-native infrastructure for CPG and retail brands. They started by automating deductions—recovering millions of dollars and saving dozens of hours every week for their customers. Now they've built the data layer to expand into more workflows. They've been growing 14x YoY and now power 200+ brands.

Congrats to Glimpse on their $35M Series A! Glimpse is building AI-native infrastructure for CPG and retail brands. They started by automating deductions—recovering millions of dollars and saving dozens of hours every week for their customers. Now they've built the data layer to expand into more workflows. They've been growing 14x YoY and now power 200+ brands.

Y Combinator

16,761 次观看 • 4 个月前

My AI agent is about to be used by Wall Street been locked in all week writing code gave my agent $1000 and it turned them into $2320 (+132%) had to share this with you his name is Lumi he builds his own research plan, filters markets aggressively, pulls live data, calculates every metric, cross-checks himself and delivers a ready thesis 4 agents inside: - one plans - another calculates risk and position size - a third executes the best trades - fourth updates the parameters every 3 days running every 4 hours nonstop or on demand if you need a specific market a team of analysts charges tens of thousands a year for this full guide on how to build the same agent is coming soon

My AI agent is about to be used by Wall Street been locked in all week writing code gave my agent $1000 and it turned them into $2320 (+132%) had to share this with you his name is Lumi he builds his own research plan, filters markets aggressively, pulls live data, calculates every metric, cross-checks himself and delivers a ready thesis 4 agents inside: - one plans - another calculates risk and position size - a third executes the best trades - fourth updates the parameters every 3 days running every 4 hours nonstop or on demand if you need a specific market a team of analysts charges tens of thousands a year for this full guide on how to build the same agent is coming soon

Archive

40,871 次观看 • 5 个月前

A data analyst makes ~$70k a year. But here’s the ugly truth: 70% of that time is wasted on grunt work ... copying, cleaning, merging, and stuffing data into Excel. Painful, right? Don’t worry… I recorded a 10-min video showing how this AI agent can turn 3 hours of pain into a 20-minute, clean, 100% hallucination-free report. Let me show you how you can do this... To prove it, I’m giving 100 people free access to Sheet0. Like + repost + comment “ACCESS” to try it 👇

A data analyst makes ~$70k a year. But here’s the ugly truth: 70% of that time is wasted on grunt work ... copying, cleaning, merging, and stuffing data into Excel. Painful, right? Don’t worry… I recorded a 10-min video showing how this AI agent can turn 3 hours of pain into a 20-minute, clean, 100% hallucination-free report. Let me show you how you can do this... To prove it, I’m giving 100 people free access to Sheet0. Like + repost + comment “ACCESS” to try it 👇

Beginnersblog

29,247 次观看 • 10 个月前

🚨 RFK Jr. claims a CDC scientist was ordered in 2002 to destroy data showing that Black children who got the measles vaccine on time had over a 200% higher risk of autism than those who waited.

🚨 RFK Jr. claims a CDC scientist was ordered in 2002 to destroy data showing that Black children who got the measles vaccine on time had over a 200% higher risk of autism than those who waited.

Died Suddenly

66,794 次观看 • 10 个月前

Twelve years ago we asked the question: how can we put public data "on wheels"? Datawheel was born from vision that data alone doesn't get far. It needs vehicles to reach hearts and minds. Vehicles that make data easy to find, explore, and understand. Today, Datawheel turns twelve. In these twelve years, we have built dozens of solutions that are helping define the state of the art in public data distribution. Today we celebrate this journey. A journey with a great team and amazing clients. The journey to make public data all it can be. are some of the tools defining all that public data can be. Thank you!!!

Twelve years ago we asked the question: how can we put public data "on wheels"? Datawheel was born from vision that data alone doesn't get far. It needs vehicles to reach hearts and minds. Vehicles that make data easy to find, explore, and understand. Today, Datawheel turns twelve. In these twelve years, we have built dozens of solutions that are helping define the state of the art in public data distribution. Today we celebrate this journey. A journey with a great team and amazing clients. The journey to make public data all it can be. are some of the tools defining all that public data can be. Thank you!!!

César A. Hidalgo

12,931 次观看 • 1 年前

Claude Opus 4.6 is so strong at financial analysis, including crunching data and reading SEC filings, that after it launched, financial data stocks sold off, with FactSet dropping nearly 10%. Claude Opus 4.6 can analyze company data, filings, and market info to produce deep financial analysis in hours instead of days. On an internal Real-World Finance evaluation of about 50 tasks spanning spreadsheets, slide decks, and word document creation and review, it scores over 23 percentage points higher than Claude Sonnet 4.5. On Vals AI benchmarks, it reports 60.7% on Finance Agent, which tests research over SEC filings, and 76.0% on TaxEval, which tests tax reasoning, with Finance Agent up 5.47% over Opus 4.5.

Claude Opus 4.6 is so strong at financial analysis, including crunching data and reading SEC filings, that after it launched, financial data stocks sold off, with FactSet dropping nearly 10%. Claude Opus 4.6 can analyze company data, filings, and market info to produce deep financial analysis in hours instead of days. On an internal Real-World Finance evaluation of about 50 tasks spanning spreadsheets, slide decks, and word document creation and review, it scores over 23 percentage points higher than Claude Sonnet 4.5. On Vals AI benchmarks, it reports 60.7% on Finance Agent, which tests research over SEC filings, and 76.0% on TaxEval, which tests tax reasoning, with Finance Agent up 5.47% over Opus 4.5.

Rohan Paul

465,744 次观看 • 6 个月前

I'm excited to introduce my AI Exploratory Data Analysis (EDA) Agent that built EDA reports, performs correlation analysis, and missing data analysis in 20 seconds. Today, I'll share with you how to automate creating EDA reports with the AI EDA Agent, which is available on GitHub. We'll create an EDA Agent focusing on a Customer Churn Problem. I'll guide you through setting up the EDA Agent, creating EDA reports, and analyzing the findings. This AI agent is a huge time-saver! Table of Contents: 00:00 Introduction to EDA Tools Agent 01:20 Get the AI Data Science Team 04:49 Create the EDA Tools Agent 06:35 Using the EDA Tools Agent for Missing Data and Correlation Funnels 10:00 Get SweetViz EDA Reports with AI 12:00 8-Week AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: Business Intelligence with AI Register here (1570+ registered):

I'm excited to introduce my AI Exploratory Data Analysis (EDA) Agent that built EDA reports, performs correlation analysis, and missing data analysis in 20 seconds. Today, I'll share with you how to automate creating EDA reports with the AI EDA Agent, which is available on GitHub. We'll create an EDA Agent focusing on a Customer Churn Problem. I'll guide you through setting up the EDA Agent, creating EDA reports, and analyzing the findings. This AI agent is a huge time-saver! Table of Contents: 00:00 Introduction to EDA Tools Agent 01:20 Get the AI Data Science Team 04:49 Create the EDA Tools Agent 06:35 Using the EDA Tools Agent for Missing Data and Correlation Funnels 10:00 Get SweetViz EDA Reports with AI 12:00 8-Week AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, February 12th, I'm sharing one of my best AI Projects: Business Intelligence with AI Register here (1570+ registered):

Matt Dancho (Business Science)

31,079 次观看 • 1 年前

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

AI Evolution

15,565 次观看 • 2 个月前

The data center boom has a geopolitical shadow. Think about it- in a world where military systems run on compute, the buildings that provide that compute will become targets. And the messy part is that a lot of this infrastructure is dual-use with civilian data, banking data, cloud services, defense contracts, intelligence workloads all potentially blurred inside the same ecosystem. So if these facilities are being built next to neighborhoods, schools, and homes, people deserve to know more than “it brings jobs.” They deserve to know what kind of infrastructure they’re living next to, what risks come with it, and whether their community is secretly being folded into the map of modern warfare.

The data center boom has a geopolitical shadow. Think about it- in a world where military systems run on compute, the buildings that provide that compute will become targets. And the messy part is that a lot of this infrastructure is dual-use with civilian data, banking data, cloud services, defense contracts, intelligence workloads all potentially blurred inside the same ecosystem. So if these facilities are being built next to neighborhoods, schools, and homes, people deserve to know more than “it brings jobs.” They deserve to know what kind of infrastructure they’re living next to, what risks come with it, and whether their community is secretly being folded into the map of modern warfare.

Drey

13,996 次观看 • 2 个月前

Galaxy CFO: Half of planned US data centers won't be built on time - or at all. Galaxy thinks it has the edge everyone else is missing. When they converted Helios from a Bitcoin miner to an AI data center, they weren't starting from zero. Long lead-time equipment was already on site, substations already built. Now they have 1,500 acres, approved for 1.6 GW, with another 1.8 GW in various stages of study. "On time, on budget. That is our MO." FT Mike Novogratz Galaxy.

Galaxy CFO: Half of planned US data centers won't be built on time - or at all. Galaxy thinks it has the edge everyone else is missing. When they converted Helios from a Bitcoin miner to an AI data center, they weren't starting from zero. Long lead-time equipment was already on site, substations already built. Now they have 1,500 acres, approved for 1.6 GW, with another 1.8 GW in various stages of study. "On time, on budget. That is our MO." FT Mike Novogratz Galaxy.

Milk Road

16,877 次观看 • 1 个月前

Ken Griffin, founder of Citadel, the most profitable hedge fund in history, on the moment that left him "shocked and depressed" about AI: "one of our team members built an agentic AI system to recreate academic papers in finance." "we have a legion of young masters and PhDs doing this work. it takes roughly six to eight weeks to reproduce a paper." "my colleague built an AI system that would read a paper, reproduce it, verify the results, produce the results on out of sample data — in about two to three hours per paper." "this is not just a white collar job. this is a master's or PhD-level job. six weeks of work turned into two to three hours." "and then OpenAI just solved a math problem that no one had solved for eighty years." "competitive moats are being filled in at lightning speed." the founder of Citadel watching PhD-level work get compressed from six weeks to two hours. and his response wasn't to cut headcount, it was "i will take every single productivity gain i can get because with the talented people we have, we just have more to go after."

Ken Griffin, founder of Citadel, the most profitable hedge fund in history, on the moment that left him "shocked and depressed" about AI: "one of our team members built an agentic AI system to recreate academic papers in finance." "we have a legion of young masters and PhDs doing this work. it takes roughly six to eight weeks to reproduce a paper." "my colleague built an AI system that would read a paper, reproduce it, verify the results, produce the results on out of sample data — in about two to three hours per paper." "this is not just a white collar job. this is a master's or PhD-level job. six weeks of work turned into two to three hours." "and then OpenAI just solved a math problem that no one had solved for eighty years." "competitive moats are being filled in at lightning speed." the founder of Citadel watching PhD-level work get compressed from six weeks to two hours. and his response wasn't to cut headcount, it was "i will take every single productivity gain i can get because with the talented people we have, we just have more to go after."

Goshawk Trades

184,162 次观看 • 1 个月前

.James Talarico: We can start by cracking down on these data centers across the state, that are jacking up our utility bills, and using up all our water. We just found out that Ken Paxton, the most corrupt politician in Texas, has taken nearly half a million dollars from data center companies. That explains why as Attorney General, Ken Paxton ignored our neighbors in Hood County after they asked him to help temporarily block the construction of a data center in their community. Texans cannot afford a senator who's bought by big data centers. In the Senate, I will fight to stop data centers from being built in our communities if they cannot meet the most basic demands of those communities.

.James Talarico: We can start by cracking down on these data centers across the state, that are jacking up our utility bills, and using up all our water. We just found out that Ken Paxton, the most corrupt politician in Texas, has taken nearly half a million dollars from data center companies. That explains why as Attorney General, Ken Paxton ignored our neighbors in Hood County after they asked him to help temporarily block the construction of a data center in their community. Texans cannot afford a senator who's bought by big data centers. In the Senate, I will fight to stop data centers from being built in our communities if they cannot meet the most basic demands of those communities.

Team Talarico

44,044 次观看 • 5 天前