Connect with us
DAPA Banner

Tech

AI companies are building huge natural gas plants to power data centers. What could go wrong?

Published

on

Who doesn’t love a good round of FOMO? From dot-com to Web 2.0, virtual reality to blockchain, the tech industry has had its share of being too afraid to miss out on a trend.

The AI bubble is the big daddy of them all. Its first offspring — the rush to lock down power for data centers — is now begetting a mad dash to secure natural gas supplies and equipment. If FOMOs could have babies, then the AI bubble is already having grandkids.

Microsoft said on Tuesday that it’s working with Chevron and Engine No. 1 to build a natural gas power plant in West Texas that could grow to produce 5 gigawatts of electricity. This week Google confirmed that it’s working with Crusoe to build a 933 MW natural gas power plant in North Texas. And last week, Meta announced that it was adding another seven natural gas power plants to its Hyperion data center in Louisiana, bringing the site to 7.46 GW of capacity — enough to power the entire state of South Dakota.

Are we missing anyone?

Advertisement

The recent investments are concentrated in the southern U.S., home to some of the largest natural gas deposits in the world. Recently, the U.S. Geological Survey estimated that there’s enough in one region to supply energy to the entire United States for 10 months by itself. Every data center operator seems to want a part of it.

The scramble for natural gas has led to a shortage of turbines for the power plants, with prices likely to rise 195% by the end of this year relative to 2019 prices, according to Wood Mackenzie. The equipment contributes 20% to 30% of the cost of a power plant. Companies won’t be able to place new orders until 2028, and it’s taking six years to get turbines delivered, the consultancy notes.

That means tech companies are betting that the AI fever won’t break, that AI will continue to need exponential amounts of power, and that natural gas generation will be necessary for success in the AI era.

Techcrunch event

Advertisement

San Francisco, CA
|
October 13-15, 2026

They may come to regret that third assumption.

Advertisement

Though natural gas supplies in the U.S. are plentiful, and because shipping the fuel isn’t cheap, the country remains somewhat insulated from the turmoil in the Middle East. But supplies aren’t unlimited, and recently, growth in production in the big three regions — responsible for three-quarters of all U.S. shale gas production — has slowed considerably

It’s not clear how insulated tech companies are from price swings since none of them have disclosed specific terms of their agreements. A lot will depend on how firm the price is in those contracts. 

Even if the contracted prices are as firm as can be, the companies could still face repercussions.

Because natural gas generates about 40% of the electricity in the U.S., according to the Energy Information Administration, electricity prices are closely tied to natural gas prices. Tech companies might be able to shield themselves from scrutiny for a bit by moving their gas power plants behind the meter — by skipping the grid and connecting them directly to their data centers. But natural gas isn’t an unlimited resource, and if their ambitions grow too big, even the behind-the-meter operations could drive up power prices for everyone. We’ve all seen how that’s played out.

Advertisement

It won’t just be regular households getting upset either. Other industries, including those that remain much more dependent on natural gas and can’t yet turn to renewables, might balk at data centers grabbing so much of the resource. Powering a data center with wind, solar, and batteries is easy. Running a petrochemical plant? Not so much.

Then there’s the weather. One cold winter could change the calculus by driving up demand among households. Wellheads might freeze off, crimping supplies dramatically, as happened in Texas in 2021. When gas runs short, suppliers will face a choice: keep the AI data centers running or let people heat their homes?

By snapping up natural gas supplies and moving behind-the-meter, tech companies can claim that they’re “bringing their own power” and not straining the electrical grid. But in reality, they’re just shifting their use from one grid to another, the natural gas grid. The AI rush has illustrated just how physically constrained the digital world remains. Does it make sense for them to bet big on a finite resource? Tech companies might regret falling for the FOMO.

Source link

Advertisement
Continue Reading
Click to comment

You must be logged in to post a comment Login

Leave a Reply

Tech

Microsoft releases new AI models to expand further beyond OpenAI

Published

on

Mustafa Suleyman, CEO of Microsoft AI. (GeekWire File Photo / Kevin Lisota)

Microsoft is expanding its roster of in-house AI models, releasing a new speech-to-text system and making two existing models broadly available to developers for the first time.

The moves by Microsoft AI (MAI) are part of a broader effort by the company to expand its proprietary AI capabilities beyond its partnership with OpenAI, giving Microsoft more control over its own destiny in the competition against Google, Amazon, and others.

Microsoft announced MAI-Transcribe-1 on Thursday, a speech-to-text model that it says is the most accurate currently available. The company also released its existing voice and image generation models, known as MAI-Voice-1 and MAI-Image-2, for broad commercial use.

It’s Microsoft’s first major model release since a March reorganization, announced by CEO Satya Nadella, in which Microsoft AI CEO Mustafa Suleyman shifted away from day-to-day Copilot oversight to focus on frontier model development and superintelligence.

Suleyman told The Verge that the transcription model runs at “half the GPU cost of the other state-of-the-art models.” He told VentureBeat that the model was built by a team of just 10 people, and that Microsoft plans to eventually build a frontier large language model to be “completely independent” if needed.

Advertisement

Microsoft also recently hired former Allen Institute for CEO Ali Farhadi and other top AI researchers from the Seattle-based institute to further bolster Suleyman’s team, as GeekWire reported last week.

MAI-Transcribe-1 is designed to handle noisy real-world conditions such as call centers and conference rooms, and Microsoft says it is testing integrations with Copilot and Teams. Microsoft says it offers the best price-performance of any large cloud provider, competing directly with OpenAI’s Whisper and Google’s Gemini on the FLEURS benchmark.

In a blog post, Suleyman called the model “not just the most accurate but also lightning fast.”

MAI-Voice-1 generates natural-sounding speech and now lets developers create custom voices from short snippets of sample audio. MAI-Image-2 ranks in the top three on the Arena.ai image generation leaderboard and is rolling out in Bing and PowerPoint.

Advertisement

All three are available on the Microsoft Foundry developer AI platform and MAI Playground.

Source link

Continue Reading

Tech

‘You Guys Look Great’: Artemis Astronauts Share Earth’s Out-of-This-World Views

Published

on

It’s been more than 50 years since NASA astronaut Harrison Schmitt took the famous Big Blue Marble photograph, showing a breathtaking vision of Earth taken aboard the Apollo 17 spacecraft on its way to the moon. Now, as the four-astronaut crew of the Artemis II mission heads toward the moon, more spectacular images are being released.

This stunning photo is perhaps the most reminiscent of the Big Blue Marble, showing Earth in all its fragile, lovely glory.

“That’s us!” NASA wrote in a post. The post also quoted astronaut Christina Koch as saying of Earth, “You guys look great.”

Advertisement

In a reply to questions on the post, NASA wrote, “Two auroras (top right and bottom left) are visible in this image. Zodiacal light (bottom right), is also visible, as well as airglow from Earth’s atmosphere.”

Another neat photo from the Artemis mission shows the planet neatly bisected, with one side lit up by the sun and the other in darkness.

Advertisement
The Earth half in shadow as taken by the Artemis II crew

This image of the Earth was taken by one of the Artemis II crew out the Orion’s window.

Reid Wiseman/NASA

“You look amazing, you look beautiful,” Victor Glover, Artemis II pilot, said of the views of Earth in a video call with ABC News.

The Orion spacecraft and a half-moon shaped view of Earth in outer space

A view of the Earth from NASA’s Orion spacecraft as it orbits above the planet during the Artemis II test flight.

Advertisement

NASA

Another intriguing image shows part of the spacecraft itself. USA Today noted that “the image appears to show the bottom of Orion’s service module where its main engine and auxiliary thrusters are housed.”

We’re tracking the 10-day Artemis II mission with a regularly updated blog.

Keep an eye on NASA’s image repository to see the latest photos.

Advertisement

Source link

Continue Reading

Tech

Tesla’s Texas factory workforce reportedly shrunk 22% in 2025

Published

on

The total workforce at Tesla’s factory outside Austin, Texas shrunk dramatically last year as the company suffered its second straight year of declining sales, according to a compliance report spotted by Austin American-Statesman.

Tesla went from employing 21,191 people at the factory in 2024 to 16,506 workers in 2025, a drop of 22%. That’s despite the company’s global workforce growing from 125,665 employees in 2024 to 134,785 employees in 2025, according to filings with the U.S. Securities and Exchange Commission.

It’s not clear which teams were most affected by Tesla scaling back its workforce at the plant. But the company has become one of the largest employers in the Austin area since it opened the factory in 2022. CEO Elon Musk also relocated Tesla’s headquarters to the factory in 2021 before it opened. The company has invested more than $6.3 billion in the facility to date, according to the new report.

Source link

Advertisement
Continue Reading

Tech

AirPods Max 2 teardown reveals nothing has changed beyond the H2 chip

Published

on

Though the AirPods Max 2 offer new features, a teardown of the headphones shows they’re still plagued by the same flaws of the original 2020 model.

Close-up of cushioned over-ear headphones in peach and orange tones resting on a dark textured fabric surface, showing mesh inside the ear cup and part of the headband
Apple’s AirPods Max 2 gained the H2 chip, but not much else.

Apple’s AirPods Max 2 debuted on March 16, with their core feature being the H2 chip. With it, Apple’s high-end headphones gained capabilities like Adaptive Audio, Conversation Awareness, and gesture controls, among others. Active Noise Cancellation was improved as well.
However, as explained in our review, the AirPods Max 2 are an iterative upgrade, that ultimately leaves something to be desired. New features and ANC enhancements aside, Apple effectively delivered more of the same with its AirPods Max 2.
Continue Reading on AppleInsider | Discuss on our Forums

Source link

Continue Reading

Tech

Meta Pauses Work With Mercor After Data Breach Puts AI Industry Secrets at Risk

Published

on

Meta has paused all its work with the data contracting firm Mercor while it investigates a major security breach that impacted the startup, two sources confirmed to WIRED. The pause is indefinite, the sources said. Other major AI labs are also reevaluating their work with Mercor as they assess the scope of the incident, according to people familiar with the matter.

Mercor is one of a few firms that OpenAI, Anthropic, and other AI labs rely on to generate training data for their models. The company hires massive networks of human contractors to generate bespoke, proprietary datasets for these labs, which are typically kept highly secret as they’re a core ingredient in the recipe to generate valuable AI models that power products like ChatGPT and Claude Code. AI labs are sensitive about this data because it can reveal to competitors—including other AI labs in the US and China—key details about the ways they train AI models. It’s unclear at this time whether the data exposed in Mercor’s breach would meaningfully help a competitor.

While OpenAI has not stopped its current projects with Mercor, it is investigating the startup’s security incident to see how its proprietary training data may have been exposed, a spokesperson for the company confirmed to WIRED. The spokesperson says that the incident in no way affects OpenAI user data, however. Anthropic did not immediately respond to WIRED’s request for comment.

Mercor confirmed the attack in an email to staff on March 31. “There was a recent security incident that affected our systems along with thousands of other organizations worldwide,” the company wrote.

Advertisement

A Mercor employee echoed these points in a message to contractors on Thursday, WIRED has learned. Contractors who were staffed on Meta projects cannot log hours until—and if—the project resumes, meaning they could functionally be out of work, a source familiar claims. The company is working to find additional projects for those impacted, according to internal conversations viewed by WIRED.

Mercor contractors were not told exactly why their Meta projects were being paused. In a Slack channel related to the Chordus initiative—a Meta-specific project to teach AI models to use multiple internet sources to verify their responses to user queries—a project lead told staff that Mercor was “currently reassessing the project scope.”

An attacker known as TeamPCP appears to have recently compromised two versions of the AI API tool LiteLLM. The breach exposed companies and services that incorporate LiteLLM and installed the tainted updates. There could be thousands of victims, including other major AI companies, but the breach at Mercor illustrates the sensitivity of the compromised data.

Mercor and its competitors—such as Surge, Handshake, Turing, Labelbox, and Scale AI—have developed a reputation for being incredibly secretive about the services they offer to major AI labs. It’s rare to see the CEOs of these firms speaking publicly about the specific work they offer, and they internally use codenames to describe their projects.

Advertisement

Adding to the confusion around the hack, a group going by the well-known name Lapsus$ claimed this week that it had breached Mercor. In a Telegram account and on a BreachForums clone, the actor offered to sell an array of alleged Mercor data, including a 200-plus GB database, nearly 1 TB of source code, and 3 TBs of video and other information. But researchers say that many cybercriminal groups now periodically take up the Lapsus$ name and that Mercor’s confirmation of the LiteLLM connection means that the attacker is likely TeamPCP or an actor connected to the group.

TeamPCP appears to have compromised the two LiteLLM updates as part of an even larger supply chain hacking spree in recent months that has been gaining momentum, catapulting TeamPCP to prominence. And while launching data extortion attacks and working with ransomware groups, such as the group known as Vect, TeamPCP has also strayed into political territory, spreading a data wiping worm known as “CanisterWorm” through vulnerable cloud instances with Farsi as their default language or clocks set to Iran’s time zone.

“TeamPCP is definitely financially motivated,” says Allan Liska, an analyst for the security firm Recorded Future who specializes in ransomware. “There might be some geopolitical stuff as well, but it’s hard to determine what’s real and what’s bluster, especially with a group this new.”

Looking at the dark-web posts of the alleged Mercor data, Liska adds, “There is absolutely nothing that connects this to the original Lapsus$.”

Advertisement

Source link

Continue Reading

Tech

Intel’s 270K Plus CPU dominates content creation workloads while challenging expensive AMD chips without breaking the bank for professionals

Published

on


  • Intel Core Ultra 270K Plus improves Adobe Premiere workflows by 15% over 9700X
  • Rendering in Cinebench and Blender achieves up to 23% faster results
  • 250K Plus outperforms previous-generation AMD CPUs by roughly 35%

Intel’s latest Core Ultra 200S Plus series has drawn attention for delivering performance that is difficult to ignore, especially compared to older Intel models and some similarly priced AMD processors.

In testing by Puget Systems, the 270K Plus and 250K Plus both increase E-core counts, boost clocks, and raise maximum memory speeds, creating a tangible improvement over prior generations.

Advertisement

Source link

Continue Reading

Tech

SpaceX and Blue Origin race to orbit while scientists question the physics

Published

on

The pitch is seductive in its simplicity: AI needs more power than terrestrial grids can supply, so move the data centres into orbit, where the sun never sets and the electricity is free. SpaceX, Blue Origin, and a growing constellation of startups are now racing to make that vision real. The problem, according to the scientists and engineers who would have to make the physics work, is that the vision skips several chapters of thermodynamics, economics, and orbital mechanics that have not yet been written.

SpaceX filed with the Federal Communications Commission on 30 January for permission to launch up to one million satellites into low Earth orbit, each carrying computing hardware that would collectively form what the company described as a constellation with “unprecedented computing capacity to power advanced artificial intelligence models.” The satellites would operate at altitudes between 500 and 2,000 kilometres, in orbits designed to maximise time in sunlight, and route traffic through SpaceX’s existing Starlink network. SpaceX requested a waiver of the FCC’s standard deployment milestones, which typically require half a constellation to be operational within six years.

Seven weeks later, Blue Origin filed its own application. Project Sunrise proposes 51,600 satellites in sun-synchronous orbits between 500 and 1,800 kilometres, complemented by the previously announced TeraWave constellation of 5,408 satellites providing ultra-high-speed optical backhaul. Where SpaceX’s filing emphasised raw scale, Blue Origin’s emphasised architecture: the system would perform computation in orbit and relay results to the ground through TeraWave’s mesh network.

The startup ecosystem is moving even faster. Starcloud, formerly Lumen Orbit, raised $170 million at a $1.1 billion valuation in March, becoming the fastest unicorn in Y Combinator history just 17 months after completing the programme. The company launched its first satellite carrying an Nvidia H100 GPU in November 2025 and filed with the FCC in February for a constellation of up to 88,000 satellites. Aethero, a defence-focused startup building space-grade computers with Nvidia Orin NX chips wrapped in radiation shielding, raised $8.4 million and is testing hardware on orbit this year.

Advertisement

The commercial logic rests on a genuine problem. Global data centre electricity consumption reached roughly 415 terawatt-hours in 2024 and the International Energy Agency projects it could exceed 1,000 TWh by 2026, with accelerated AI servers driving 30 per cent annual growth. In Virginia alone, data centres consume 26 per cent of total electricity supply. Ireland’s share could reach 32 per cent by year’s end. The grid constraints are real, the permitting delays are real, and the political resistance to building more terrestrial capacity is real.

Advertisement

What is also real, scientists argue, is the physics that makes orbital computing spectacularly difficult at any meaningful scale. The most fundamental challenge is heat. In space, there is no air to carry heat away from processors, only radiative cooling, which requires vast surface areas. Dissipating just one megawatt of thermal energy while keeping electronics at a stable 20 degrees Celsius demands approximately 1,200 square metres of radiator, roughly four tennis courts. A several-hundred-megawatt data centre, the minimum threshold for commercial relevance, would require radiators thousands of times larger than anything ever deployed on the International Space Station.

Radiation presents the second structural problem. Low Earth orbit exposes unshielded chips to cosmic rays and trapped particles that induce bit flips and permanent circuit damage. Radiation hardening adds 30 to 50 per cent to hardware costs and reduces performance by 20 to 30 per cent. The alternative, triple modular redundancy, means launching three copies of every chip, three times the cooling, three times the electricity, and three times the mass. Starcloud’s approach of flying commercial GPUs with external shielding is an interesting experiment, but no one has demonstrated that it works at scale or over hardware lifetimes measured in years rather than months.

Latency is the third constraint. A million satellites spread across orbital shells from 500 to 2,000 kilometres cannot achieve the tight coupling required for frontier model training, where inter-node communication latencies must remain in the microsecond range. Low Earth orbit introduces minimum latencies of several milliseconds for inter-satellite links and 60 to 190 milliseconds for ground-to-orbit round trips, compared to 10 to 50 milliseconds for terrestrial content delivery networks. That makes orbital infrastructure potentially viable for inference workloads, not for training, which is where the overwhelming majority of AI compute demand currently sits.

Then there is cost. IEEE Spectrum estimated that a one-gigawatt orbital data centre would cost upwards of $50 billion, roughly three times the cost of an equivalent terrestrial facility including five years of operation. Google has said that launch costs must fall to under $200 per kilogram before space-based computing begins to make economic sense. SpaceX’s current Starlink economics operate at roughly $1,000 to $2,000 per kilogram. Some analysts argue the true threshold for competing with terrestrial refresh economics is $20 to $30 per kilogram, a figure no credible projection places within the next two decades. The economics look even less favourable when set against the deep-tech funding landscape on the ground, where terrestrial infrastructure projects can draw on established supply chains and proven unit economics.

Advertisement

Even OpenAI’s Sam Altman, who explored a multibillion-dollar investment in rocket maker Stoke Space as a potential SpaceX competitor for orbital data centres, has publicly called the concept “ridiculous” for the current decade. Altman told journalists that the rough maths of launch costs relative to terrestrial power costs simply does not work yet, and he pointedly asked how anyone plans to fix a broken GPU in space.

The astronomical community adds a separate objection entirely. The vast majority of the roughly 1,000 public comments on SpaceX’s FCC filing urged the commission not to proceed. If approved, the constellation would place more satellites than visible stars in the sky for large portions of the night throughout the year, further militarising and commercialising an orbital environment that is already straining under the weight of existing megaconstellations.

None of this means orbital data centres will never exist. SpaceX’s Starship, if it achieves its cost targets, could fundamentally change the mass-to-orbit economics that currently make the concept unworkable. Starcloud’s incremental approach of flying small payloads and iterating on radiation performance is the kind of engineering pathway that occasionally produces breakthroughs. And the terrestrial grid constraints driving the interest are not going away.

But the gap between filing an FCC application for a million satellites and actually making orbital computation economically competitive with a warehouse full of GPUs in Iowa is not measured in years. It is measured in physics problems that the current pace of AI infrastructure investment cannot shortcut, no matter how many billionaires are willing to try. The question scientists are asking is not whether space data centres are theoretically possible. It is why, given the magnitude of the unsolved engineering, anyone is treating them as a near-term solution to a problem that requires near-term answers. The sky, it turns out, is not the limit. The radiator is.

Advertisement

Source link

Continue Reading

Tech

Ireland begins digital wallet testing and consultation

Published

on

The wallet will also be used to verify age for accessing online platforms.

The Irish Government is inviting people to try out the new official ‘Government Digital Wallet’ as the platform enters its training phase.

Countries including Nigeria, Laos and New Zealand – and the US state of California – are all piloting their own versions of a digital ID platform, as governments across borders try to bolster security and make administration smoother.

The digital wallet makes up a key part of the Government’s Digital Public Services Plan 2030, which aims to use digital technology to make accessing public services easier and more efficient.

Advertisement

It facilitates identity management that residents should be able to use within the EU to access public and private services. The wallet can be used both offline and online, and will allow users to self-manage how their data is shared.

The ID can help obtain a marriage certificate or register for key welfare supports, and holders can also obtain a digital version of their birth certificates, driving licences and other official documents. The wallet will also be used to verify age on online platforms, amid debates in the region on a ban for social media for those under 16.

It is also expected to reduce the need to repeat the same information to different Government departments and make everyday interactions with state administration more seamless.

The EU mandates that all member states must make a digital wallet available to their citizens by the end of 2026. The Irish wallet will be developed to EU digital identity standards, the Government said.

Advertisement

The digital wallet will “make it simpler for people to verify their identity, apply for supports and access entitlements”, said Minister for Public Expenditure, Infrastructure, Public Service Reform and Digitalisation Jack Chambers, TD.

“The wallet is designed so that all personal data is fully protected, and the user stays in control of what information they put in the wallet and choose to share. Only the details needed for a service will be shared, and nothing more.”

Minister of State at the Department of Public Expenditure, Infrastructure, Public Service Reform and Digitalisation Frank Feighan, TD said that the wallet will be “a crucial element of the Government’s overall portfolio of digital services”.

He added: “It will be able to facilitate secure age verification capability as set out in Digital Ireland and the implementation of the Online Safety Code, under which designated platforms must have age verification measures in place to help protect, in particular, children and young people from online harm.”

Advertisement

Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.

Source link

Advertisement
Continue Reading

Tech

Stop trying to make people read instructions: 10 startup lessons from Convoy co-founder Dan Lewis

Published

on

Convoy co- founder and Microsoft Corporate Vice President Dan Lewis at the Seattle AI Startup Summit on April 2, 2026. (Ken Yeung Photo)

Dan Lewis’ career is hard to summarize in a sentence. He was a product manager at Microsoft, then an early employee at the Seattle AI startup Wavii, which Google later acquired. He made a stop at Amazon before ultimately boomeranging back to Microsoft, where he is today.

At this week’s Seattle AI Startup Summit, it was his experience building Convoy, the one-time unicorn trucking startup that shuttered in 2023, that he wanted to talk about. 

But instead of relitigating what led to Convoy’s collapse, Lewis used his time on stage to share lessons to help entrepreneurs build a startup from the ground up.

Be deliberate about culture

Every company develops a culture, whether the founder shapes it or not, Lewis said. “The question is, are you involved in influencing what that is and helping to shape it around something you think aligns with your mission and the people you want in the company?”

Codify values only after you see what’s working

Back when Lewis was at Amazon, he asked then-CEO Jeff Bezos how the leadership principles were derived. Bezos told him that “he started writing stuff down when he first created the company, and then he realized he didn’t quite know what he was doing. So he waited a year to see what was working and what wasn’t, just to get a feel for how things were going.”

Advertisement

Anything that Bezos wanted to keep was codified. Lewis mirrored this approach for Convoy.

Make sure people know why, not just what

Founders shouldn’t have a culture in which workers accept decisions simply because the CEO says so. Lewis called that dynamic “demotivating,” arguing that employees who don’t understand the reasoning behind decisions can’t act independently or feel real ownership. Without that context, he said, people won’t feel like they’re truly part of the company.

Name teams after problems, not solutions

Lewis urged founders to name teams after the customer problems they’re solving, not the products they’re building. He pointed to his time at Amazon, where he built a Q&A tool called  “Ask a Question, Get an Answer” for the ratings and reviews team. 

The team pushed back: their mandate was to grow ratings and reviews, not launch someone else’s product. Had the team been named around a broader goal like customer or buyer confidence, Lewis said, its members would have been more open to creative approaches rather than feeling like they were “executing somebody else’s plan.”

Advertisement
Innovate deliberately

Invest time and energy into the areas that will really differentiate your company and “give you a chance to win.” Lewis acknowledged that it can feel uncomfortable to copy someone else’s innovations in undifferentiated areas, but sometimes it’s OK, especially when you’re not spending time on things “that don’t matter a lot.” 

Storytelling is a startup superpower
Convoy co-founder Dan Lewis discusses the power of storytelling at the 2026 Seattle AI Startup Summit. (Ken Yeung Photo)

Another critical cultural value is the company’s story. Have you crafted a narrative that is interesting, something people can relate to, and want to be a part of? 

“Think about for what [you’re] doing, what’s the context in the world?” Lewis said. “What is the opportunity that’s just right there in front of us? What’s the tension point as to why we can’t get that opportunity? What is holding the world back from it, and how are we going to unlock it for everyone so it makes everything better?”

When it came to Convoy, for example, he had his work cut out for him early on trying to sign on new business.“Why would my customer, who’s never worked with a technology company, because they’re shipping freight, want to take a bet?” Lewis explained. “Because they want to be part of the story. It’s interesting.” 

Clarify expectations bidirectionally

Trust between founders and employees doesn’t happen by accident. Lewis recommended sitting down — perhaps over a meal — and laying out expectations from both sides before the work begins. It’s a bidirectional process, meaning that both the leader and employee must be heard.

Advertisement
Hire deliberately — and reluctantly
Dan Lewis offers recruiting and hiring insights at the 2026 Seattle AI Startup Summit. (Ken Yeung Photo)

When it comes to hiring, Lewis offered three tips. 

First, every company wants team members who want to “show up every day, knock down walls, and make it happen.” But for more established organizations, they also need an additional type of employee, those capable of operating and innovating existing systems. This creates conflict inside a large business, Lewis said, because two cultures can’t live in harmony, nor is it possible to have “two compensation structures that manage the risk-reward.”

He argued that startups have the “pure play” advantage where there’s one culture, one risk-reward trade-off, and founders can focus on the type of person they need. In fact, Lewis thinks 80% of the workforce should possess that “wall-knocker” mentality.

Second, startups must be deliberate in hiring, applying filters to candidates throughout the candidate funnel, and rating how someone introduced themselves, spoke during the first meeting, and followed up. At the end of the process, companies will “only have people that really want to be there and want to be part of this.” 

Founders shouldn’t invest a lot of time trying to convince someone to join their company. If they are, “you’re working too hard,” and that it’s “probably not the right sign for a startup.”

Advertisement

Lewis’ last tip: Don’t hire. He admitted that it may sound counterintuitive, but he wants founders to think that every time someone new is onboarded, “it was a failure to operate more efficiently and to innovate” in a way that wouldn’t have required bringing a new person aboard.

Instead, they should first ask whether there was an alternative way to complete the task — perhaps through AI — rather than increasing headcount. 

And to be clear, Lewis isn’t advocating for the end of great hiring. Rather, he wants leaders to approach it this way: “Always consider it to be the thing that you wish you didn’t have to do. You wish you could have gotten it done without hiring that person.”

People don’t read instructions

At Convoy, Lewis said, they designed an operations system assuming people would carefully read each other’s notes during multi-day truck jobs with multiple support shifts. Most skipped the notes and started from scratch, irritating customers who had to repeat themselves. 

Advertisement

When Lewis asked investor Henry Kravis of KKR for advice, the answer was blunt: “Stop building a system that assumes people are going to read.” 

The lesson applies beyond operations. Whether it’s customers, employees, or end users, people scan for a button rather than read text. Founders should design processes and products, especially in the AI era, that work even if nobody reads the instructions.

Use data, and embrace concrete examples
Convoy founder Dan Lewis urges startups to back up data with concrete examples at the 2026 Seattle AI Startup Summit. (Ken Yeung Photo)

One final piece of advice from Lewis: be data-driven. Leave the jargon behind and look to the data when something’s wrong, or there’s confusion, and you’re talking it through with your team or customer. 

But also be specific — use clear, concrete examples, along with the exact words customers use, to clarify quickly.

Lewis closed his keynote with a note of humility. None of these lessons came easily, he acknowledged. In fact, many of them weren’t obvious to him until his experience at Convoy forced the issue. The company reached the heights of the startup world before closing its doors, but for entrepreneurs trying to build something that lasts, that hard-won experience may be exactly the point.

Advertisement

His talk kicked off a day of conversation at the second annual Seattle AI Startup Summit, a conference that brings together investors, founders, executives and others. 

In addition to Lewis, attendees heard from AI2 Incubator’s Managing Director, Yifan Zhang, CopilotKit’s CEO, Atai Barkai, Edge Delta’s Founder and CEO, Ozan Unlu, MotherDuck Co-Founder and CEO, Jordan Tigani, and OSS4AI CEO, Yujian Tang, who heads up the conference.

Source link

Advertisement
Continue Reading

Tech

Burning Wood To Brew Wood To Preserve Wood : Pine Tar

Published

on

Before there was pressure-treated wood, before modern paints, there was pine tar. Everything from tool handles to wagons to ships were made of wood preserved with pine tar, once upon a time, and [woodbrew] wants to show you how to make it, how to use it, and why you might put it on your skin.

It starts with, you guessed it, pine! In the first part of the video, [woodbrew] creates a skin salve with pine resin and food-safe oil. The pine resin–which is the sticky goop that dries around wounds on evergreen trees–is highly antiseptic and has been used in wound salves since the stone age. The process is easy: melt it in a double boiler, then mix with equal parts oil. [woodbrew] also adds a touch of beeswax to firm it up, an a little eucalyptus extract for extra germ-killing power, and a nice smell to boot.

That’ll preserve your hands, but what about preserving wood?  That starts at about 9 minutes in, and for that you’re going to need a lot more resin, so picking it off wounded trees like he does at the start of the video won’t work. [woodbrew] suggests starting with dead-or-dying pines, and harvesting the crooks of their branches for “fatwood” — wood with the highest resin content. He also suggests the center of stumps, again of trees that died or were severely injured before being cut down. Then it’s a matter of cooking those fine organic molecules out. This is where we burn the wood to save the wood. Well, to save other wood. Wood we didn’t burn, obviously.

The distillation process [woodbrew] uses it fairly traditional, and consists of a couple of buckets. One bucket is buried and collects the pine tar; the other, with holes in the bottom to allow the tar to drip out, is filled with fatwood and covered tightly before being surrounded by firewood which is set alight. You could use an alternate source of heat here, but if you just cut down a pine tree for its fatwood, well, you’d have the rest of the tree to work with. Inside the fatwood bucket, the heat of the fire cooks off the volatile compounds that make pine tar, while the lack of oxygen from being closed up keeps it from burning. Burying the collection bucket keeps it from getting so hot the volatiles all boil off.

Advertisement

If this sounds like the process for making charcoal or woodgas, that’s because it is! He’s letting the gas fraction flare off here, but you could probably capture it– though a true gasifier brakes the tar down into gaseous compounds as well. The charcoal of course stays in the bucket as a bonus.

To make it usable as a wood finish, [woodbrew] mixes his homemade pine tar 50:50 with linseed oil, thining it to a spreadable consistency that helps it penetrate deep into the wood. By filling the voids in the wood, this mixture will help keep moisture out, and the antiseptic properties of the organic soup that is pine tar will help keep fungi at bay for potentially decades to come.

Thanks to [Keith Olson] for the tip!

Advertisement

Source link

Continue Reading

Trending

Copyright © 2025