Longtime owners of the Neo Geo AES have watched countless other platforms receive Doom ports over the decades. The console always looked like a strong candidate on paper, with its fast 68000 processor and graphics hardware built for fast sprite handling. Yet the 64 kilobytes of RAM available to the main CPU kept creating a hard stop for anyone who tried a straight conversion. A fresh project shows the limitation was never as final as it once seemed.

SNK designed the Neo Geo with the goal of making as much visual impact as possible with the limited memory they had available, and boy did they succeed. It’s a console that really excels when developers know how to give it well-organized sprites and tile data rather than expecting it to draw things on the fly. Classic Doom, on the other hand, builds its environment one vertical strip at a time, transmitting it all to the screen from a large framebuffer, but that approach is far too memory intensive, and the Neo Geo simply cannot keep up.

NEOGEO AES+ Anniversary Edition

• Legendary video game console reborn
• 1:1 replica of the original console from the 90s
• Unmistakable and uncompromising arcade-grade build

Miguel Sabino figured out a way around this by starting the DoomGeo project on a standard computer with a bunch of conversion tools. These programs consume a Doom WAD file before spitting it out in a format that the Neo Geo can understand. Walls become strips of sprite graphics, along with all of the background elements and animations, because they are all pre-baked and ready to go, rather than having to be created on the fly. In the end, all of this is squeezed onto the cartridge as neat little tables and sprite banks.

Once the ROM boots up, the 68000 CPU’s primary function is to update the sprite control blocks rather than going in and filling in a whole framebuffer pixel by pixel. The hardware sprite system then places, scales, and layers all of those strips to create a great first-person perspective. Floors and ceilings are handled by pre-baked planes that scroll and tilt as they move, while the fixed tile layer houses the entire heads-up display, which includes the status bar, the marine’s face, key indications, and ammo counters. They kept memory demands low by breaking things up this way, yet the game still looks and plays well.

The current build will support every original weapon, including your fist, rocket launcher, and BFG. Monsters have several rotation frames, ensuring that they always face the player in the correct manner while moving about. Doors open, secrets are tucked away, floors that will damage you do exactly that, and the AI inside keeps the enemies on their toes. Even the collision checks take into account the player’s height and step height, ensuring that the movement seems completely natural. A solid 16×16 homemade map becomes the major showpiece, with some experimental paths that can even capture a full-on E1M1 level from the original Doom for testing, and, of course, there’s the audio conversion for the YM2610 sound chip, which is still on the to-do list.

Doom64KB, an even more stripped-down project, takes a completely different approach. It’s based on an older low-memory PC port, and it reduces features even further to fit under the same 64k RAM limit. Floors and ceilings lose their texture maps, music is removed, saving and loading are no longer possible, and only a few particular maps may be played, but hey, it works, even if it sacrifices much of the original experience in the process.

Both of these projects emphasize one basic point: the Neo Geo’s processor and sprite hardware were never the issue. The big challenge was making Doom’s original graphics model to fit within that small memory footprint. These recent initiatives have ultimately overcome that barrier by shifting the heavy lifting to the pre-processing stage and allowing the current sprite system to perform its job, all without the need for additional RAM or custom hardware.
[Source]

Winners & losers: Famed video game director Konrad Tomaszkiewicz has shared surprisingly contrarian views on the impact of delayed next-generation consoles on game developers and publishers, arguing that such delays could actually benefit indie studios and startups. Best known as the director of The Witcher 3, Tomaszkiewicz is currently leading development of the upcoming vampire-themed RPG The Blood of Dawnwalker.

Speaking to Eurogamer, Tomaszkiewicz said he believes the reported delays could be a blessing in disguise for small studios like Rebel Wolves, which he co-founded with other industry veterans in 2022. According to him, smaller teams and indie developers have an easier time optimizing their games for existing consoles than developing for entirely new hardware.

Tomaszkiewicz revealed that Rebel Wolves is preparing four builds of The Blood of Dawnwalker – one each for Xbox Series and PlayStation 5, along with two PC versions tailored for different regions with varying ratings restrictions. According to him, delivering bug-free patches for four versions of a game is already challenging enough without having to develop additional builds for next-generation consoles.

Tomaszkiewicz argued that supporting new platforms multiplies the workload required not only from developers but also from testers, who must ensure that the game “has no blockers (and) you can finish it from the beginning to the end.” He added that the extra work could make development exponentially more complex and prohibitively expensive for smaller teams.

Originally announced in January 2025, The Blood of Dawnwalker is an open-world dark fantasy RPG set in a fictional vampire-infested kingdom in 14th-century southeastern Europe. Players take on the role of Coen, the game’s main protagonist, and complete quests using his human abilities during the day and vampiric powers at night.

The game also features a time-sensitive structure, giving players 30 days and nights to achieve their goal. It offers a wide range of choices that can alter the storyline while providing more freedom than The Witcher 3. Tomaszkiewicz claims that the game draws inspiration from the first two Fallout titles.

Rebel Wolves revealed gameplay details and system requirements for The Blood of Dawnwalker in April, following weeks of media speculation about its storyline and release date. Built using Unreal Engine 5, the game launches on September 3 for PC, PlayStation 5, and Xbox Series.

The city of Los Angeles is letting a three-year contract with Flock Security expire — at least for now — amid concerns about privacy, data storage and the effectiveness of Flock’s license plate reader technology, as well as moves by other cities to distance themselves from the Atlanta-based surveillance company.

Over the weekend, the Los Angeles Police Department announced it would no longer use the 138 mounted surveillance cameras in the city operated by Flock, which were being used to track vehicles by automatically reading their license plates. A few months ago, the Los Angeles Times reported on discontent in LA over Flock potentially sharing information with the US government, including the Immigration and Customs Enforcement agency, although at the time the LAPD praised Flock’s cameras as “tremendous investigative tools.”

In May, a city council member moved to suspend new contracts or agreements with Flock.

Neither the LAPD, the LA City Council nor Flock Safety responded immediately to a request for comment. 

The LAPD told news outlets that a sticking point on moving forward with the company was uncertainty about the data that Flock collects from its cameras, including who owns it and how it can be used once it’s collected. 

Flock’s statement to outlets, including KTLA, suggested that misperceptions were driving the decision and that it had been working with the LAPD on data privacy protections and limits around data access. “While this latest development comes as a surprise, we remain committed to continuing our active and ongoing conversations with LAPD to find a path forward,” a Flock spokesperson told the TV station. 

Cities dropping or reevaluating Flock

A number of US cities have decided to part ways with Flock Safety this year, but even after contracts ended, some continued to have issues with the company.

Dayton, Ohio, and Evanston, Illinois, both used trash bags to cover Flock cameras to prevent the company from continuing to operate them. 

Dayton accused the company of data-sharing violations, including searched related to immigration enforcement. Evanston issued a cease-and-desist order after discovering that Flock had reinstalled cameras the city had ordered removed. 

Other cities that have canceled contracts with Flock include Mountain View and Oakland, California; Knoxville, Tennessee; Flagstaff, Arizona; Cambridge, Massachusetts; San Marcos, Texas; and Redmond, Washington. The website DeFlock is maintaining a running list of city councils that have canceled contracts or rejected bids from Flock. 

As DeFlock points out, Flock isn’t the only vendor of software and hardware that performs automatic license plate reading. Others include Axon, Genetec and Motorola Solutions.

In a secluded room deep within Samsung Display’s headquarters in South Korea, rows of whirring gray and black machines repeatedly fold, flex and stress test the company’s newest mobile displays. During a mid-June visit, I was among the first people outside the company to step inside the high-security lab and see how Samsung pushes its foldable screens to their limits before they reach consumers.

On Tuesday, Samsung unveiled Flex Titanium, a new display technology for its upcoming Galaxy foldable phones including the Z Fold 8. It combines a titanium-alloy film with a titanium plate to create a thinner, more durable display structure designed to better withstand drops and other impacts — an important consideration for foldable phones that can cost thousands of dollars.  

Samsung Display designs and manufactures screens for Samsung Electronics as well as competitors including Apple, and has become one of the industry’s leading developers of flexible and advanced display technology. Beyond commercial products, the company regularly showcases futuristic display concepts for phones, tablets and other devices.

Watch this: I Went Inside Samsung’s Secret Display Lab and Saw Its Wildest Phone Concepts

03:16

As Samsung makes its foldable phones thinner — last year’s Galaxy Z Fold 7 measures an impressively slim 4.2mm when open — the company is looking for ways to scale back various components to maintain a sleek profile. Samsung says it spent about three years developing Flex Titanium technology while examining customer feedback across seven generations of its foldable phones. 

“We have to understand user behavior and various display challenges like dropping or pressure with a large object or a tiny object,” Samsung executive vice president Byung Duk Yang said in an interview. “Because of that, we have developed a very comprehensive and sophisticated evaluation method to understand user behavior in the real world.”

Testing the endurance of foldable displays

As we navigated the maze-like, pristine white hallways snaking below Samsung Display’s headquarters in Korea, about 20 miles from Seoul, our guide touted the exclusivity of what we’d be seeing. No one outside the company — not even the employee’s mom and dad — had been here, she said as she led us into the testing lab.

In this secluded room, which only engineers enter, equipment runs around the clock, folding and unfolding display panels to ensure they can pass 500,000 folding tests. Once the metal latch is closed, the Z Fold 8 panels (there are four inside right now) are subjected to extreme temperatures ranging from -20 degrees to 60 degrees Celsius (or -4 degrees to 140 degrees Fahrenheit).  

Outside the machine, a monitor shows what’s happening inside from eight different camera angles. The footage, which is also being recorded, can detect issues such as the display lifting off the device frame. Currently, the display panels being tested are off, but the machine can evaluate how operational displays respond to extreme conditions, too.

Down another long hallway (I feel like I’m in an episode of Severance at this point), we enter a lab for examining the display’s image quality, including brightness and color. After placing a display in the center of the machine and closing what looks like a miniature garage door with sliders on the windows for peering in, the testing begins. 

A series of bright lights beams down on the panel, and the machine measures how much light is reflected — the less, the better. That’s for a few reasons: The display’s colors appear deeper, less reflection makes it easier to see the screen under bright lighting and you’re less likely to just be staring at your reflection when you look down at your phone. It takes about three minutes to test one panel.

Another test I saw appeared rather simple compared to these more deeply technical mechanics, but it’s equally important for ensuring a display’s durability. A towering 220-pound machine propped on a counter holds a marble-sized metal ball weighing around 21 grams. An arm-like structure drops the ball from a height of 30 centimeters onto the display three times to ensure it won’t crack. In our demo, we pushed the limits to higher drops from 40 and 50 centimeters, and the display effectively absorbed and distributed the pressure to avoid damage. 

Making a “better display”

Samsung’s new Flex Titanium is all about bolstering durabily without adding bulk. Compared to polymer film, titanium-alloy film has 20 times greater mechanical stiffness, the company says, meaning it better retains its shape. This component sits below the OLED panel and is less than one-third the thickness of a human hair. Below that is the titanium plate, which Samsung says can provide more stable support when the phone is unfolded without compromising flexibility. 

Last year’s Z Fold 7 also used a titanium plate, but the display structure was made up of multiple polymer-based support layers. Samsung has now consolidated those layers into a single titanium-alloy film, reducing the thickness of the display module while maintaining strength, flexibility and long-term durability, the company says.

See also: Beyond the Galaxy Z Fold: Samsung’s Future Phone Concepts That Roll, Slide and Expand

Notably, the upgraded display also has a reduced crease — a growing focal point in the world of foldable phones. Samsung Display showed off a creaseless foldable concept screen at CES earlier this year. The company is reportedly working with Apple to develop a creaseless screen for a foldable iPhone, which could make its debut this fall. What I saw at Samsung Display in June still had a minimal crease, although it’s much less apparent than the Z Fold 7’s. 

Samsung is slated to share more about Flex Titanium and upcoming Galaxy foldable devices, including the Z Fold 8, during its summer Unpacked event on July 22. These advancements look to be a step toward mitigating many of the durability and aesthetic compromises that have long characterized foldable phones — though the work is far from done. 

“Years ago, Samsung created this foldable category,” Yang said. “And the foldable display and the structure we developed became the standard. So we feel some responsibility for this market; we have to make a better display.”

Twenty-six anonymous Meta employees have sued the company in federal court in Oakland, California, alleging it used AI-powered software to disproportionately target workers with disabilities, medical leave histories, and pregnancies during mass layoffs.

The employees are seeking to halt the next round of layoffs, scheduled to begin on Jul 22, while they pursue arbitration.

The plaintiffs, from six states, including California, New York and Washington, DC, accused Meta of using tools such as Metamate and productivity metrics to rank employees when it cut thousands of jobs—about 10% of its workforce—earlier in 2026.

The lawsuit, filed on July 13, said that this disadvantages people who missed work because of medical conditions or to care for family members, violating federal and state discrimination and retaliation laws.

However, Meta has refuted the claims, stating that they lack merit and that people, not AI, made the workforce decisions.

The lawsuit appears to be the first against a major company to challenge the alleged use of AI in conducting layoffs.

• Read other articles we’ve written on Singapore’s job landscape here.

Feature Image Credit: Shutterstock

HWMonitor is a lightweight hardware monitoring program that reads your system’s main health sensors. It provides real-time data on voltages, temperatures, fan speeds, and power consumption for CPUs, GPUs, motherboards, storage devices, and more.

Whether you’re troubleshooting, stress testing, or just keeping an eye on system health, HWMonitor delivers clear and reliable metrics in a simple interface. Ideal for PC enthusiasts, overclockers, and tech professionals. The program handles the most common sensor chips, like ITE IT87 series, most Winbond ICs, and others. In addition, it can read modern CPUs on-die core thermal sensors, as well has hard drives temperature via S.M.A.R.T, and GPU temperature.

Why does HWMonitor show several different CPU temperatures?

HWMonitor lists core temperatures individually (Core 0, Core 1, etc.) and also shows an overall CPU package temperature. The core readings are from thermal sensors inside each CPU core, while the package temperature represents the hottest part of the CPU die. When monitoring for thermal issues or stress testing, the highest of these values is the most important.

Is HWMonitor accurate for reporting GPU temperatures?

HWMonitor is generally accurate for GPU temperature readings, as it pulls data directly from the onboard sensors. However, some users report small differences when comparing with MSI Afterburner and other tools. If you need exact numbers for overclocking or thermal analysis, it’s worth comparing with a second tool.

Can HWMonitor show how much power my GPU is using?

Yes, HWMonitor can display GPU power usage if your graphics card supports it. It shows readings from the PCIe slot and the auxiliary power connectors (6-pin or 8-pin). By adding these values together, you can estimate the total power draw of your GPU. This can be helpful when deciding whether your power supply is sufficient or if you’re planning an upgrade.

What are TMPIN readings in HWMonitor?

TMPIN labels are temperature sensors on the motherboard, but their exact purpose can vary depending on the manufacturer. They might monitor the VRMs, CPU socket area, chipset, or other components. Because the naming isn’t standardized, the readings can be hard to interpret without checking your motherboard documentation.

Which CPU temperature should I focus on: package, cores, or motherboard?

The most important temperatures to monitor are the CPU package and the highest individual core temperatures. These reflect the real thermal state of your processor. Motherboard CPU readings are often lower and less precise. As long as your CPU stays below 90 – 95 °C under load, it’s within safe limits for most modern CPUs.

What’s New:

• Hotspot temperature on NVIDIA RTX 50×0 GPUs.
• Preliminary support of Lisuan 7G100 GPU.

Previous Release Notes:

• Intel Arc G3 & G3 Extreme (Panther Lake).
• Intel Core Ultra 5 250KF Plus (Arrow Lake Refresh).
• AMD Ryzen 7 7700X3D (Raphael).
• AMD Ryzen AI Max+ 495, 492, 488 (Gorgon Halo).
• AMD Ryzen AI Max 490, 485 (Gorgon Halo).
• AMD Ryzen AI Max PRO 495, 490, 485, 480 (Gorgon Halo).
• AMD Ryzen 9 9950X3D2 (Granite Ridge).
• AMD Ryzen 9 PRO 9965X3D, PRO 9945 (Granite Ridge).
• AMD Ryzen 7 PRO 9755, PRO 9745 (Granite Ridge).
• AMD Ryzen 5 PRO 9645 (Granite Ridge).
• AMD Ryzen AI 7/PRO 450G/GE (Gorgon Point 2).
• AMD Ryzen AI 5/PRO 440G/GE (Gorgon Point 2).
• AMD Ryzen AI 5/PRO 435G/GE (Gorgon Point 3).
• Support of HUDIMM and HSODIMM memory modules.
• New themes.
• New real-time graphs.

1Password on Tuesday launched AI Spend and Consumption Management, a new capability embedded in its SaaS Manager platform that gives IT and finance teams a unified, real-time view of how their organizations consume and spend on AI services from vendors including Anthropic, Cursor, and OpenAI.

The move marks the latest strategic expansion for a company that built its reputation on password management for consumers and, over the past three years, has aggressively repositioned itself as a broader identity security and SaaS governance platform for enterprise buyers. With this release, 1Password is staking a claim in one of enterprise technology’s newest and most chaotic budget categories: the consumption-based cost of large language models.

“Executives want teams to build faster with AI, but that speed is creating a new kind of spending pressure,” Greg Henry, 1Password’s chief financial officer, said in an exclusive interview with VentureBeat. “Developers are consuming tokens at a pace that traditional budgets weren’t built to manage, and IT and finance teams are being asked to forecast and justify AI investments without a clear view of what’s actually driving costs.”

The product, now in public preview with broad availability planned for fall 2026, connects directly to vendor admin APIs to pull token-level consumption data daily. It normalizes that data across providers into a single dashboard and allows organizations to set vendor-level spend limits, configure threshold-based alerts via Slack and email, and break down usage by team, user, vendor, and model.

Why traditional software budgets can’t keep up with AI token pricing

The core challenge 1Password is targeting is structural. Traditional SaaS pricing operates on a per-seat, per-year model that is easy to budget and reconcile. AI pricing does not. Every API call to Claude, GPT-5.6, or a Cursor-powered coding assistant consumes tokens, and the cost of those tokens varies by model, by input versus output, and by the complexity of the task. A single engineering team running agentic workflows can burn through a prepaid token budget in weeks — and the finance team may not notice until the invoice arrives.

Henry drew a sharp analogy to a problem enterprises have already lived through once. “Consumption-based pricing isn’t new,” he said. “We saw it arrive with cloud infrastructure, and it took years to build the tools and disciplines to manage it. AI is the next version of that shift.”

That comparison resonates across the industry. When Amazon Web Services, Microsoft Azure, and Google Cloud popularized consumption-based pricing for compute and storage in the 2010s, enterprises initially lacked the tooling to monitor and optimize their cloud bills. That gap spawned an entire FinOps ecosystem — companies like CloudHealth, Spot.io, and Apptio built multi-billion-dollar businesses helping organizations understand what they were spending on cloud and why. Henry is explicitly betting that AI token spend will follow the same trajectory, and that organizations that fail to build visibility now will end up, as he put it, “paying far more than they needed to, for far longer than they should have.”

The scale of the coming wave lends credibility to that bet. Goldman Sachs has estimated that token consumption from AI agents alone will grow 24 times by 2030, a projection driven by the expectation that autonomous AI systems will increasingly execute multi-step workflows — booking travel, writing and deploying code, managing customer service interactions — that generate vastly more API calls than a human sitting at a chat interface.

How 1Password’s new dashboard tracks every token across Anthropic, Cursor, and OpenAI

The new capability extends 1Password SaaS Manager‘s existing foundation of application discovery, license management, and spend analytics. It is not a standalone product. Existing SaaS Manager customers can activate it by connecting their supported AI vendor API keys, at which point consumption data flows into a dedicated AI Consumption Management dashboard. Henry confirmed that there is no separate product or add-on fee: “AI Spend and Consumption Management is available to all 1Password SaaS Manager customers.”

The system provides four core functions. First, it aggregates token usage and spend across Anthropic, Cursor, and OpenAI into a single, normalized view — eliminating the need to toggle between three separate vendor dashboards with three different reporting formats. Second, it enables budget controls: organizations can set vendor-level spend limits, configure percentage-based thresholds, and receive automated alerts when prepaid balances approach depletion. Third, it disaggregates consumption by team, user, vendor, and model, allowing finance and IT to understand not just how much is being spent, but where and by whom. Fourth, it situates AI spend within the broader SaaS portfolio, helping organizations see how token costs relate to their total software investment.

Notably, the system captures consumption regardless of whether a human or an AI agent generated it. “Token consumption is captured at the API level regardless of whether a human or an agent is generating it,” Henry explained. “Organizations get the total consumption picture, including the spikes that agent loops can create, which can be some of the hardest usage to catch before it becomes a problem.”

That agent-level visibility matters because autonomous AI systems can generate runaway costs in ways that human users typically cannot. An agentic coding assistant stuck in a retry loop, for example, can consume thousands of dollars in tokens in minutes — with no human in the loop to notice. For now, the product alerts but does not enforce. When asked whether 1Password will eventually give organizations the ability to automatically cut off spending when a threshold is crossed, Henry said the company is “actively evaluating” automatic enforcement but emphasized that visibility must come first: “You can’t enforce what you can’t see.”

The choice of launch partners reveals where enterprise AI budgets are under the most pressure

The decision to start with Anthropic, Cursor, and OpenAI — rather than casting a wider net — reflects where enterprise AI adoption and budget strain are most concentrated right now. Henry said the choice was driven entirely by customer demand. “Anthropic, Cursor, and OpenAI are where we’re seeing the highest adoption, and where token consumption can move fast and get ahead of the teams responsible for managing it,” he said. The company plans to add additional vendors based on customer demand, API availability, and budget impact, though it has not committed to a specific timeline or vendor list.

The inclusion of Cursor alongside the two major foundation model providers is telling. Cursor, an AI-powered code editor that has rapidly gained traction among developers, represents a category of AI tool where consumption is particularly difficult to forecast. Unlike a chatbot interface where a user consciously types a prompt, Cursor integrates AI suggestions directly into the development workflow, generating token consumption continuously as developers write code. That ambient, always-on consumption pattern makes it especially prone to budget overruns.

Henry also addressed who inside an organization should actually own this problem — and acknowledged that the honest answer right now is no one. “When spend is fragmented across vendor dashboards and finance teams are reconciling it monthly, you’re always behind,” he said. “AI spend can’t be treated as a finance-only or IT-only problem.” He noted that the pricing differences between models have become significant enough that the choice of which AI model a team uses is now a meaningful financial decision, one that is pulling CFOs into conversations with IT, product, and engineering leaders “in ways they never had to before.”

Steve May, director of IT at ServiceTrade, a 1Password customer that has been using the capability, said it addressed a concrete planning gap. “Forecasting tools for AI consumption and spend was one of our biggest gaps in planning because we didn’t have a reliable way to track it,” May said. He added that the visibility has “prevented overages that would have cost far more to fix after the fact.”

Where 1Password fits in the fast-consolidating SaaS management market

1Password is not the only company racing to solve the AI cost management problem, but the competitive landscape is still fragmented and the category is far from mature.

Zylo, a SaaS management platform that Gartner has also recognized as a leader in the space, published its 2026 SaaS Management Index in January showing that AI-native application spend surged 393% year over year in organizations with more than 10,000 employees and 108% overall. Zylo’s data also revealed that ChatGPT has become the most expensed application in enterprise environments, highlighting how AI tools are entering organizations through employee credit cards and expense reports — outside formal procurement and governance workflows. Zylo has added its own token-level cost tracking for AI vendors including Anthropic, OpenAI, Cursor, and Perplexity.

Meanwhile, according to a comparison published by Coommit in May, Vendr — which focuses more on SaaS negotiation than discovery — tracks AI tools at the contract level but does not yet offer consumption-level visibility. And the FinOps Foundation reported in its 2026 State of FinOps survey that 98% of organizations now actively manage AI costs, up from just 31% in 2024. The broader SaaS management market is also consolidating rapidly. In May, Deel acquired Sastrify, a German SaaS management vendor, and began folding it into its HR platform — a signal that SaaS management capabilities are increasingly being absorbed into adjacent enterprise platforms rather than remaining standalone products.

1Password’s approach differs from pure-play SaaS management competitors in one important respect: it is building AI cost management on top of an identity security platform, not a FinOps or procurement tool. The company’s SaaS Manager product grew out of its 2025 acquisition of Trelica, a UK-based SaaS access management startup whose technology enabled the discovery of unsanctioned applications — so-called shadow IT. As BetaKit reported at the time of that deal, 1Password co-CEO Jeff Shiner described Trelica as “a pioneer in modern SaaS access management” and said the acquisition would accelerate 1Password’s Extended Access Management product roadmap by more than a year. CRN noted that Trelica brought more than 300 SaaS integrations to the platform. That identity-first lineage gives 1Password a natural advantage in connecting spend data to specific users and teams — a linkage that matters when the question shifts from “how much are we spending on AI?” to “who is spending it, and is it delivering value?”

From password manager to platform company: 1Password’s $6.8 billion bet on enterprise identity

The launch raises a question that Henry addressed head-on: whether a company that started as a consumer password manager can credibly compete in enterprise AI cost management.

“It doesn’t feel like a stretch to us. It feels like a natural progression,” he said. “For more than 20 years, 1Password has evolved alongside how our customers work. We started by protecting passwords. Then we helped organizations manage secrets, control access, and get visibility into the applications their teams rely on.”

The company’s evolution has been rapid. 1Password raised a $620 million Series C in January 2022 led by ICONIQ Growth, reaching a $6.8 billion valuation — at the time, the largest funding round ever raised by a Canadian company, according to Crunchbase. The round also attracted celebrity investors including Ryan Reynolds, Scarlett Johansson, and Robert Downey Jr. As of early 2025, BetaKit reported that 1Password had surpassed $250 million in annual recurring revenue, with B2B sales accounting for nearly three-quarters of total revenue and the company claiming to be cash-flow positive.

In May 2024, 1Password launched Extended Access Management, a platform designed to secure sign-ins across both managed and unmanaged applications and devices. That same year, it acquired Kolide for device trust and, in early 2025, Trelica for SaaS discovery. In June 2026, Gartner named 1Password a Leader in its Magic Quadrant for SaaS Management Platforms. According to 1Password’s own blog post on the recognition, its SaaS Manager now supports over 400 integrations and provides visibility into a library of more than 40,000 pre-populated application profiles. Each step has moved the company further from its consumer roots and deeper into enterprise infrastructure. The AI Spend and Consumption Management launch extends that trajectory into financial operations territory — a domain where 1Password will compete not only with SaaS management vendors but potentially with dedicated FinOps platforms and the AI vendors’ own billing dashboards.

Why high AI token consumption doesn’t always mean wasted money

Perhaps the most revealing part of Henry’s commentary concerns what organizations should actually do with the consumption data once they have it. He pushed back forcefully against the assumption that high token consumption automatically signals waste.

“A team burning through tokens may be building something genuinely valuable,” he said. “A lower-usage project might not be moving the business forward at all. What matters is whether that consumption is producing enough business value to justify the spend.”

Henry drew a distinction between personal productivity — “having a bot summarize your meeting or draft a quick email” — and genuine business outcomes. “What organizations need to see is where consumption is actually driving revenue, efficiency, or something that moves the needle.”

That framing positions AI Spend and Consumption Management not just as a cost-cutting tool but as a decision-support system for AI investment allocation. If a CFO can see that one engineering team’s heavy Claude usage is powering a product feature that drives revenue, while another team’s OpenAI spend is funding low-value internal automation, the organization can reallocate budget accordingly rather than imposing across-the-board cuts.

“When costs rise faster than expected, the instinct is to cut,” Henry said. “But most organizations can’t yet tell which teams, models, or tools are responsible for the increase, so they end up cutting across the board rather than directing investment toward the AI projects that are actually delivering business value. Blunt cuts on a technology you’re counting on for competitive advantage is not a management strategy, it’s a missed opportunity.”

The next enterprise budget crisis is already here — and it’s priced per token

The product’s current scope — three vendor integrations, alerting but not enforcement — is clearly a starting point. Henry signaled that automatic spend limits are on the roadmap and that additional vendor integrations will follow based on customer demand.

But the broader trajectory he described suggests 1Password sees this launch as a wedge into a much larger opportunity. “As traditional SaaS products add AI capabilities, their pricing models are going to follow,” he said. “Organizations that build visibility and management discipline around consumption now are going to be in a much better position when that happens across the rest of their software portfolio.”

If Henry is right, the chaos currently confined to AI token budgets is not a temporary growing pain but a preview of how all enterprise software will eventually be priced. A decade ago, companies scrambled to understand their cloud bills. Today, they are scrambling to understand their AI bills. The question is whether the organizations building the dashboards this time around can get ahead of the curve — or whether, as Henry warned, they will end up where so many companies ended up with cloud, realizing too late how much they were overpaying, and for how long.

AI Spend and Consumption Management is available now in public preview for 1Password SaaS Manager customers. Broad availability is planned for fall 2026.

Bit.Bio’s Dr Emma Pepperell discusses her career in the biotechnology sector, the advancements occurring around her and the importance of bringing a touch of humanity to an often clinical industry.

Interested in veterinary medicine and science from a young age, the now Dr Emma Pepperell focused on the subjects in her early education, before committing to a BSc in Pharmacology at Newcastle University, where she graduated with first class honours. 

It was during her undergraduate degree that she undertook a placement at pharmaceutical GlaxoSmithKline, where for a year she spent her time working with organ models of the brain and gut, to better understand how one might impact the other. 

Pepperell said, “Even then, 20 odd years ago, there was the idea that what’s going on in the brain could affect things like Crohn’s disease and conditions like this that we know affect a lot of people. 

“So that sort of sparked my interest in drug development and the whole sort of pharmaceutical industry and the application of science and research products for health.”

Inspired to continue her education in this field, Pepperell enrolled in the University of Oxford, where she soon graduated with a DPhil in Clinical Laboratory Sciences. As so often happens, her Doctorate focused on an area of learning that would eventually form the basis of her career, which in this case was the application of stem cells to therapies. 

She said, “I was looking at cells from umbilical cord blood to see if they could repopulate the bone marrow for childhood leukemia, so it was very translational. And then I went into the commercial side of life sciences. 

“The opportunity to join Bit.Bio came up a couple of years ago and it seemed like a natural, sort of complete circle to go back to the stem cell field and really think about how could I apply everything I’d learned about life science research tools and drug development and to think about how we can really bring these human cell products to have an impact, help develop drugs and understand disease better.”

For others looking to move into the STEM space or even careers outside of it, she finds it crucial that no matter what decisions you make, that you show a genuine interest in what you are doing. If you have a natural curiosity about something, she finds you will always be far more motivated and invested in developing yourself to fit the dream. 

“I would say for young students starting their career, try and try lots of work experience and find what works for you. I went to a veterinary practice, I went to a patent attorneys and learned about patenting screwdrivers. I tried all sorts of different things to see, okay, what is it that’s actually going to really interest me, so I can find something that’s going to be highly motivating.”

Keeping healthcare humane

Having contributed to the work at Bit.Bio for two years, Pepperell was recently named the organisation’s CEO.

She said, “Fundamentally, what we do is we make human cells. So you can take an adult skin cell or blood cell and reprogramme it back to what’s called a pluripotent state and that means it can become any cell in the body.

“So we can then put in codes that essentially direct the cell to become a neuron, a brain cell, a liver cell, a heart cell, any kind of cell you like and then you can use these cells to really start to understand how disease works. 

“You can use them to identify new drug targets. You can use them to study what happens if a new drug that’s being developed is applied to them to see if that drug is toxic or what the metabolic profile is like. We make cells that essentially replicate human biology in quite a controlled way to really enable the study of health and disease and drug interactions.”

An element of her industry that greatly appeals to her is largely in how it manages the challenges that arise. Pepperell explained how, in drug development, animal testing is an unfortunate, albeit often necessary and even crucial component of the drug development process. 

As more organisations and institutions look to methodologies that limit the use of animal models in creating results for human biology, Pepperell said, “You know we use animal models because it represents a system, but nobody really wants to use them where they can avoid it.

“So, there is a big challenge in the industry at the moment for building non-animal models that people can trust will deliver safe drugs to the market, whilst acknowledging that all of the knowledge and evidence that has been built up for almost the entirety of the pharmaceutical industry’s history has been in animal models.” 

She noted her pride at being part of an organisation that works to support scientists in the adoption and development of new approaches, required by the FDA and other bodies, that may ultimately phase out the use of animals wherever possible in drug development.

Keeping such a clinical industry humane, is for Pepperell, particularly important, as her mission and that of Bit.Bio’s is to leave society better off than they found it. Knowledge sharing is one such way she believes STEM professionals can contribute to a fairer and more thoughtful world. 

She said, “You are only as successful as the teams who are around you because no one can achieve anything on their own.”

An ideal example, she finds, is Bit.Bio’s recently organised Human Cell Forum, where the company brought together 200 scientists all working on human models designed for better drug development. She found that the community feel it created, particularly amongst professionals that are often under immense pressure to secure funding and resources, in some ways alleviated silos and lead to a positive outcome in the research space. 

She said, “What we start to see in these events that we’ve put together is that scientists are really coming together to share how they’re solving problems. One example is ALS, which is a neurodegenerative disease. 

“There were three or four companies who are all trying to develop a similar model and they all brought their learnings to this event and we’re very openly sharing with each other how they’ve optimised the model and that’s quite rare to see.”

Ultimately, she finds it often boils down to who you have in your corner, having faith in your own skills and striving each day to do better than you did the day before, not just for yourself, but for the colleagues, patients and test animals impacted by your work. 

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Do you remember AIM? It may suprize you to hear that AOL’s instant messanger was actually supported all the way up to 2017– two years after Discord launched. Unlike Discord, AIM is a protocol, not a platform. Everything on your favourite Discord server is at the mercy of the corporate masters of said server; you can’t just spool up your own. Not so for AIM, as [Veronica] explains, both on her blog and in a YouTube video that we’ve embedded below.

The key is the fact that the AIM protocol isn’t locked into AOL’s now-defunct servers; it was reverse engineered in its prime for open-source messengers like Pidgin. You can host your own server, too, using the OpenOscarServer by [mk6i]. Even better, it’s not just AIM, but ICQ! In the sort of irony you only get in real life, the OpenOscar community does all its support on a Discord server. But then, they couldn’t hardly do it over AIM or ICQ these days.

For those of you who were too old or too young to get sucked into the 90s instant messenger craze, these protocols don’t just create chat rooms, that would be the even older Internet Relay Chat protocol, but usually worked more like SMS text messages. You have a contact list, and you send messages to your contacts via a server that acts as a hub. Once upon a time, that server was AOL’s, but now thanks to the OpenOscar project, it can be anybody’s computer. Of course, like texting, you can rope all of your contacts into one big group chat, and the protocol does support images and VOIP. (Which is starting to sound a lot like Discord.)

If you’re tired of your friend-group being at the mercy of American tech companies, [Veronica]’s blog post serves as a good guide to get you started running OpenOscarServer on a Linux system; she used a virtual private server but figures a Raspberry Pi ought to have enough grunt if you don’t have a huge number of people signed up.

For completeness, we should mention that while AOL pulled the plug on AIM nearly a decade back, ICQ, the other protocol supported by OpenOscarServer, lasted straight through until 2024.

Thanks to Keith Olson for the tip! Our tipsline is based on decentralized “electronic mail” technology that anyone can access.