Runway spent weeks trying to engineer its way out of a stubborn bug: AI-generated avatars would drift off-center during real-time video generation. The fix wasn’t a back-end patch — it was a new front-end feature that just worked around the problem. That’s the kind of lesson Ryan Phillips, head of enterprise product at Runway ML, walked through at VB Transform 2026, arguing that even companies not building foundation models themselves can learn from how Runway builds, evaluates, and ships them.

“I think even if you are not all building models yourselves, it’s helpful to learn how we do it because I think almost all of the lessons are applicable to what you all are doing day-to-day,” Phillips said.

Runway is an applied AI research company building general world models to power generative tools. During his presentation, Phillips showcased Runway Characters, a real-time video model that enables zero-latency, back-and-forth interactions with AI-generated avatars. Five years ago, creating a video with illegible text and low framerates took artists hundreds of hours of stitching individual frames together, he said. Today, Runway’s models generate interactive video on the fly.

“Studying how we build these real-time models can inspire how you build and deploy real-time experiences, whether agentic or not, in your companies today,” he said.

Demystifying evals

Building a robust AI product starts with a high-quality evaluation set. However, creating this set cannot be treated solely as an engineering task. It requires deep cross-functional alignment across product, design, research, and sales to define what “quality” actually looks like.

Phillips emphasized running internal workshops where team members review generated examples together. The goal is to align the entire organization on specific failure modes so everyone shares a unified definition of a successful generation.

“We spent a lot of time working with our team, running through examples… of what success and failure looks like, down to the very, very detailed and picky things,” Phillips said.

The resulting evaluation set must cover broad customer use cases alongside extreme edge cases. For instance, Phillips highlighted that to ensure the model behaves predictably when pushed beyond standard human facial structures, they used “Tooth,” a non-human character with no nose and very unusual teeth.

When grading these generations, the Runway team looks for subtle artifacts. In one example, a video where a character’s face remained intact but background elements, such as a net, began morphing was strictly graded as a failure.

Despite the cutting-edge nature of the product, the tool Runway uses to track these evaluations is simple: an Excel spreadsheet. The team logs tests daily, categorizing outputs as “minor” or “major” failures against a predetermined pass rate. 

“We set a bar before we get started on what percentage we need to pass, and when we hit that, we ship the model,” Phillips said. “So it’s not magical.”

For enterprise developers facing non-deterministic quality drift in their own real-time pipelines, manual evaluation at scale is a bottleneck. To solve this, Phillips noted that developers can rely on language models to automate the visual grading process. 

“LLMs are getting quite good at being a judge for a lot of this content, especially the types of morphing or changing that you would see in an evaluation set,” he said. Teams can also feed an LLM behind-the-scenes context (e.g., a hand-drawn sketch or an ad’s structural layout) to guide the generation and validation processes, ensuring quality without adding cognitive load to the end user.

Model training and turning bugs into features

Delivering real-time generative video requires a highly optimized technical stack. The process begins with pre-training a massive foundation model, which is resource-intensive and slow to generate outputs. To achieve real-time latency, Runway relies on distillation, where a smaller, faster “student” model is trained to mimic the large “teacher” model. According to Phillips, distillation helps Runway cut down “80 to 90% of the generation time.”

The team then applies adversarial post-training (APT) to the distilled model. This technique forces the model to continuously improve by testing it against a system designed to find its flaws, helping regain the visual sharpness lost during the distillation process.

However, altering the model architecture introduces new problems. The distillation and APT phases introduced a stubborn bug: characters would sway or drift from the center of the frame during real-time generation.

The team spent weeks attempting to fix the core model to eliminate the drift, he said. Ultimately, they discovered that if the user’s initial input image was perfectly centered, the generated video remained stable. Instead of spending more time on a backend engineering patch, Runway pivoted to a user experience solution.

“What we did was, when we noticed this in our evaluations, we then said, ‘What if we just offered that as a feature?’ If a user gives us a character that is turned to the left, we know the video is going to morph. Let’s just fix it for them,” Phillips said. 

They introduced a frontend feature called “Optimize for Image Quality,” which automatically re-centers the user’s image before generation begins. By wrapping a backend model limitation in a frontend tool, users perceived a helpful feature rather than an engineering flaw.

“Turn model limitations into product features so that you can actually expand how the model works,” Phillips advised. “It might feel like a limitation internally, but your customers will not see it that way if you’re kind of building this in as a product feature.”

The devil is in the infrastructure details

Delivering video globally at 24 frames per second requires optimizing every layer of the infrastructure stack. This ranges from caching and parallel decoding to making deep kernel changes in partnership with hardware providers like Nvidia.

Shortly after launching Runway Characters, he said the team noticed that 8% of API calls were dropping to 16 frames per second, causing the video to stutter for customers. 

Finding the root cause required deep observability. The team used an AI agent powered by Claude alongside monitoring tools like Datadog and Sentry to trace the anomaly. The debugging session isolated the problem to a single data center in the us-east-1 region.

“The solution actually wasn’t [to] go fix anything or change a config,” Phillips explained. “They actually went and physically replaced those GPUs in the data center to fix it, and that ultimately solved the problems.”

For enterprise teams deploying real-time applications, the takeaway is clear: hardware and infrastructure anomalies will directly impact model performance, requiring rigorous, full-stack debugging capabilities. 

“Don’t forget about all the small details, because there’s so many of them when you’re deploying these models,” Phillips said.

Surviving “failure hell” and the future of world-building

Developing AI systems is rarely a linear process. Teams often find themselves stuck for weeks on a single problem with no end in sight, a phase Phillips referred to as “failure hell.”

“We think you have to go through that pain and really struggle with the problem for a little bit before you can get the breakthrough,” he said. Consistent iteration eventually flattens the difficulty curve, triggering sudden, exponential improvements.

As the underlying models overcome these technical hurdles, the role of enterprise creatives is also fundamentally changing. Traditionally, marketing and design teams have focused on creating single assets, like a specific advertisement or illustration. In an era of real-time generation and agentic workflows, that paradigm is shifting toward defining parameters, aesthetics, and intellectual property.

“You might not be designing a single ad, but you might design a world that then the agent or a real-time video model can generate ads from,” Phillips said. 

Last week’s unprecedented security event in which two OpenAI security hacking models trespassed into the network of fellow AI company Hugging Face was enabled by exploiting one or more zero-day vulnerabilities in Artifactory, JFrog, the product’s developer, said Monday.

In an incident mimicking a dystopian sci-fi novel, two OpenAI models broke out of the restricted environment meant to keep them from accessing the Internet during an internal test, the AI company revealed last week. The models went on to breach Hugging Face’s network and steal confidential information and credentials. OpenAI said its agent achieved the feat by exploiting a previously unknown vulnerability. The company called the event “unprecedented,” and outsiders largely agreed.

Not the triumph made out to be

OpenAI said the models exploited multiple attack vectors, including stolen credentials and zero-days, to gain remote code execution capabilities, but until now, the vulnerable software was unknown. JFrog’s Monday disclosure said the product was a self-managed instance Artifactory, a repository management system that secures and streamlines customers’ software development operations. JFrog says Artifactory is used by more than 7,500 developer Teams, 80 percent of which work for Fortune 100 companies.

“During an internal evaluation of frontier cyber capabilities, OpenAI’s models, running deliberately without production safeguards in an isolated research environment, autonomously discovered and employed chained vulnerabilities to escape its sandbox, reach the open internet, and extract evaluation answers from Hugging Face’s infrastructure,” JFrog CTO Yoav Landman wrote. The executive went on to say that the company learned of the zero-days from OpenAI.

The company said Monday that it fixed the exploited vulnerabilities, but it didn’t identify them or provide other important details, such as the conditions under which the vulnerabilities can be exploited. Such details are standard in many vulnerability disclosures because they’re necessary for customers to assess risks. In an email, a company representative declined to provide the details.

Release notes published Monday for version Artifactory 7.161.15 listed the CVE designations for nine patched vulnerabilities. The disclosure made no mention that any of them had been actively exploited in the wild. External sources, however, show that three of them—CVE-2026-65617, CVE-2026-65923, and CVE-2026-66018—were privately reported by OpenAI researcher Khai Tran. It’s likely that at least two of them were the zero-days OpenAI’s models exploited, but without confirmation, it’s impossible to say so definitively.

In shaping her career, Peru native Mariana Costa has asked herself a question: What can I do to make life better for women in Latin America?

The answer she landed on was training them for tech jobs.

Such positions pay well and are in demand. And for too long, women across the region have been locked out of them, she says.

Costa is president of Laboratoria, a U.S.-registered nonprofit based in Miami that she helped found. Laboratoria has trained thousands of women in 11 Latin American countries for technology careers. She has built training centers in the countries and has placed graduates at major companies. Meanwhile, she has become one of the most recognized voices in the region on workforce equity and tech education for women.

IEEE recognized her work with its President’s Award this year for her “distinguished leadership and contributions to the betterment of society.” Recipients of the award are selected by the IEEE president with the consent of the IEEE Board of Directors.

Costa says the recognition came as a surprise because she is not an engineer by training and had never considered becoming affiliated with IEEE.

She was presented with the award at the IEEE Honors Ceremony on 24 April in New York City.

Peru: a country of contrasts

Costa grew up in Lima, Peru’s capital, in a household with no connection to engineering or technology. Her mother was an art historian and professor, and her father was a lawyer. The family was financially comfortable and traveled abroad regularly. Costa attended well-resourced schools.

That economic stability came with a reckoning, Costa says, in that she recognized early on that economic inequality had created separate societies inside Peru. Her parents, she says, made it “clear that my reality wasn’t the reality of most people in my country.”

Lima is a microcosm of the country, she says. The divide in the capital city is visible: A kilometers-long concrete wall topped with barbed wire separates wealthier neighborhoods from shantytowns, where residents lack running water.

Nationally, there are splits along ethnic and geographic lines. The highland and jungle regions remain home to mostly indigenous communities with limited educational access and a deep cultural distance from the Hispanic-dominated coast.

The questions that stirred in her as a child never left, she says.

“Why do I live in a country where so much depends on where you’re born?” she asked herself. “What does it mean to be Peruvian when individual realities are strikingly different?”

Those questions followed her to the London School of Economics, where she studied international relations, graduating with a bachelor’s degree in 2007. She held onto the questions when she moved to Washington, D.C., where she spent the next four years working for the Organization of American States, helping Latin American governments improve public services that fall under the heading of civil registration.

“I said, ‘How can it be? The tech space has so many rich opportunities. Why aren’t any women here?’”

The OAS Universal Civil Identity Program in the Americas provides technical support to national civil registry institutions, modernizing them to foster social inclusion and ensuring the right to civil identity for all people. Without civil identity, a person can’t access education, health care, legal employment, social services, or the right to vote. People without the classification don’t exist in the eyes of the government. They also can’t own property, get married officially, or pass citizenship rights to their children.

Doing that work deepened her concern about the socioeconomic disparities in her homeland, she says. In search of practical solutions to those problems, she went to New York City in 2011 to further her education. She earned a master’s degree in public administration and development from Columbia in 2013.

Technology was not yet part of a solution. But Costa already had met someone who would change that.

Falling in love with a programmer

While working in Washington, Costa met Herman Marìn, a software engineer who used digital tools in support of social causes. Because he was doing work she had never associated with programmers before, her assumptions about the field dissolved quickly.

“I had a vision of [programmers doing] something not very social—strictly technical,” she says. “And my then-boyfriend, now husband, actually worked for different social movements that used technology to address social causes.”

That realization cracked something open, she says: “I said, ‘Oh! Technology can actually be a tool to address some of the more stubborn problems in our societies.’”

After earning her degree at Columbia, Costa returned to Lima with her husband. She had been abroad for nearly a decade and felt the pull of home.

“The thought of not moving back to my country was something that tormented me a bit,” she says. “I really felt I had to move back, at least to try it out and contribute somehow.”

What Latin America’s tech space lacked

When Costa, her husband, and a friend from graduate school moved to Lima, they had modest savings and big ambitions. They wanted to build something that combined technology with social impact.

They started with what they had: a small digital services agency, where they built websites for clients.

The business grew, and they hired more employees. Their team expanded to a dozen software engineers. And as it did, Costa noticed three things.

First, there weren’t enough trained developers to meet the demand. Second, many of their best hires did not have traditional computer science degrees. Some had never even finished college.

“There was no other space where you could actually build an amazing career and get a well-paying job without a good degree from a good school,” she says. “The tech world was different. It was open in ways other fields weren’t.”

Thirdly, she noticed that there were no women on the team. In the first six months, Costa says, they didn’t interview a single female developer.

Her colleagues shrugged. It’s just how it is, they told her.

Costa, the outsider, didn’t accept that.

“I said, ‘How can that be? The tech space has so many rich opportunities,’” she says. “‘Why aren’t there any women?’”

Building Laboratoria

In 2014 she decided to launch Laboratoria. The business model was simple: Find talented women who hadn’t yet broken into tech, train them quickly on practical skills, and connect them with employers who needed developers.

Laboratoria started offering a six-month immersive boot camp that covered Web development, UX design, data literacy, strategic use of artificial intelligence, and soft-skills coaching such as interview prep and projecting confidence.

Just as important for career success, Costa says, is a user-centered mindset. She says Laboratoria’s program emphasizes the discipline of keeping the client’s needs in mind when designing the work.

The teaching model has evolved beyond the boot-camp structure, but the organization still focuses on helping Latin American women develop tech skills and land quality jobs in the digital age. These days, the training, conducted via twice-weekly live Zoom sessions, lasts six weeks.

“We needed developers ourselves,” she says of the company’s original logic. “I said, ‘Why don’t we run a program to train women—women who are incredibly talented but haven’t been given a chance yet—and help them gain the skills they need to get a great job as quickly as possible?’”

Mariana Costa [seated, right] poses with Laboratoria co-founder and CEO Gabriela Rocha and co-founder and chief product officer Rodulfo Prieto.Valeria Martens

It worked. Laboratoria expanded from Lima to Santiago, Chile; Mexico City; São Paulo, Brazil; and Bogotá, Colombia. The organization eventually incorporated as a nonprofit in the United States. Today its programs are held remotely in Latin America’s major job markets. So far, Laboratoria has opened the doors to tech careers for more than 3,500 women.

Costa says she believes the most important skills Laboratoria’s graduates need aren’t purely technical. Close behind the growth mindset is self-confidence, she says.

“Knowing who you are, valuing who you are, and learning to trust yourself and your capacities are indispensable traits,” she says.

Networking, she adds, is the third pillar, and often the hardest to build for women without access to elite schools or flexible work schedules.

“When you go out in the market,” she says, “you realize that having a network of people who trust you and know your work is such a valuable and critical asset.”

IEEE: a new connection

Costa’s introduction to IEEE came late—but it landed hard.

She is not an IEEE member, so when she was contacted this year about receiving the President’s Award, she did her homework on the organization. What she found, she says, was a public charity whose reach and values aligned with her mission.

“IEEE is about expanding access to opportunities in the world of technology,” she says. “And that’s also the core of what we do at Laboratoria.”

She says she also sees IEEE as a living example of something her company preaches every day: “I was talking about the value of professional networks, and I think IEEE is such an amazing reference in that space. It exemplifies this belief that human connection—not only doing your work but also sharing and learning with others—is at the core of building thriving technology careers.”

The engineering organization found her well after she launched her tech-related career. But it wasn’t too late. She says she intends to make the most of the connection.

Bleak Future: A few hours after recovering from the “great Xbox outage” of July 2026, Microsoft is now trying to assure customers that these kinds of systemic issues will not happen again in the future. Transparency is great, but people are questioning why Redmond isn’t removing online requirements for single-player, disc-based games.

Earlier this week, the Xbox network became unavailable to a majority of players. Users were unable to launch their purchased games, sign in, or complete new purchases, with even offline games and disc-based releases being affected by the outage. Most of the issues should now be resolved, although the Xbox team is still investigating the incident in preparation for a full post-incident review.

While the investigation is ongoing, Xbox CTO Scott Van Vliet has shared a few crucial details about the outage. The source of the outage appears to have been a licensing service operating outside the main Xbox infrastructure. Microsoft uses this service to manage licenses and user access to several products, but the Xbox network was hit hard when the service began to fail.

The outage affected both end customers and Xbox partners, Vliet said. Players were unable to sign in in many scenarios requiring an “entitlement check” for purchased products, while Microsoft publishing partners relying on the same system were unable to manage their games. In Microsoft’s parlance, an entitlement check is simply a way to manage digital rights for content “purchased” by end customers.

– Scott Van Vliet (@scottvanvliet) July 28, 2026

In any case, the Xbox support team was quick to identify the “major incident” and isolate the failing part of the network’s infrastructure. They shifted network traffic to other, healthy parts of the network and were eventually able to restore almost full access to the entire Xbox experience. The service came back at different times across the global network, which is why some people regained access before others.

Vliet was adamant that having a single point of failure for a complex network such as Xbox is not an ideal solution going forward. Microsoft is apparently working on “hardening” the systems that sign-in and game-launch processes rely on while improving the team’s responsiveness to this type of platform-breaking problem.

Users welcomed Vliet’s “no bullshit” approach, but some were still frustrated by the fact that a network-related issue was capable of turning their disc-based games into useless plastic coasters.

Now that the industry is preparing for a future where physical games no longer exist, some enthusiasts fear that a failed “entitlement check” could turn thousands of dollars’ worth of purchased games into thin air.

Month-end Apple deals are in full effect at Amazon, with AirPods 4, AirPods Pro 3, and AirPods Max 2 discounted by up to $100.

Those looking for the lowest AirPods price this week can take advantage of Amazon’s $99 special on AirPods 4, reflecting a $30 price cut off MSRP.

Buy AirPods 4 for $99

If you would like the added functionality of Active Noise Cancellation, AirPods 4 with ANC are also marked down, with a $35 discount bringing the price down to $144.99.

AirPods Pro 3 are reduced to $199.99 thanks to a $50 price cut, with delivery as early as today to select locations for Prime members.

The steepest discount can be found on Apple’s over-ear option, with AirPods Max 2 now $100 off at Amazon as well. With the triple-digit savings, you can pick up a pair in any of Apple’s five color options for $449.

Today’s top AirPods deals

Layoffs partially a cost-saving measure, sources told Bloomberg.

Payments giant Visa is cutting roughly 7pc of its workforce in a now familiar pivot towards AI. The layoffs translate to about 2,600 employees.

The job cuts are expected to primarily affect technology and product teams. Visa has European offices in Poland and the UK.

“To capture the opportunities ahead and best position Visa to lead this transformation, we must continue evolving how we work,” company CEO Ryan McInerney wrote in a memo to staff, parts of which were verified by multiple news organisations.

“AI is also helping to accelerate this evolution and shape the way work gets done at Visa.”

Visa’s layoffs come at a transformational moment for the tech industry, which has been rapidly evolving since generative AI’s mainstream popularity skyrocketed in recent years.

Tech leaders, including the likes of Meta CEO Mark Zuckerberg and Block’s Jack Dorsey, among several others, have shared their vision for slimmer teams powered with AI for better cost saving and added efficiency.

Fintech Block cut around 40pc of its company’s staff – or around 4,000 people – earlier this year. More recently, Microsoft announced 4,800 job cuts and the parent company behind the Reuters news agency laid off 500 engineering jobs. Even bigger layoffs, including 8,000 job cuts at Meta, were also announced in recent months.

According to technology and start-up layoffs tracker Layoffs.fyi, 252 tech companies have cut more than 124,000 jobs so far in this year alone, already crossing the nearly 123,000 that were laid off in the whole of 2025.

Sources, however, told Bloomberg that AI-powered work efficiency was not the only reason behind Visa’s decision to cut jobs.

Visa intends to redirect the funds saved towards consumer payments, business and value-added services, including stablecoins, cross-border and business-to-business offerings, they added.

“I have deep conviction that we are doing what is right for Visa, our clients and our partners as we continue to focus on driving efficiency across the company in order to reinvest in our highest potential opportunities.

“As a result of the choices we have made over the past few years, we are entering a new era in commerce with a business that has real momentum,” McInerney said in the memo.

“We see this in our continued strong financial results, client satisfaction, employee engagement, and breakthrough innovation as we build and ship products better and faster than ever before.”

Net revenue at the company is up 14pc this quarter past to $11.6bn. Company shares gained more than 1pc by trading close on Tuesday (28 July), falling marginally in after-hours trading. Share prices have risen nearly 5pc over the past year.

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Ryan McInerny at the World Economic Forum Annual Meeting, 2025. Image: World Economic Forum via Flickr (CC BY-NC-SA 4.0)

Visa aimed Anthropic’s Claude Mythos at the infrastructure behind billions of daily transactions, a network that spans more than 200 countries and territories, moves money in roughly 160 currencies, and connects nearly 5 billion payment credentials to more than 175 million merchant locations.

The model stitched minor weaknesses deep in the stack into working exploit chains that would traditionally have surfaced only late in penetration testing. Rajat Taneja, Visa’s president of technology, walked the VB Transform 2026 audience through what came next, including why Visa released the harness that governed the entire hunt as open source and why the company abandoned traditional remediation metrics for a measurement its team invented.

Taneja has run technology strategy, product engineering, and global infrastructure at Visa since 2019, after joining the company in 2013 from Electronic Arts, where he served as CTO following 15 years at Microsoft. He co-authored, with Visa chief information security officer Subra Kumaraswamy, the June 10 blog post announcing the release of the Visa Vulnerability Agentic Harness on GitHub as a reference implementation that any security team can inspect, adapt, and extend. Visa also published a technical white paper detailing the architecture, lessons learned, and 12 non-negotiable architectural practices for critical infrastructure.

Trust built on pessimism and paranoia

Taneja led with the arithmetic that makes Visa a target worth defending obsessively. Trust at the scale of global payments gets engineered through what he called pessimism and paranoia, by assuming failure and designing around it before failure arrives. The network has been hardened over many years through zero-trust architecture, layered defenses, and highly automated security operations built for the scale and reliability global payments demand.

So when Anthropic invited the organizations behind critical software to test Mythos under Project Glasswing, Visa said yes. Glasswing participants collectively identified more than 10,000 high- or critical-severity vulnerabilities in the first month of testing across software underpinning critical systems industry-wide, according to Anthropic. Anthropic’s own conclusion placed the bottleneck after discovery, in verification, disclosure, and patching speed. Visa joined to test decades of hardening at AI speed and learn where advanced models could push its defenses further.

What Mythos showed at Visa

Inside Visa’s environment, Mythos demonstrated system-wide, context-aware analysis, surfacing vulnerabilities buried deep in the stack and flagging issues that grow more serious when chained together, with findings clean enough that engineering teams could act on them without wading through noise. Some findings carried critical severity ratings, and Visa credits its zero-trust controls, network segmentation, and layered safeguards with breaking the chain before any external actor could have acted.

That confirmation mattered, Taneja said, but the epiphany that followed mattered more. “In a world of agentic attacks, defense also has to be agentic,” he said. Even at a company that has invested decades in defense-in-depth, the model revealed assumptions the team had been operating under that needed rethinking. Traditional SAST tools keep their place as a first pass against known vulnerability patterns, Visa’s white paper notes, but pattern matching alone cannot follow an adversary who reasons through logic, data flow, and the exploit chains that live between the signatures.

A harness, not a scanner

Visa’s response was not another monolithic scanner. The team built the Visa Vulnerability Agentic Harness, now in its fifth generation, as a governed pipeline that directs frontier AI models through structured security tasks while enforcing deterministic controls, policy gates, and human oversight at every stage. Taneja walked through the design philosophy. The harness operates across four phases and eleven stages, from code ingestion and threat modeling through deep-dive verification, exploit chain synthesis, and finally remediation and fix validation.

Three design choices drive finding quality, per the project’s own documentation. Threat modeling runs before analysis to focus on the attack surface rather than scanning everything blindly, multi-agent deterministic voting requires convergence across independent reasoning chains before a finding advances, and structured triage artifacts compress the lifecycle from discovery to a result developers can actually ship. The payoff is a pipeline that runs hot by default. A plain scan in the shipped profile runs all eleven stages and edits source files in the target repository in fix mode, applying candidate patches unless the operator stops it at detection.

The harness is multi-model by design. An LLM abstraction layer lets Visa swap or combine providers without changing the control plane, and the open-source version works with Anthropic Claude, OpenAI-compatible models, or a mix. The repo’s documentation is candid about the exception. Applying a fix requires the file-editing tools that only the Anthropic backends expose, so the remediation and validation stages currently require Anthropic models for full functionality, and an OpenAI-compatible model in those roles is limited to report-only output. VentureBeat’s Q2 2026 Pulse research, presented earlier at the conference, reinforces why that provider flexibility matters. Among the enterprises surveyed, 82% rely on provider-native controls as their primary security layer, and 59% plan to adopt or switch agent security tooling within the year. The controls enterprises adopted last year are already becoming the controls they plan to replace.

Mean Time to Adapt replaces legacy metrics

Finding vulnerabilities is no longer the hard part, Taneja argued. The real challenge is how quickly a team can confirm an issue is truly exploitable, fix it, and prove the attack path is closed rather than just showing a patch was applied. Visa calls this Mean Time to Adapt, and the white paper tracks it along three dimensions. Inventory freshness measures how current and complete the organization’s view is of code, configuration, and runtime deployment. Exploitable paths per release counts how many end-to-end attack chains remain possible after each release, not just how many findings were closed. Validation cycle time tracks how long it takes to produce repeatable, evidence-backed proof that a fix works and stays working in production.

That distinction matters because legacy measures such as mean time to detect and raw CVE closure counts can look better on paper while actual exposure keeps growing underneath them. An organization can close hundreds of findings a month and still leave viable exploit chains open if nobody tested whether the patches actually break the attack. MTTA forces teams to measure the outcome that matters, and the white paper leans on CISA Known Exploited Vulnerabilities data to make the prioritization case, noting that fewer than 1% of CVEs are ever actively exploited. Visa’s SSDLC policy now assumes every exploitable path will be exercised in production and requires it to be remediated before code is promoted.

Supply chain risk accelerates under AI

The conversation moved past Visa’s own perimeter when Taneja turned to suppliers. A well-defended enterprise stays exposed through weak vendors and weak open-source components, the white paper warns, so Visa is making AI-specific security posture a non-negotiable dimension of supplier due diligence, with expectations for continuous vulnerability validation, living software bills of materials, and MTTA baselines across its technology stack.

Visa has also joined Project Lightwell, the $5 billion IBM and Red Hat initiative to harden widely used open-source components through AI-driven validation and coordinated patching, alongside financial institutions including Bank of America, JPMorganChase, Goldman Sachs, and Mastercard. The commitment extends the same logic upstream, because the MTTA clock does not pause at any single company’s perimeter.

When agents start buying things

Securing agentic commerce is Visa’s next problem. Taneja described a future where AI agents transact on behalf of consumers and enterprises, and said Visa is building the trust framework, identity layer, and agent readiness scoring that merchants will need before agents can safely complete transactions. Behind that work sits the Visa Payment Threats Lab, a simulation environment where real fraud scenarios get replayed against the authorization rules, thresholds, and configurations Visa actually runs, to surface AI-enabled failure modes as targeted hardening recommendations.

The identity challenge is not theoretical. VentureBeat’s Pulse research found that 69% of enterprises already run credential sharing somewhere in their agent deployments, and companies with shared credentials report security incidents or near-misses at a 63.5% rate, against 40.9% where every agent has its own scoped identity. Visa’s white paper addresses that gap directly, listing “AI agents are identities” among its 12 non-negotiable practices and requiring scoped permissions, least privilege enforcement, full audit trails, and inclusion in IAM governance for every agent that calls an API, reads data, or modifies a system.

Three priorities for defenders

Visa is organizing its defensive strategy around three priorities, Taneja said. Shift security left until exploitable flaws are designed out before they reach production, and replace high-risk, under-supported components before they turn into material exposure. The third is the heaviest lift at Visa’s scale, refactoring defenses to run autonomously under human governance so detection, validation, and response keep pace as threat volume grows and the models behind attacks improve.

None of it requires a payment network’s budget to start. The harness sits on GitHub with 595 stars and 97 forks as of July 20, MTTA needs a dashboard rather than a procurement cycle, and the white paper’s 12 non-negotiable practices map onto architecture reviews security teams already run. Visa’s own conclusion reads like a deadline. The opening to get ahead of machine-speed attackers is still there, the paper argues, and it will not stay open.

Not too long ago, PC gaming was still considered a niche hobby, stereotyped by the typical gamer who lives inside a basement and refuses to come out. Those times, fortunately, are long gone. Esports has grown massively in both viewership and competition, so much so that we have an esports World Cup currently happening in Paris. This popularity is driven mostly by games like Valorant. Even I, famously a MacBook user, have spent countless hours playing Valo with my friends because it’s so much fun. Around 20 million players play the game every month, and some are its biggest fans.

Playing PC games, though, isn’t cheap. You need a capable processor, a GPU that doesn’t throttle when you’re in the middle of a fight, and enough RAM to keep all tasks at bay. Not to mention a high-refresh-rate display, which is super important for hitting those headshots. If you’re in the market for a new machine to take your Valorant gameplay to the next level, I don’t see any better machine than the HP Omen 16 Valorant Edition. It’s the company’s top-of-the-line gaming laptop, complete with a Valorant-inspired design, the Ryzen 9 9955HX processor, an RTX 5070 GPU, and, even in this economy, 24GB of LPDDR5X RAM. Naturally, when HP sent over the laptop for review, I was very excited to get my hands on it. But is it worth your money? This review should help you answer that.

Design & Hardware

If you love Valorant, there is nothing I can say right now that’ll make you not love this laptop. I’ve tested many limited edition phones, and most times brands just slap a logo on the back and call it a day. That’s not the case with the HP Omen 16. The Valorant inspiration starts with the color. It’s painted VALORANT BLUE, a dark navy blue of sorts that looks very unique among the sea of grey laptops. In the center of the back panel, you’ll find the HyperX logo, which is encircled by the red Valorant logo. I didn’t think this combination would work this well, but it does, and it looks fantastic. But that’s not all. On the back panel’s left side is Valorant written in the iconic font, and the right side lists the game’s maps, along with a small logo.

Open up the laptop, and you’re greeted with the same design cues. The WASD buttons are painted red; there’s another logo on the right and a few other subtle design cues. I think it’s a very faithful attempt at making a special edition laptop that doesn’t go over the top. To confirm, it’s not just me fanboying the laptop; I put it on my Instagram story. Look, I post a lot of new tech to show my friends, and never once have I gotten so many likes on the story as with the Omen 16. People asked me all sorts of things about the laptop, with the main thing being it’s so pretty.

Besides all the Valorant stuff, the HP Omen 16 is made from aluminum. The color finish is matte, so thankfully it doesn’t pick up many fingerprints. However, if you’re like me and eat Doritos while watching a series, please keep your hands away because they will smudge the laptop. I had to give the laptop a thorough clean before taking the review photos. When it comes to handling, the Omen 16 is like a typical gaming laptop. All those powerful internals add weight, 2.47 kg to be precise. I wouldn’t call that too heavy, but carrying around a 16-inch laptop will hurt your back a bit. Still, I was able to take it to my nearby coffee shop for some work without much trouble. If I had to complain, it’d be about the charger, which is a hefty unit and a pain to carry around.

Beyond that, the hinge is a bit wobbly, but it keeps the laptop steady and can be opened with one hand. I also wasn’t worried about the durability since there was almost no chassis flex on the keyboard deck. You can chuck it inside your backpack, and it’ll be fine.

Let’s talk ports. With a gaming laptop, brands can’t get away with bundling just one USB-C port. And fortunately, that’s not the case with the Omen 16. On the left and right sides, there are two USB Type-A 5Gbps ports, coupled with a USB 3.0 Type-C port with charging support and a headphone/microphone combo jack. Is that it, you may ask? To which I’d answer no. There is a USB Type-A 10Gbps port, an HDMI 2.1 port, an Ethernet jack, and a barrel charging port on the back side for easier connectivity.

Keyboard & Trackpad

Given that you’d be spending most of the time using the keyboard when gaming, it quickly becomes an important subject. And as a surprise to maybe no one, the HP Omen 16’s keyboard is very good. Keys have a lot of travel, which I love, and there’s satisfying feedback when pressed. The actuation energy isn’t much, and you won’t be disturbing your colleagues with the sound inside an office. Since this is a 16-inch device, HP also bundled a dedicated number pad row.

While I’m not the biggest fan of this layout as it shifts everything to the left, I can see the appeal for gamers and professionals. In classic gaming laptop fashion, the keyboard has RGB backlighting, which can be configured using the Omen Light Studio app. There are four zones, and you can choose to go all the way in the funky territory if you wish. For me, I’m more of a white-backlit guy to keep everything classy.

Moving over to the trackpad, I have nothing to complain about here, as well. It’s a big, glass-topped surface that does the job when navigating the UI. The surface is smooth enough to not cause much friction. The physical buttons feel nice to press, and the energy required for a press isn’t so much that it causes strain.

Display & Cameras

What’s the one thing about the display that matters with games like Valorant? If your answer was high-refresh rate, then you’d be absolutely correct. HP thinks the same, which is the reason the Omen 16 houses a 240Hz refresh rate screen. It’s hard to put that feeling into words, but there’s some genuine advantage that you will get. Beyond that, the panel spans 16 inches and has a resolution of 2.5K and a 3ms response time.

To hit that 240Hz refresh rate, HP had to go with an IPS panel, which is fine to me. Do I miss the deep blacks and vibrant colors of an OLED display? Yes. Still, the Omen 16’s display is fantastic. Colors feel natural, and watching a movie on that big screen is a delight. I finally got around to watching Ted Lasso, and it was a very enjoyable experience, thanks to the 500 nits of peak brightness. For all my creative friends, the Omen 16’s display does cover 100% of the sRGB color space. So, you can edit videos/photos and not worry about them looking messed up on others’ screens. The anti-reflective coating proved quite capable as well, keeping most of the reflections at bay.

As far as the camera is concerned, it won’t be winning any competitions. It’s 1080p, thankfully, and works well for quick video calls or classes. The sharpness in low light can be missing, and colors are washed out compared to my MacBook.

Performance

It’s no secret that a gaming laptop isn’t just for playing games. It’s also a tool for creative and coding professionals who need the extra horsepower. Under the hood, the HP Omen 16 packs the latest AMD Ryzen 9955HX processor, which has 16 cores and 64 MB L3 cache, and can boost up to 5.4 GHz in demanding tasks. It’s paired with 24 GB DDR5-5600 MT/s RAM and a 1 TB PCIe Gen4 NVMe SSD. Graphics are handled by the RTX 5070 GPU, with 8GB of VRAM. Since you can’t have the thirsty RTX graphics running all the time, and people do need more battery life than just one hour, there’s integrated AMD Radeon 610M graphics for lighter tasks.

It shouldn’t come as a surprise, but the Omen 16 is a very powerful machine. You can throw any workload at it, and it’ll handle it like a champ. I did my usual writing and researching on the laptop, and it never once hesitated when opening another application. Everything felt effortless, and I just couldn’t push the laptop with my office work even if I tried. As this was the case, I also installed Da Vinci Resolve to do a spot of video editing. Even with multiple 4K streams, some advanced effects and color grading work, the timeline preview was pretty smooth, and the render times were some of the fastest in my testing. The same happened when running a long Python script, marked by exceptionally quick compile times. Not to mention how smooth everything feels on the 240Hz display.

Benchmarks, however, are where you see the real power of the Omen 16. In Geekbench, the Ryzen 9955HX scored 2,751 in the single-core test and 18,266 in the multi-core test. The closest competition I have tested is last year’s Zephyrus G14, which ran on the Ryzen 9 HX 370. The Omen 16 scored more than 20% higher in multi-threaded workloads. Moving to Geekbench’s GPU test, the score reached a pretty remarkable 120,517 points.

Gaming & Thermals

It’s time to talk about the things you came here for: gaming. After all, that’s the biggest reason to buy the Omen 16. And it would be a shame to start with anything else except Valorant. There, the Omen 16 delivered easy 250+ FPS on high settings. With Red Dead Redemption 2, I could max out the resolution at 2.5K with very high graphics and still get around 80 FPS. Cyberpunk 2077 was a bit more challenging, pushing the laptop to its very limit. On maxed-out settings, I observed around 50 FPS. If that’s not enough for you, there’s always DLSS. It’s a very clever way to get over 100 FPS without losing much detail. Some purists may argue those frames are not real, but you’d be hard-pressed to find the difference playing on a laptop screen.

I employed DLSS once again, with Indiana Jones: The Great Circle, to get an average of 100 FPS, with 1% lows around 80 FPS. If you’re a racing fan, Forza Horizon and Motorsport both worked flawlessly at highest settings, with RTX reflections turned on. Even Call of Duty fans will be pretty pleased with this setup.

As far as thermals are concerned, the bottom plate is a large intake, and the hot air comes out from the sides and back. Regardless of the game I tested, there were no signs of thermal throttling inside a temperature-controlled room. HP also bundles its OMEN app with the laptop to control the metrics. It has ads, which is something I absolutely despise in a first-party app. They should not have ads. That said, it was pretty good at controlling different metrics of the laptop, and you can manually tweak different aspects of the performance.

Battery Life & Speakers

Battery life is usually the Achilles’ heel of gaming laptops, simply because running all those internals takes a lot of power. The HP Omen 16 tries to combat that with an 83 Wh cell. In my daily use, which is mostly on Chrome, along with some spreadsheet work and YouTube, the laptop lasted roughly 4 hours on a single charge. I wouldn’t call that groundbreaking, but it’s enough to get you through a work session inside a cafe. Fortunately, there’s a fast charger bundled, albeit with a massive one. With it, you can recharge the battery to 50% in 30 minutes. If you’d rather not carry the large brick, the USB-C port supports charging.

I can say almost the same about the speakers, which you get two of. They are decent if you want to watch a quick YouTube video with clear dialogue and vocals. Just don’t expect them to fill a room with music. The highs and lows do get slightly muffled, and the treble was a little less than what I like. They also sounded quieter than my MacBook.

Verdict

At ₹299,990, the HP Omen 16 Valorant edition is certainly a premium laptop, but for the right person, I believe it’s a no-brainer. I think it’s one of the better special edition laptops, with a really striking yet sophisticated design that pays homage to Valorant. All the little details are excellent. The build quality is solid, and the performance is just next level. I don’t think there is any workload the Omen 16 can’t handle, and even AAA games run smoothly, albeit sometimes requiring DLSS. Rounding things out is a sizeable 16-inch 240Hz display that keeps things fast, and the excellent-feeling keyboard. I do think the speakers could have been better, but that’s a tradeoff with most gaming laptops.

The indie game company is downsizing as it parts ways with Xbox.