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Amanda Florian

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An arrow pointing down inside of a box denoting IT software

Software

When it comes to software tools listed first alphabetically, OpenAI isn’t messing around.

Just a day after founder Sam Altman said OpenAI aims to become “a true platform” for app builders, the company introduced a new 

 dubbed “Aardvark.” Although still in beta, Aardvark is intended to help software developers automate the difficult task of finding and fixing codebase vulnerabilities.

During the Oct. 30 unveiling, OpenAI announced that Aardvark (which it termed an “agentic security researcher”) is powered by GPT-5, its latest large language model (LLM). According to the company’s blog post breaking down the features, Aardvark:

Uses LLM-powered reasoning—as opposed to traditional cybersecurity methods like 

—to monitor new codebase changes (also known as commits), find vulnerabilities, and propose fixes.

Analyzes a full code repo, scanning its history to “identify existing issues”

Integrates with GitHub and explains found vulnerabilities, “annotating code for human review”

Can test a vulnerability’s impact in an isolated, sandboxed environment

Can also attach a patch for subsequent developer review

Is this a revolutionary development in cybersecurity? “Most of these AI tools find things that you can’t find manually,” Avivah Litan, distinguished VP analyst at market-intel firm Gartner, said of the coding assistants on the market today. Litan added that Aardvark demonstrates OpenAI is “​​putting the infrastructure together for application developers to make applications.”

Stephen Bennett, director of cloud-native applications practice at Soliant Consulting, and his team have a quarterly maintenance process for production applications—a manual effort to ensure security packages and libraries are up to date. Bennett also built an agentic tool from scratch, which connects with the team’s code-hosting tool Bitbucket and identifies potential security vulnerabilities in new pull requests.

It’s a bit like the “commit scanning” promised by Aardvark.

When code changes at Soliant are detected, all the code for the pull request provides context to an LLM, which then provides a structured output of whichever security vulnerabilities and errors an 

Aardvark’s commit scanner likely offers a similar functionality with broader context, Bennett said, and he sees a tool like Aardvark helping developer teams if it can truly scan a full code repository as claimed.

“It’s one thing to look at the commit that’s coming in and say, ‘Hey, I can see that you’re using this new library or this new package, and there’s a known security vulnerability with that,” Bennett told IT Brew. “But if it doesn’t have the larger context of the application, it may not understand some additional security pieces or vulnerabilities that you might be introducing with your pull request.”

AI has found its way into the code-scanning process, and autonomous capabilities exist in a range of products, including GitHub Copilot, Amazon CodeGuru Security, Snyk Code, and academic projects like SWE-agent.

These bots must cover an immense number of software vulnerabilities. 

 common vulnerabilities and exposures (CVEs) were published in 2024—an increase from the still-gigantic 28,818 CVEs published in 2023. According to Verizon’s 2024 Data Breach Investigations Report, vulnerability exploits were an initial access vector in 20% of breaches.

An important consideration for Patrick Garrity, security researcher for exploit-intel company VulnCheck, with an AI-powered tool like Aardvark: determining the ratio of noise to value. “If you have a bunch of findings that now you have to triage, naturally, it takes humans to do that work,” he said.

While you certainly can’t automatically trust an AI output without doing some verification, Litan said, a developer still needs AI capabilities to view all alerts, prioritize them, and provide content: “It’s AI versus AI these days. You just can’t do this without it.”

AI is for Aardvark: OpenAI launches continuous code analyzer

The move dovetails with the company’s aim to be a “true platform” for app builders, according to one Gartner analyst.

Brianna Monsanto

A pig in lipstick is still a pig, a mouse in armor is still a mouse, and a piece of non-agentic software marketed as agentic but with no real agentic capabilities is still…non-agentic software.

Tech leaders shopping for new software are encountering a new spin on the not-so-new problem of 

Gartner defines agent-washing as products “inaccurately labeled or rebranded as 

 or agentic AI,” causing confusion for customers. The research firm said the practice is currently “commonplace” within the industry.

Philip Carter, general manager and group VP for IDC’s AI, data, and automation research practice, said agent-washing is the “biggest gap ever between vendor hype around an emerging technology…versus organizational readiness to adopt” the technology.

Part of the issue, according to Carter, is that vendors are quickly embracing 

, leaving some buyers overwhelmed with the amount of options in the marketplace and different 

. Adding to the complexity: There are several different types of 

, each with different levels of capabilities. An AI assistant, for example, can answer questions and perform basic tasks. Meanwhile, AI agents can autonomously perform different tasks on behalf of a user, and may even use persistent memory to improve their performance.

“It’s also exacerbated by the fact that there are a range of other agentic terms that are being thrown out there: agent fleets, agent swarms, headless agents, ambient agents, all doing a slightly different type of thing,” Carter said.

 Rivka Gewirtz Little, chief growth officer at digital identity verification company Socure, said tech professionals can detect faux agents by first determining what type of AI functionality a piece of software is offering.

“What are we really having here?” Little said. “Is it an assistant or an agent? That’s one.”

After professionals understand the vendor’s proposed functionalities and whether those are truly agentic, they must figure out whether the agentic AI can actually solve their problems.

“Are they an agent? Sure?” Little said. “Are they effective? Maybe for two or three parts of the workflow, and then…you get to part five, which is critical to the ultimate outcome, and it’s a terrible result.”

Rory O’Brien, VP of client experience at orchestration platform company Tonkean, said leaders can do this by checking customer references or even turning to testimonials on platforms like Reddit.

“References are big,” O’Brien said. “If they’re saying they do a lot of these things, definitely talk to a reference and then get very specific on the use case that they solved.”

O’Brien said potential buyers should also have conversations with vendors about the composition of their tech stack.

“I would also ask if I’m talking to a vendor, ‘What is your IP? What are you going to go get a copyright for at your organization?’” O’Brien said. “If they can’t answer anything or if they just say, ‘We have really good prompts,’ that probably doesn’t have enough depth.”

 It’s important for organizations to dodge agent-washed purchases because of the unintended consequences it may have down the line, such as agent sprawl, according to Carter.

“Once you’ve got an agent sprawl, you potentially have a major cost problem,” Carter said, “Because you’re paying for a whole bunch of agents that you’re not necessarily using, or you are using but you’re not seeing the value from them or the value that you expected.”

A robot Customer Service AI Assistant typing on laptop

How to shop for software in the era of agent-washing

Gartner says agent-washing is now commonplace in the tech industry.

In a few years, consistent software pricing might join the list of things technology leaders reminisce about as companies deploy new pricing strategies to keep up in the AI era—strategies that might lead those prices to swing wildly depending on a variety of factors.

, more than half (52%) of 501 surveyed product leaders said they plan to roll out new 

What are the biggest changes tech leaders can expect to see from 

 as AI features become the new norm? For starters, a dip in pure subscription-based pricing and a rise in pricing models that blend subscription and usage-based charges. While 42% of surveyed leaders claim to offer pure subscription-based pricing, which was the most popular pricing model for AI offerings, only 37% expect to do so going forward. Revenera found the subscription and usage-based hybrid pricing structure will see a five percentage-point uptick in the future.

 Nicole Segerer, SVP and general manager at Revenera, told IT Brew it’s no surprise that pure subscription-based models will take a blow, partly because AI’s increased capabilities may lead to less users, eventually threatening the traditional per-user subscription model.

“The second reason is that, with AI solutions coming in, the traditional flat-fee subscription where someone pays $10 or $100,000 or whatever it is per year, is also coming under threat, just because there will be a bigger correlation between what customers do and how they use the software, and what the cost of that is,” Segerer said. “And pricing will have to adjust.”

 Segerer said traditional and blended-pricing models aren’t the only strategies vendors will lean on as they bulk their software up with AI-enabled features.

“In the future, there might be a little bit more flexibility as to providing people with access to what they really need, versus trying to sell them the whole thing when it’s not needed,” Segerer said, describing an à la carte pricing model.

Segerer said the software industry may also rely more on an outcome-based pricing strategy, where costs are tied to a specific result.

“I’ll give you an example: So, when I send an MRI scanner, a usage-based model would be, you pay for every scan. Every time the thing switches on and runs, you pay for the scan,” Segerer said. “An outcome-based model would be, I only pay when the scan is successful, as in, the picture quality is good.”

Andy Sen, a CTO and CIO at subscription commerce platform company AppDirect, told IT Brew he has already seen vendors switch to outcome-based pricing. He hopes to see more companies follow suit, along with a flexible pricing structure down the line.

“What I would like to see is vendors…really being clear on how much of their product their customers are using and price based on that,” Sen said. “I think that will help everyone.”

 While pure subscription pricing may lose some companies in the long run, Segerer said subscription-based pricing isn’t going anywhere because it offers recurring revenue and predictability.

“Predictability is super important for both the vendors of software, but then also, even more importantly, for the buyer, because they want to know what they pay,” Segerer said.

Software pricing models expected to get a revamp for the AI era

Revenera SVP and general manager says outcome and à la carte-styled pricing models are in the cards for the future.

At around $187 billion in revenue last year, the video game industry is serious business—and with that size and influence, it’s a prime target for attackers.

Chris Anley, a chief scientist with research firm NCC Group, told IT Brew that security issues in games run the gamut from platform-related concerns like social engineering to standard cyberattacks like ransomware. Those threats aren’t ignored, even if they’re not front-and-center for the IT pros and developers working on the games.

But the threat is real, especially in a BYOD environment.

“Games are becoming more complex, the interactions with the player base is richer, so persuading someone to click on a link within a game might cause the execution of arbitrary code on your corporate computer,” Anley said.

Adding to that complexity is the online component, said Kevin Janzen, CEO of Globant’s gaming and ed. tech AI studio. Every game, from free-to-play phone games to larger multiplayer games, is connected to the web on one level or another.

“It forces you also to spend money on cybersecurity, because you know you’re going to be subject to attacks and you know ill-intended groups that really want to either have fun at your expense or even make money,” Janzen said.

Budgeting for that expense has to be part of game development, Janzen continued. He told IT Brew that consumers need to keep that in mind when they’re buying games and make sure that whoever is developing them is prioritizing their safety and security.

“As a consumer, we also need to be informed and be careful, especially because in many cases the users are kids that…perhaps are completely oblivious of the threats that they are being subjected to,” Janzen said.

He added that, as a parent, he believes that there should be a higher standard “in terms of ensuring that the person that joins and interacts within the platform is not a predator.”

For back-end developers and industry IT professionals in general, video games suffer from the same cybersecurity problems as the overall tech sector. 

 around third-party software clients and backend services present challenges. Taking payment information and providing what’s essentially a platform for users to exchange rich text and other messages presents a significant attack surface. That means IT developers need to ensure they take time to write code responsibly—no easy task in a highly competitive industry where speed is of the essence.

“You’ve got this balance of speed versus security, there’s a dynamic there in terms of, secure coding takes longer,” Anley said. “Producing a quality game is very difficult, and then there’s the market pressures that nudge you towards getting the game out quickly, which means that you may not have kicked the tires on all of the complex cybersecurity attack surface.”

This leads to a difficult scenario for video game IT workers, who must balance the needs of the company, the security of users, and what’s realistically doable.

“The pressure on gaming companies is they’re not just writing probably the most complex and demanding category of software there is—high-performance video games, parsing complex network stacks and all that stuff,” Anley said. “They’re also having to deal with all of the same challenges as anyone taking payments online and protecting their users, and they have the same problem as social media networks, which is user-supplied content that may be hostile to other users or illegal in various different ways.”

retro video game controllers and game cartridges photographed in front of a purple-pink background.

IT workers in video game space need to be aware of security risks, solutions

“As a consumer, we also need to be informed and be careful, especially because in many cases the users are kids,” gaming industry CEO says. 

Curiosity may have killed the cat…but for Microsoft veteran Stefan Weitz, it opened a lot of doors.

Curiosity is what led Weitz, who described his younger self as the “prototypical ’80s nerd kid” who loved his computer and 

, to his first gig outside of college with Andersen Consulting, a premier consulting firm.

“I did that because I like the idea of trying different things,” Weitz told IT Brew. “Part of my problem, honestly, is I love to learn different things, which is great, but also from a career perspective, it can be kind of sketchy, because you kind of bounce around.”

His knack for trying new things is what attracted him to Microsoft after Andersen embedded him in the tech giant as a consultant.

“When I was there, I was sitting in RedWest, which was a new building at the time…I looked around as I was having lunch with these people and said, ‘These are all people like me. They’re all just nerds who really just loved the work and loved the puzzles and loved the challenges,’” Weitz recalled.

After six months, a Microsoft recruiter approached Weitz to make his stay permanent with one line: “You can either stay with the Navy or join the pirates” (Microsoft being the pirates in this analogy).

“That was the pitch that got me over,” Weitz said.

Weitz’s time at Microsoft spanned almost two decades, during which he juggled several titles and opportunities.

“I would basically ingratiate myself with different organizations and then they’d say, ‘Well, okay, just come run it then,’” Weitz said.

One of Weitz’s most notable projects as a Microsoftie: helping launch Microsoft’s Bing search engine, which was designed to compete against Google. Part of the challenge of launching a brand-new search engine was not only the need to build something different from the competition, but also persuade people to try it, he said.

“That was literally building a product that nobody said they wanted and then convincing people they actually wanted it,” Weitz said.

The team ended up producing a “decision engine” designed to help users quickly move past “basic” search to find and utilize the information they needed. “So, if you looked at flights to Boston from Seattle, we would give you all the stuff you’d usually see, but we then have a prediction as to whether or not you should buy it now or wait,” Weitz said.

While Bing’s market share was never able to surpass Google’s, the work that Weitz’s team did had a lasting impact.

“It’s helped a lot with the AI efforts because a lot of the work we did in Bing early days…kind of laid the groundwork for a lot of the work in how AI operates today,” Weitz said.

In 2016, Weitz closed his chapter at Microsoft to focus on his love of building. Since then, he has been up to just about everything under the sun, including running the e-commerce fulfillment solution provider Radial for a few years, co-founding a PTSD treatment company, and starting up a music superfans platform.

“I love to go from zero to one,” Weitz said. “I love to have the idea and then get the thing running, and get it all stood up, and then hand it off to somebody to actually really run it. That’s my throughline there, for sure.”

Weitz’s journey after Microsoft hasn’t followed the traditional playbook of ex-Microsofties, but isn’t out of character for Weitz, according to Matt Wallaert, chief experience officer at outsourcing company Oceans and former Microsoft colleague of Weitz, who said Microsoft employees tend to stay with the company long-term or leave the tech giant to chase roles at similar companies.

“You just don't see that many people who go and do something entrepreneurial and do it really well and dive into that with discipline,” Wallaert said. “Stefan is a really shining example of what it looks like to find a second act that is meaningful and thoughtful.”

 These days, Weitz is known for his event-planning skills. Earlier this year, he tried his hand in the conference industry, co-founding the HumanX conference, an AI-centric conference. Inspiration for the conference came after he noticed some industry leaders’ AI investments remained stagnant, as well as a lack of general-purpose AI gatherings.

“I said, ‘Well, shoot, if we’re relying on enterprises to figure their way through this cacophony of innovation that’s happening every single day, we are going to, at best, under-deliver on the promise of what AI can do,” Weitz said.

The conference’s inaugural year went better than Weitz expected, who said the conference industry is not for the “faint of heart.” Even so, he sees room for improvement for year two, including the type of content the conference will focus on.

“It’s very much more focused on the role of the person, not the industry in which they find themselves,” Weitz said. “We’ll have some that are more geared towards that, but the majority is going to be focusing on the people and the job they have to do.”

As a co-founder of one of the largest AI conferences, he advised young AI talent to remain curious and open to challenges, two of the skills that worked in his favor in his own career.

“That curiosity and that lack of determinism is what’s missing in a lot of young people today, but also is the opportunity for those who identify that to thrive.”

A portrait of co-founder and CEO of Human X, an AI conference, Stefan Weitz.

Why this Microsoft veteran’s next act is AI conferences

The Microsoft veteran recalls what it was like to launch the Bing search engine.

A browser powered by agentic AI could take care of buying plane tickets, setting appointments—and open the door to threat actors.

New research from browser detection and response company SquareX shows how agents in the AI browser Comet can be used by attackers to access account information and email inboxes. Agents are given commands and allowed permissions that can result in malicious actors finding ways to get at your private information.

Audrey Adeline, a member of the SquareX Founder’s Office, told IT Brew that while AI browsers come with a lot of promise, the researchers’ discoveries should serve as a caution. Adeline isn’t saying not to use agentic AI in browsers, especially with internet service providers like 

 integrating the technology into their products, but she did sound a note of caution.

“Because it’s still a new technology, there are still a lot of architectural vulnerabilities that are not fixed yet,” Adeline said. “Among them are the fact that these AI agents are not security-aware. They’re trained to complete tasks to make people more productive, but it’s very easy for attackers to trick these AI agents to make them think that certain malicious tasks are required to complete whatever prompt the user is telling them to do.”

In a demo video Adeline shared with IT Brew, SquareX researchers showed how an agent could give attackers access to their accounts. In the scenario, the Comet agent is asked to research and compile data for a project. In doing so, it encounters a file-sharing app that asks for permissions to read and access the user’s Google account and email. The agent allows access because it is following other instructions; threat actors could use this tactic and others to infiltrate systems.

Adeline said Comet has already come a long way in dealing with security in its browser. But those protections aren’t enough given the scope of potential attacks.

“There are so many ways to essentially exploit them, so it is still not comprehensive at all,” Adeline said. “The fact that we could find these four attacks within just a couple of weeks—the only real guardrail that you can provide is essentially to limit these agentic identities on what they can do.”

AI browser developers like Browserbase are aware of the security threat. The company is partnering with password manager 1Password on a secure authentication process for AI agents that will be incorporated into the Browserbase browser. For CEO Paul Klein, working with 1Password is making things easier when it comes to secure access, and keeping the human element in play helps.

“In the old world, people were giving agents a list of their passwords and saying, ‘Hey, this is the one to log in,’” Klein said. “But now, with this 1Password iteration into a browser agent, we have those best-in-class things where the password is never shared—they can list the sites that you can log into and request access to a certain site, but then the human is approving that.”

Ultimately, browsers using agentic AI will become more or less ubiquitous, Klein said, but as with cloud infrastructure, getting there will require trial and error.

“More and more, the infrastructure needs to catch up to AI, and that’s a lot of the work that we’re doing,” Klein said.

Part of that process is making sure things are locked down. 1Password SVP and Head of Engineering Nancy Wang told IT Brew that encryption is an important part of the security process for browsers because they are the new endpoints. She analogized the protections to holding a safety deposit box in a bank vault.

“Even if you get into the bank, you have the bank key—we’re not actually able to see the contents of your safety deposit box, because you need your own account key,” Wang said, adding, “That’s the same principle that we apply for when we give agents the right access to sensitive things.”

AI browsers are here, and so are attackers

“Because it’s still a new technology, there are still a lot of architectural vulnerabilities that are not fixed yet,” researcher says.

Are you keeping an eye on your protocols?

If not, you may have missed the importance of the model context protocol (MCP), a tool that assists large language models to integrate and communicate with external data sources. As Alex Salazar, co-founder and CEO of 

 firm Arcade.dev, told IT Brew, the speed with which AI has taken over the tech industry—ChatGPT exploded onto the scene just three years ago, in November 2022—has led to a proliferation of tooling-like protocols, many of which never see adoption.

An open-source framework developed by software company Anthropic, MCP quickly became one of the dominant protocols in a field where companies like IBM and Google are also major players. Google’s agent-to-agent (A2A) and IBM’s agent communication protocol (ACP) have seen less adoption, though, as research firm Everest Group 

, that’s not set in stone, given how A2A and ACP are picking up steam: “Enterprises should align protocol use with their architecture—centralized (MCP), collaborative (A2A), or local-first (ACP).”

To Salazar, the interconnectedness protocol war is largely over. Once MCP was adopted by Anysphere’s popular AI-coding platform Cursor, developer interest exploded and MCP was propelled into the mainstream.

“It’s just just connectivity, period, and that war wasn’t terribly long because MCP ended up being one of the fastest, most buzzy protocols I’ve ever seen in my career in tech,” Salazar said.

The protocol came into the conversation at a time when different companies and organizations were looking for tooling solutions that would allow AI systems to integrate and connect with each other and external systems without suffering security and efficiency lapses. What MCP offered, Salazar said, was standardization—an essential building block for the agentic AI technological revolution we are in the midst of.

“How do we get more value out of our AI investments? By connecting our AI to other systems so that we can get workflow automation,” Salazar said. “Because at the end of the day, having a chatbot give you advice is not terribly valuable—having an AI agent automate workflows, that’s huge. That’s ROI.”

, RSAC VP of research, cautioned that the protocols are all in early development, and there are some kinks still to be ironed out.

“MCP is relatively simple,” Efstathopoulos said. “A2A is slightly more complex in the sense that it can be extended to have some context and pass more additional information to the next stage—sometimes it provides too much information, if you ask me, but all of this is in early stages.”

Workers in an office space with surrounded AI patterns.

MCP, A2A, ACP—AI protocol initialisms explained

“At the end of the day, having a chatbot give you advice is not terribly valuable—having an AI agent automate workflows, that’s huge,” AI developer says.