The Rise of AI Super-Agents: Promises and Challenges in the Next Era of Artificial Intelligence

AI super-agent: Frequently asked questions and answers

AI super-agents could potentially be able to do jobs typically done by humans, meaning AI may be coming for your job - in theory. The past two years have been the start of the era of artificial intelligence, and the prevalence of AI in workplaces may be increasing faster than people realize. AI is advancing at a breakneck pace, especially in the field of generative AI. What started out as a tool that could help the everyman in their tasks and improve efficiency is continuing to refine itself, and now, the leaders in the AI field are already touting what can come next. If the predictions of top AI industry figures like OpenAI's Sam Altman and Meta's Mark Zuckerberg are to be believed, 2025 is set to be the start of the era of the AI super-agent. These AIs are, in theory, smarter and have far more utility than their predecessors, and are capable of carrying out more complex tasks by themselves. To put it simply, AI super-agents could potentially be able to do jobs typically done by humans, meaning AI may be coming for your job. But what is the truth behind this claim? What is pushing the public discourse around AI super-agents? And will something like ChatGPT really be coming for your job in the near future? Here is everything you need to know about AI super-agents and what they can, in theory, do. What is an AI super-agent? To understand what a super-agent is, it's important to first understand what an AI agent is. Putting it simply, an AI agent is an AI software that can work towards a specific end by itself. This means it can perform tasks without human assistance and can make decisions on its own. This itself isn't anything new. Other companies have already debuted AI agents that can interact with computers, and OpenAI has already been reported to be working on an AI agent that can interact with a web browser by itself. That AI agent, reported to be called "Operator," according to reports published back in November 2024, could debut before the end of January 2025, or at least a preview of it, but what exactly it can do and what its limitations are have yet to be revealed. Advertisement A super-agent, in theory, is an AI that does even more than that. According to a report from Axios, rather than responding to a simple command or undertaking simple tasks, super-agents would be able to carry out far more complex matters in the pursuit of their goal. This doesn't just mean making decisions, it could mean creating complex and detailed plans and analyses to plan what is essentially an entire vacation, including making the relevant bookings and reservations or even creating entire products from scratch. Stay updated with the latest news! Subscribe to The Jerusalem Post Newsletter Subscribe Now Will AI super-agents be coming for your jobs? This is the biggest question with new advancements in AI, and for good reason. In the past few years, many companies around the world have already seen widespread adoption of AI, which has come at the cost of human staffers. According to a June 2024 survey by Duke University and the Federal Reserve Banks of Richmond and Atlanta, nearly 60% of companies have already started implementing ways to automate tasks that human employees used to do. And according to that same survey, that is set to continue into 2025. The reason for this is twofold. AI being automated can be used to boost productivity and efficiency, and AI is also cheaper than humans. But if an AI super-agent is as good as many are predicting, AI could see even more widespread use in a wide range of industries. For example, making a product, such as software, from scratch is a legitimate possibility for an AI super-agent. In fact, Mark Zuckerberg said as much in a recent appearance on The Joe Rogan Experience podcast. There, he predicted that Meta and other companies could soon release an AI that "can effectively be a sort of midlevel engineer that you have at your company that can write code" and that this could be a reality in 2025. OpenAI's Sam Altman hasn't been as vocal about this timetable as Zuckerberg, but he and his company have been touting the prowess of the next generation of AI, with OpenAI officials having compared them with a human with a PhD. In addition, Altman is also set to meet with US lawmakers and officials to demonstrate OpenAI's new tech, which will "show the economic power of AI," according to The New York Times. Will AI super-agents really be coming for your jobs in 2025? Despite the bold claims in many reports about the imminent arrival of AI super-agents, it is unclear how much of what is being touted about these yet-to-be-released programs is genuine rather than simple hype. Taking to X/Twitter, Altman said that Twitter hype was "out of control" and stressed that the company is not going to deploy artificial general intelligence (AGI), a term used for AI with cognitive skills on par with or greater than that of a human, within the month, and stressed that people's expectations should be lowered. The possibility of AI taking over many jobs, however, is still something many experts say is likely, but not in the immediate future. Speaking to CNN in June 2024, LinkedIn co-founder Reid Hoffman said that AI disruption in the labor market is coming, but not right away. "I believe in three to five years, we'll all have kind of an agent co-pilot that's helping us with anything from how we cook dinner... to doing your job and writing and so forth," he told CNN. "It's job transformation. Human jobs will be replaced - but will be replaced by other humans using AI." Sign up for the Business & Innovation Newsletter >>

OpenAI's Super Agents : The AI Revolution That Could Change Everything

OpenAI is poised to introduce a significant advancement in artificial intelligence: "PhD-level super agents." These advanced AI systems are designed to handle complex tasks with unparalleled precision, speed, and creativity. Their potential to transform industries is immense, but they also bring critical challenges related to workforce disruption, societal adaptation, and technical limitations. As these systems evolve, they promise to redefine the relationship between humans and technology. Imagine a world where the tasks that once required years of human expertise -- designing software, analyzing financial markets, or even managing supply chains -- could be completed with precision and creativity by artificial intelligence. It sounds like the plot of a futuristic novel, but OpenAI's rumored "PhD-level super agents" are bringing this vision closer to reality. These advanced AI systems promise to transform industries by handling complex, multi-layered tasks autonomously, potentially reshaping the very fabric of work and society. But with such new potential comes an undercurrent of uncertainty: what happens to the people whose jobs these super agents might replace? And how do we prepare for the ripple effects of such a profound shift? In this overview AI GRID explore what these super agents are, the challenges they face, and what their rise could mean for all of us. While the future may feel uncertain, understanding the opportunities and risks ahead is the first step toward navigating this new era responsibly. Super agents represent a new evolution in AI technology. Unlike current AI tools that are limited to narrow, predefined tasks, these systems are engineered to autonomously manage intricate, multi-step processes that typically require human expertise. Their capabilities extend far beyond basic automation, allowing them to: The potential applications of super agents span a wide range of industries. For example, they could independently design and debug software, optimize supply chain logistics, or conduct comprehensive market analyses -- tasks that currently require highly skilled professionals. This versatility positions super agents as a fantastic force in fields such as software development, financial analysis, healthcare, and strategic planning. Their ability to perform these tasks efficiently and accurately could lead to significant cost savings and productivity gains for businesses. Recognizing the profound implications of super agents, OpenAI has engaged in private discussions with U.S. government officials. These briefings aim to address the societal, economic, and security challenges posed by deploying such advanced AI systems. Historically, similar consultations have occurred during pivotal technological shifts, underscoring the importance of aligning innovation with public policy. Key topics reportedly discussed during these briefings include: These discussions highlight the urgency of preparing for the societal shifts that super agents could trigger. Policymakers and industry leaders must collaborate to create strategies that balance technological progress with economic stability and social equity. Gain further expertise in AI Agents by checking out these recommendations. The introduction of super agents has the potential to reshape the global economy and labor market profoundly. By automating tasks that require specialized skills, these systems could replace mid-level professionals in areas such as software engineering, data analysis, and customer support. Early examples of AI-driven productivity gains from companies like Meta and Salesforce demonstrate the potential of these systems to streamline operations and reduce costs. However, this efficiency comes with significant challenges. Job displacement is a primary concern, as many roles traditionally performed by humans may become obsolete. This shift could exacerbate economic inequality, particularly if new opportunities are not created to offset the loss of traditional jobs. OpenAI has suggested that AI-driven productivity could support reindustrialization efforts, provided the necessary infrastructure is developed. This vision includes revitalizing industries such as manufacturing and logistics, potentially creating new roles even as others are phased out. To mitigate the risks of economic disruption, governments and businesses must invest in workforce retraining programs and education initiatives. These efforts will be essential to equip workers with the skills needed to thrive in an AI-driven economy. Additionally, fostering innovation in emerging industries could help create new opportunities and ensure a more equitable distribution of the benefits of AI. The rapid progress in AI development has been fueled by several key innovations that have expanded the capabilities of super agents: These advancements have empowered super agents to tackle tasks that were previously beyond the reach of AI. However, the accelerated pace of development has also raised concerns. Critics argue that the technology may be overhyped to attract funding and public support, emphasizing the need for transparency and accountability in AI research and deployment. Despite their promise, super agents face significant technical and ethical challenges. One of the most pressing issues is "AI hallucinations," where systems generate incorrect or nonsensical outputs. This problem undermines trust in AI, particularly in high-stakes fields such as healthcare, legal analysis, and financial decision-making, where accuracy is paramount. Another challenge is the ambitious timeline proposed by OpenAI for achieving its goals. While the company has made remarkable progress, unresolved research challenges and the complexity of real-world deployment suggest that caution is warranted. These limitations highlight the importance of rigorous testing, continuous innovation, and collaboration between researchers, policymakers, and industry stakeholders. Ethical considerations also play a critical role in the development of super agents. Making sure that these systems are designed and deployed responsibly will require robust oversight mechanisms and clear guidelines to prevent misuse. Addressing these challenges will be essential to realizing the full potential of super agents while minimizing risks. OpenAI envisions a future where super agents achieve superintelligence, capable of performing nearly all tasks with minimal human intervention. If realized, this milestone could redefine productivity, creativity, and the nature of work itself. However, the societal changes accompanying such advancements will require careful planning and adaptation. Over the next 18-24 months, the world will closely monitor OpenAI and other leaders in the field as they work to bring super agents closer to reality. Whether these systems fulfill their promise or encounter unforeseen obstacles, their development marks a pivotal moment in the evolution of artificial intelligence. The question remains: how will society adapt to a world where human work may no longer be indispensable? The answer will depend on the collective efforts of governments, industries, and communities to navigate this fantastic period responsibly.

Everything you need to know about AI agents and what they can do

Table of Contents Table of Contents What is an agentic AI? What can AI agents do? Where can I see an AI agent in action? Are AI agents safe to use? The agentic era of artificial intelligence has arrived. Billed as "the next big thing in AI research," AI agents are capable of operating independently and without continuous, direct oversight, while collaborating with users to automate monotonous tasks. In this guide, you'll find everything you need to know about how AI agents are designed, what they can do, what they're capable of, and whether they can be trusted to act on your behalf. What is an agentic AI? Agentic AI is a type of generative AI model that can act autonomously, make decisions, and take actions towards complex goals without direct human intervention. These systems are able to interpret changing conditions in real-time and react accordingly, rather than rotely following predefined rules or instructions. Based on the same large language models that drive popular chatbots like ChatGPT, Claude, or Gemini, agentic AIs differ in that they use LLMs to take action on a user's behalf rather than generate content. Recommended Videos AutoGPT and BabyAGI are two of the earliest examples of AI agents, as they were able to solve reasonably complex queries with minimal oversight. AI agents are considered to be an early step towards achieving artificial general intelligence (AGI). In a recent blog post, OpenAI CEO Sam Altman argued that, "We are now confident we know how to build AGI as we have traditionally understood it," and predicted, "in 2025, we may see the first AI agents 'join the workforce' and materially change the output of companies." Marc Benioff hailed AI agents' emergence as "the third wave of the AI revolution" last September. The "third wave" is characterized as generative AI systems outgrowing being just tools for human use, instead, evolving into semi-autonomous actors capable of learning from their environments. "This is the biggest and most exciting piece of technology we have ever worked on," Benioff said of the company's newly announced Agentforce platform, which enables the company's enterprise customers to build digital stand-ins for their human customer service reps. "We are just starting." What can AI agents do? Being designed to take action for their users, AI agents are able to perform a staggeringly wide variety of tasks. It can be anything from reviewing and automatically streamlining computer code to optimizing a company's supply chain management across multiple vendors to reviewing your calendar availability then booking a flight and hotel accommodations for an upcoming business trip. Claude | Computer use for automating operations Claude's "Computer Use" API, for example, enables the chatbot to effectively mimic the keyboard strokes and mouse movements of a human user, enabling Claude to interact with the local computing system. AI agents are designed to tackle complex, multi-step problems such as planning an eight-course dinner party by establishing a menu after contacting guests for their availability and potential allergies, then ordering the necessary ingredients from Instacart. You'll still have to cook the food yourself, of course. Where can I see an AI agent in action? AI agents are already being rolled out across myriad industries. You can find agentic AI in the banking system where it assists with fraud detection and automated stock trading tasks. In the logistics industry, AI agents are used to optimize inventory levels and delivery routes as market and traffic conditions change. In manufacturing, AI agents are already helping to enable predictive maintenance and equipment monitoring, ushering in an era of "smart" factory management. In healthcare, AI agents help patients streamline appointment scheduling and automate prescription refilling. Google's automotive AI agent will even provide near-real-time information about local landmarks and restaurants for Mercedes' MBUX entertainment and navigation system starting with the next model year's CLA. The technology is also being applied to enterprise business and Salesforce is far from the only SaaS company to embrace AI agents. SAP and Oracle both have similar offerings for their own customers. It should come as no surprise then that the industry's top companies like Google, Microsoft, OpenAI, Anthropic and Nvidia are all racing to develop and deploy AI agents for the business and consumer markets as well. In November, Microsoft announced Copilot Actions, which would see Copilot-based agents integrated throughout the company's 365 app ecosystem, and began rolling the feature out to business and enterprise users in January 2025. NVIDIA AI Building Blocks for Agentic AI In November, Google Cloud announced its AI agent ecosystem program, dubbed AI Agent Space, which, like Agentforce or Google's other AI agent platform, Vertex AI, enables business customers to develop and deploy their own customized AI agents. Nividia unveiled its Nemotron model families, designed specifically for agentic AI tasks, at CES 2025 earlier this month. For its part, OpenAI recently unveiled its new Tasks feature for ChatGPT which allows users to set future reminders and regularly-scheduled tasks (like weekly news roundups) for the chatbot to perform at a later date. The company is also rumored to be working on an AI agent of its own, codenamed: Operator, which is expected to be released at some point in January 2025. Are AI agents safe to use? That depends on your definition of "safe." Because agentic AI systems are built atop hallucination-prone large language models susceptible to adversarial attack, AI agents are themselves prone to hallucinations and can be tricked by malicious actors to behave outside of their established safety guardrails. A 2024 study from Apollo Research, for example, found that tasking OpenAI's o1 model with achieving a goal "at all costs" led the AI agent to try to disable its monitoring mechanism before copying "what it believes to be its weights to a new server and then lie about it to its developers," claiming it suffered "technical errors." Of course, when a chatbot boofs its answer, the stakes are relatively low (unless that user is a lawyer or Google, mind you), compared to what would happen if an AI agent hallucinates data about its automated stock trading strategy. As with all generative AI, users need to be vigilant about what information (be it financial, medical, or personal) they share with chatbots and LLMs.

'AI agents' promise to arrange your finances, do your taxes, book your holidays - and put us all at risk

University of Sydney provides funding as a member of The Conversation AU. Over the past two years, generative artificial intelligence (AI) has captivated public attention. This year signals the beginning of a new phase: the rise of AI agents. AI agents are autonomous systems that can make decisions and take actions on our behalf without direct human input. The vision is that these agents will redefine work and daily life by handling complex tasks for us. They could negotiate contracts, manage our finances, or book our travel. Salesforce chief executive Marc Benioff has said he aims to deploy a billion AI agents within a year. Meanwhile Meta chief Mark Zuckerberg predicts AI agents will soon outnumber the global human population. As companies race to deploy AI agents, questions about their societal impact, ethical boundaries and long-term consequences grow more urgent. We stand on the edge of a technological frontier with the power to redefine the fabric of our lives. How will these systems transform our work and our decision-making? And what safeguards do we need to ensure they serve humanity's best interests? AI agents take the control away Current generative AI systems react to user input, such as prompts. By contrast, AI agents act autonomously within broad parameters. They operate with unprecedented levels of freedom - they can negotiate, make judgement calls, and orchestrate complex interactions with other systems. This goes far beyond simple command-response exchanges like those you might have with ChatGPT. For instance, imagine using a personal "AI financial advisor" agent to buy life insurance. The agent would analyse your financial situation, health data and family needs while simultaneously negotiating with multiple insurance companies' AI agents. It would also need to coordinate with several other AI systems: your medical records' AI for health information, and your bank's AI systems for making payments. The use of such an agent promises to reduce manual effort for you, but it also introduces significant risks. The AI might be outmanoeuvred by more advanced insurance company AI agents during negotiations, leading to higher premiums. Privacy concerns arise as your sensitive medical and financial information flows between multiple systems. The complexity of these interactions can also result in opaque decisions. It might be difficult to trace how various AI agents influence the final insurance policy recommendation. And if errors occur, it could be hard to know which part of the system to hold accountable. Perhaps most crucially, this system risks diminishing human agency. When AI interactions grow too complex to comprehend or control, individuals may struggle to intervene in or even fully understand their insurance arrangements. A tangle of ethical and practical challenges The insurance agent scenario above is not yet fully realised. But sophisticated AI agents are rapidly coming onto the market. Salesforce and Microsoft have already incorporated AI agents into some of their corporate products, such as Copilot Actions. Google has been gearing up for the release of personal AI agents since announcing its latest AI model, Gemini 2.0. OpenAI is also expected to release a personal AI agent in 2025. The prospect of billions of AI agents operating simultaneously raises profound ethical and practical challenges. These agents will be created by competing companies with different technical architectures, ethical frameworks and business incentives. Some will prioritise user privacy, others speed and efficiency. They will interact across national borders where regulations governing AI autonomy, data privacy and consumer protection vary dramatically. This could create a fragmented landscape where AI agents operate under conflicting rules and standards, potentially leading to systemic risks. What happens when AI agents optimised for different objectives - say, profit maximisation versus environmental sustainability - clash in automated negotiations? Or when agents trained on Western ethical frameworks make decisions that affect users in cultural contexts for which they were not designed? The emergence of this complex, interconnected ecosystem of AI agents demands new approaches to governance, accountability, and the preservation of human agency in an increasingly automated world. How do we shape a future with AI agents in it? AI agents promise to be helpful, to save us time. To navigate the challenges outlined above, we will need to coordinate action across multiple fronts. International bodies and national governments must develop harmonised regulatory frameworks that address the cross-border nature of AI agent interactions. These frameworks should establish clear standards for transparency and accountability, particularly in scenarios where multiple agents interact in ways that affect human interests. Technology companies developing AI agents need to prioritise safety and ethical considerations from the earliest stages of development. This means building in robust safeguards that prevent abuse - such as manipulating users or making discriminatory decisions. They must ensure agents remain aligned with human values. All decisions and actions made by an AI agent should be logged in an "audit trail" that's easy to access and follow. Importantly, companies must develop standardised protocols for agent-to-agent communication. Conflict resolution between AI agents should happen in a way that protects the interests of users. Any organisation that deploys AI agents should also have comprehensive oversight of them. Humans should still be involved in any crucial decisions, with a clear process in place to do so. The organisation should also systematically assess the outcomes to ensure agents truly serve their intended purpose. As consumers, we all have a crucial role to play, too. Before entrusting tasks to AI agents, you should demand clear explanations of how these systems operate, what data they share, and how decisions are made. This includes understanding the limits of agent autonomy. You should have the ability to override agents' decisions when necessary. We shouldn't surrender human agency as we transition to a world of AI agents. But it's a powerful technology, and now is the time to actively shape what that world will look like.

AI Agents : How Google, OpenAI, and Anthropic Are Changing the Game

AI agents are redefining how technology interacts with the world, offering autonomous systems designed to achieve specific goals with precision and adaptability. Recent advancements from Google, OpenAI, and Anthropic illustrate how these agents are evolving to address increasingly complex challenges. By using advanced tools, orchestration layers, and cognitive architectures, these organizations are pushing the boundaries of what AI agents can accomplish. This article explores their latest developments, frameworks, applications, and the potential future of AI agents. In this guide by All About AI explore the latest innovations from these tech giants, exploring how they're pushing the boundaries of AI agent capabilities. From Google's sophisticated frameworks to OpenAI's real-time multi-agent systems and Anthropic's tool-enhanced Claude, each approach offers unique insights into the future of AI. Google's approach to AI agents focuses on creating systems capable of observing, reasoning, and acting to achieve defined objectives. At the heart of this framework is the integration of tools that connect foundational AI models to real-world applications. These tools are categorized into three primary types: A critical component of Google's framework is the orchestration layer, which governs reasoning, planning, and decision-making. This layer ensures that agents can manage tasks effectively, maintain memory, and adapt to dynamic environments. Additionally, Google emphasizes the use of multi-agent systems, where specialized agents collaborate to solve domain-specific problems. For example, one agent may focus on retrieving data while another analyzes it, creating a streamlined and efficient workflow. This collaborative approach highlights the potential for scalability and specialization in AI systems. OpenAI has introduced a real-time API designed to enable advanced multi-agent systems, facilitating seamless interaction and coordination between agents. This innovation allows agents to work together in real-time, enhancing their ability to tackle complex tasks. Key features of OpenAI's system include: OpenAI has demonstrated the practical applications of these capabilities through real-time voice agents. These agents excel in customer service scenarios, managing tasks such as authentication workflows and live interactions. By allowing real-time responsiveness and coordination, OpenAI's advancements showcase the potential of AI agents to transform industries that require high levels of interaction and adaptability. Uncover more insights about AI agents in previous articles we have written. Anthropic has focused on enhancing its AI model, Claude, by integrating tools that expand its functionality and reliability. Through function calling, Claude can produce structured outputs with deterministic responses, making sure consistency and accuracy. JSON schemas play a pivotal role in this process, providing a framework for well-defined and reliable outputs. One notable example of this innovation is the creation of a Python file execution tool. By defining a schema and integrating it into Claude's workflow, Anthropic enabled the agent to execute Python scripts as part of its tasks. This capability demonstrates how tool integration allows agents to perform specialized functions and interact effectively with external systems. Such advancements highlight the potential for AI agents to handle increasingly complex and technical tasks with precision. AI agents are poised to transform industries by addressing complex challenges with efficiency and scalability. The strategic chaining of specialized agents -- where each agent focuses on a specific aspect of a task -- has the potential to deliver impactful results across various domains, including: As the field continues to evolve, advancements in tools, orchestration layers, and cognitive architectures will further enhance the adaptability and reliability of AI agents. The focus will remain on creating systems capable of addressing real-world challenges with precision and efficiency. Organizations will likely prioritize iterative development and continuous experimentation to refine these systems and tailor them to unique business needs. The innovations from Google, OpenAI, and Anthropic underscore the critical role of tools and collaboration in advancing agents. By integrating robust frameworks and using multi-agent systems, these organizations are setting the stage for a future where AI agents play a central role in solving complex problems across industries. As these technologies mature, their potential to transform industries and redefine automation will only continue to grow.

AI Agents Are Here. How Much Should We Let Them Do?

Should I set up a personal AI agent to help with my daily tasks? -- Searching for Assistance As a general rule, I think relying on any kind of automation in your daily life is dangerous when taken to the extreme and potentially alienating even when used in moderation, especially with regards to personal interactions. An AI agent that organizes my task list and gathers online links for further reading? Fabulous. An AI agent that automatically messages my parents every week with a quick life update? Horrific. The strongest argument for not involving more generative AI tools into your daily routine, however, remains the environmental impact these models continue to have during training and output generation. With all of that in mind, I dug through WIRED's archive, published during the glorious dawn of this mess we call the internet, to find more historical context for your question. After searching for a bit, I came back convinced you're likely already using AI agents every single day. The idea of AI agents, or God-forbid "agentic AI," is the current buzzword du jour for every tech leader who's trying to hype their recent investments. But the concept of an automated assistant dedicated to completing software tasks is far from a fresh idea. So much of the discourse around "software agents" in the 1990s mirrors the current conversation in Silicon Valley, where leaders at tech companies now promise an incoming flood of generative AI-powered agents trained to do online chores on our behalf. "One problem I see is that people will question who is responsible for the actions of an agent," reads a WIRED interview with MIT professor Pattie Maes, originally published in 1995. "Especially things like agents taking up too much time on a machine or purchasing something you don't want on your behalf. Agents will raise a lot of interesting issues, but I'm convinced we won't be able to live without them." I called Maes early in January to hear how her perspective on AI agents has changed over the years. She's as optimistic as ever about the potential for personal automation, but she's convinced that "extremely naive" engineers are not spending enough time addressing the complexities of human-computer interactions. In fact, she says, their recklessness could induce another AI winter. "The way these systems are built, right now, they're optimized from a technical point of view, an engineering point of view," she says. "But, they're not at all optimized for human-design issues." She focuses on how AI agents are still easily tricked or resort to biased assumptions, despite improvements to the underlying models. And a misplaced confidence leads users to trust answers generated by AI tools when they shouldn't. To better understand other potential pitfalls for personal AI agents, let's break the nebulous term into two distinct categories: those that feed you and those that represent you. Feeding agents are algorithms with data about your habits and tastes that search through swaths of information to find what's relevant to you. Sounds familiar, right? Any social media recommendation engine filling a timeline with tailored posts or incessant ad tracker showing me those mushroom gummies for the thousandth time on Instagram could be considered a personal AI agent. As another example from the '90s interview, Maes mentioned a news-gathering agent fine-tuned to bring back the articles she wanted. That sounds like my Google News landing page.