#ai-agents

#ai-agents

From crafting replies that sound just like you to handling high volumes of DMs, comments, and mentions, the Jotform Instagram Agent promises to save time while strengthening your connection with your audience. Curious how it adapts to your unique communication style or integrates with platforms beyond Instagram? Let's uncover how this AI redefines what it means to stay engaged in the digital age. Sometimes, the best way to be present is to let technology amplify your voice.

Microsoft announced in August 2025 that support for the Model Context Protocol (MCP) is generally available in Visual Studio. MCP enables AI agents within Visual Studio to connect to external tools and services via a consistent protocol. The announcement notes that Visual Studio now provides new means to configure and manage MCP servers. MCP, introduced by Anthropic in 2024, is an open standard that simplifies interactions between AI‑enabled development workflows and external systems such as databases, code search engines and deployment pipelines.

"AI represents a rare, once-a-decade opportunity to rethink what a browser can be," OpenAI's CEO said yesterday when announcing the company's latest product: ChatGPT Atlas. In this new AI-powered browser, ChatGPT becomes the central mechanism for surfing the internet. From any webpage in Atlas, you can click an "Ask ChatGPT" button to open a side conversation with the chatbot. Want cooking inspiration? Atlas can pull from recipes you've recently viewed through its "browser memories" feature.

LangChain raised $125 million at a $1.25 billion valuation, the company announced on Monday. TechCrunch reported in July that the provider of a popular open source framework for building AI agents was raising fresh funds at a valuation of at least $1 billion. The deal was led by IVP, as we previously reported. New investors CapitalG and Sapphire Ventures joined in, as did existing investors Sequoia, Benchmark, and Amplify.

"They just don't work. They don't have enough intelligence, they're not multimodal enough, they can't do computer use and all this stuff," he said. "They don't have continual learning. You can't just tell them something and they'll remember it. They're cognitively lacking and it's just not working."

The American dream is "life, liberty, and the pursuit of happiness" but, in practice, it has always been about ownership. Sadly, the dream of ownership is slowly slipping away for many people. Harvard University's 2025 Youth Poll found that three-quarters say they want to own a home, but barely half think they ever will. Ownership feels increasingly out of reach.

A vertical agent is more than a chatbot. It's a core part of the martech stack, built with autonomy, context and memory to drive business goals. Vertical agents are powered by the LLM of choice but are trained on a company's catalogs, knowledge base, policies, and brand tone - all centralized in a unified data source. They: Embody the roles a brand requires (i.e., sales, support, etc.). Understand industry language. Adapt across multiple languages. Deliver credible responses.

Problem: If your pricing is tied to human users, but AI is doing the work, you're leaving money on the table (or worse, annoying customers with irrelevant seat counts). Reality: Customers don't care about seats. They care about results. Manny's take: "Don't sell software. Own outcomes." If your product helps a customer resolve 1,000 support tickets a month, why charge for seats? Charge for resolved tickets.

Around the middle of last year, Pim de Witte started reaching out to a handful of prominent AI labs to see if they'd be interested in using data from Medal, his popular video game clipping platform, to train their agents. Within weeks, it became clear that Medal's data was more valuable to the labs than he expected. "We received multiple acquisition offers very quickly," he told me.

Regarding AI agents, the survey found ambition was outpacing readiness. Overall, 83% of organisations planned to deploy AI agents, and nearly 40% expected them to work alongside employees within a year. But the study discovered that, for majority of these companies, AI agents were exposing weak foundations - that is, systems that can barely handle reactive, task-based AI, let alone AI systems that act autonomously and learn continuously.

A research team from Stanford University has released Paper2Agent, a framework that automatically converts scientific papers into interactive AI agents. The system, introduced in a recent paper, aims to make research methods more accessible by transforming traditional publications into dynamic entities that can execute analyses, reproduce results, and respond to new scientific queries through natural language interaction. Paper2Agent builds on the Model Context Protocol (MCP), a standard that allows large language models to connect with external tools and datasets.

In an ever-changing world of U.S. tariffs, shifting trade policies, and rising geopolitical tensions, businesses are forced to make decisions at an expedited pace. AI is here to help: streamlining some productivity and allowing businesses and their leaders to gather and summarize information at a faster clip. That's why Hanneke Faber, the CEO of global tech manufacturing company Logitech, said she'd be open to the idea of having an AI-powered board member.

However, AWS hasn't just made another drag-and-drop agent builder. The e-commerce giant is also using generative AI models to help users plan out and create automated workflows that take advantage of tools such as LLMs in a matter of minutes. For example, Amazon's Quick Flows is designed to automate routine tasks by allowing the user to explain what they're trying to accomplish and what the deliverable should look like. Meanwhile, Amazon's Quick Automate is similar in concept but is designed to support more complex projects.

That's where Knapsack comes in. It's a collaboration platform specifically designed for enterprises that need to resolve misunderstandings between UI designers, product managers, and engineers. Knapsack creates a unified workspace that connects with tools like Figma and Git, ensuring that any design changes are automatically updated in the code and documentation. This approach makes sure that everything remains up to date, so branding stays consistent across all digital products.

Slack believes it has a gold mine of data. According to the company, the conversation data between employees is said gold needed to feed AI with the right context. That data is now available within Agentforce, but also to third parties. In recent years, there has been a race to build the best LLMs and have sufficient computing power to enable AI. The latter has been achieved, and now it is time to collect the right data and context and feed it to AI agents.

Atlassian wants to help customers in multiple ways with Rovo AI. There is Rovo Search, Rovo Chat, and Rovo Studio. Today, these three areas are naturally linked to a growing range of AI agents. The search function searches more than 50 connected apps, from Jira and Confluence to external tools. The chat function uses company data to answer questions. In Rovo Studio, teams can build their own agents. This is done in plain language, without programming.

All those (AI) agents need management, automation, scalability control, maintenance, testing and orchestration. This was the central remit that CamundaCon set out to explore. Camunda's process orchestration and automation conference was held this month at the Sheraton New York Times Square Hotel. With end-to-end orchestration in its sights, did the company manage to deliver on its promise of "AI with no BS" (as the banner read on the hotel exterior) or would this event fuel more of the AI hype-cycle?

The $100T world of B2B commerce operates in a "Wild West" where businesses provide goods and services first and chase payment later - often for months. Despite decades of software innovation, the accounts receivable process still depends on millions of finance professionals manually sending emails, tracking down contacts, answering invoice questions, and reconciling incomplete payment data. With 57% of invoices paid late and 77% of AR teams falling behind, this communication and negotiation bottleneck has become one of the most persistent inefficiencies in the modern economy.

Hi everyone, my name is Srini Penchikala. I am the lead editor for AI, ML and data engineering community at infoq.com website and I'm also a podcast host. Thank you for tuning into this podcast. In today's episode, I will be speaking with Elena Samuylova, co-founder and CEO at Evidently AI, the company behind the tools for evaluating, testing and monitoring the AI powered applications.

The launches see new agents designed to make human-AI collaboration a reality; an operating system for collaboration devices with RoomOS 26, powered by Nvidia, to deliver agentic capabilities for users and IT; a Microsoft Device Ecosystem Platform (MDEP) to enhance security on Cisco devices running Microsoft Teams Rooms; and Webex Suite integrations including Amazon Q index, Microsoft 365 Copilot and Salesforce for agentic workflow automation.

What if you could delegate your most time-consuming tasks to a team of tireless, hyper-efficient assistants, all without hiring a single person? Enter Perplexity Comet, an innovative AI-powered browser that's reshaping how professionals approach their daily workflows. With its ability to handle everything from real-time competitor analysis to SEO optimization, this tool doesn't just automate, it transforms. Imagine a world where your research organizes itself, your sales leads find you, and your content practically writes itself.

You ask Claude Code or Cursor about a shadcn/ui component, and it'll confidently spit out props that don't exist, dust off patterns from 2023, or just flat-out make things up. Most of the time, this comes down to version changes. shadcn/ui keeps evolving, new props, updated requirements, and agents often lean on older docs or outdated patterns. Other times, it's simply the AI guessing.

Identity and access management (IAM) provider Descope has announced raising $35 million in a seed funding extension that brings the total raised by the company to $88 million. The cash infusion came from existing investors Cerca Partners, Dell Technologies Capital, Lightspeed Venture Partners, Notable Capital, Triventures, and Unusual Ventures. Founded in 2022, the Los Altos, California-based startup landed a large $53 million seed funding round in 2023, aiming to disrupt the customer identity and authentication market.

The picture the company paints of the modern office worker is someone who's juggling a growing number of AI systems -- as more get added, it becomes increasingly difficult to manage them all. Instead, ServiceNow is offering to help by telling those workers to simply drop the juggling act and let their own AI software pick up where they left off.

Life sciences leaders are increasingly adopting AI and AI agents to address growing industry disruption. This shift is occurring as the sector confronts new regulatory demands that strain compliance teams, increasingly complex clinical trials, and rising expectations from healthcare professionals. A recent Salesforce study revealed that life sciences leaders see AI as a powerful tool for navigating these challenges, with 94% expecting AI agents to be critical for scaling organizational capacity and strengthening operations.

AI agents are steadily becoming embedded in enterprise workflows: automating customer interactions, coordinating operations, and reasoning across complex datasets. However, if you take a closer look beneath the surface, many organizations are struggling with the technical challenge of supporting them in real time. Legacy data architectures aren't built for this. To make agents performant, scalable, and accountable, IT leaders are turning to something familiar, but more flexible: NoSQL.