#ai-agents

#ai-agents

Software engineering didn't adopt AI agents faster because engineers are more adventurous, or the use case was better. They adopted them more quickly because they already had Git. Long before AI arrived, software development had normalized version control, branching, structured approvals, reproducibility, and diff-based accountability. These weren't conveniences. They were the infrastructure that made collaboration possible. When AI agents appeared, they fit naturally into a discipline that already knew how to absorb change without losing control.

A year-and-a-half ago, management consulting firm McKinsey had just 3,000 AI agents in its possession, with its 40,000 employees far outnumbering its agentic fleet. But in just 18 months, that number has grown more than 500% to about 20,000 AI agents supporting the company's work, CEO Bob Sternfels said on Harvard Business Review's Ideacast. Now, the company is evaluating how well job candidates can work with its AI tool as part of the interview process.

I attended the convention, held in New York City from January 11 to 13, for the first time tohear from industry insiders about the retail trends to watch in 2026. This year's event drew speakers such as Walmart's incoming CEO John Furner and Google CEO Sundar Pichai, who announced a new AI deal this week, as well as Fanatics CEO Michael Rubin. It was clear that artificial intelligence was the big topic on the minds of the attendees from over 5,000 brands at the event.

Update January 9, 2026: Although the acquisition amount has not been disclosed, we do know that Snowflake has purchased the ITOM platform Observe. Before the deal was finalized, Snowflake had already considered adopting Observe, the company told The Register. Now, the company can not only offer observability functionality to customers, but also apply it itself. However, the emphasis is on preventing downtime and the loss of important data for users of the Snowflake platform.

The 29-year-old told Business Insider that he waited over an hour on the phone to book an appointment with an orthopedist, and then two weeks for insurance to approve his MRI scheduling. Frustrated with the pace of the healthcare system, Seelamsetty cofounded the AI agents startup Tivara with Aumesh Misra. The company promises to answer patient phone calls, handle scheduling and refills - and cut down the hours of grunt work that comes with a medical visit.

In organizations with mature processes, this demonstrably leads to a 30 to 50 percent reduction in mean time to respond. This is not an optimization, but a necessary adjustment. The question is no longer whether AI agents will be deployed, but how far their autonomy extends. Security teams must explicitly determine which decisions can be automated and where human oversight remains mandatory. If these frameworks are lacking, the risks only increase.

In practice, Lemkin, the founder of SaaStr, the world's largest community of business-to-business founders, said on Lenny's Podcast recently that this means he will stop hiring humans in his sales department. Instead, SaaStr is going all in on agents, which are commonly defined as virtual assistants that can complete tasks autonomously. They break down problems, outline plans, and take action without being prompted by a user.

A lot of mega-cap tech titans are ending off 2025 on a high note with big acquisitions. Meta Platforms ( NASDAQ:META) joined in the year-end deal-making spree by buying up AI agent startup Manus in a deal reportedly worth over $2 billion. Undoubtedly, Manus is an incredible technology that's already gained quite the following, with around $100 million in annual recurring revenue.

"This is not just risky; it's unsustainable," he writes. "By 2026, the demand for robust frameworks and private environments to ensure stability and control will be undeniable. Running models locally-on-premises or in controlled AI factories-will become the norm to provide a stable foundation and insulate organizations from external disruptions. But this is more than a prediction. It's an urgent appeal."

Manus debuted in March 2025 and immediately pitched itself as a leap beyond generative AI chatbots, which it characterizes as best suited to summarizing information and answering questions. The outfit promotes its own services as enabling "wide research and context-aware reasoning to produce actionable results in the format you need." To illustrate that promise, Manus offers a scenario in which users ask its tech to select the best candidate for an job by evaluating job applications stored in a .ZIP file.

For years, the cost of using "free" services from Google, Facebook, Microsoft, and other Big Tech firms has been handing over your data. Uploading your life into the cloud and using free tech brings conveniences, but it puts personal information in the hands of giant corporations that will often be looking to monetize it. Now, the next wave of generative AI systems are likely to want more access to your data than ever before.

Every executive I speak with wants to deploy AI agents in their business. Yet most are making the same costly mistake: choosing the wrong tasks to automate. In my previous article, A Beginner's Guide To Building AI Agents, I explained how to get started with agentic AI. Now it's time to tackle the most critical step: finding the right jobs to use them for. Get this wrong, and you'll waste time and money. Get it right, and you'll transform how your business operates.

Amazon ( NASDAQ:AMZN) has been a quiet laggard in the Magnificent Seven this year after gaining just over 3% year to date. With just a few trading days left in the year, it's looking like the $2.45 trillion e-commerce juggernaut is about to disappoint yet again, despite all the encouraging AI projects going on behind the scenes, from "frontier" AI agents to those impressive Trainium3 AI chips, the rollout of Alexa+, and let's not forget about the warehouse robots.

In late 2025, Mark Karpelès, ex CEO of Mt. Gox, lives a quieter life in Japan, building a VPN and an AI automation platform. As Chief Protocol Officer at vp.net-a VPN that uses Intel's SGX technology to let users verify exactly what code runs on servers-he works alongside Roger Ver and Andrew Lee, the founder of Private Internet Access. "It's the only VPN that you can trust basically. You don't need to trust it, actually, you can verify".

David Cohen, Chief executive of the Interactive Advertising Bureau (IAB), has climbed onto the dangerous prediction limb, with his 2026 Predictions, oppulently titled Search Takes a Backseat as Brands Battle Inside AI's Black Box. AI seems to be top-of-mind, as four of the predictions (including the top three) focus on artificial intelligence. We will spill those top three below, but leaving out the editorial content which accompanies each of his forecasts:

Last week, Google DeepMind made the Interactions API available as a public beta. The new API represents a fundamental change in how developers work with AI models: from stateless to a stateful architecture with server-side context management. With this move, Google is following the path that OpenAI embarked on in March 2025 with its Responses API. Over the past two years, developers have been working with generative AI via a so-called 'completion' model.

Something new is now taking shape on the factory floors. AI agents, independent, context-aware and task-oriented, are functioning as a third layer of intelligence. Not a replacement for what came before, but a layer that complements and elevates it. These agents are not confined to a single screen or workflow. They move between systems, interpret context via semantic data, and solve problems across functional boundaries.

ODSC's Ai X Podcast had a busy year with 50 published episodes! Over the year, we discussed everything from the latest AI agent to enterprise AI strategies for implementing said agents. We spoke with researchers, academics, practitioners, and AI leaders for hundreds of hours over the year, and we're thrilled that you took the time to listen and comment on them. Looking back on the year, here are the top ten most listened to AI podcast episodes, and the common themes that we found.

the one thing I have become most convinced of is that product teams are really in a unique position to unlock AI value for their organizations.