#agentic-ai

#agentic-ai

Accenture is betting that the future of retail will run through AI with an investment in Profitmind, an agent-based platform that automates pricing decisions, inventory management, and planning. "Profitmind bridges the gap between insight and action through agentic AI," Accenture global retail lead Jill Standish said in a statement that announced Accenture's buy in. "It mirrors how retailers run their businesses, linking data from multiple sources for clear, prioritized recommendations that can be trusted and executed quickly in response to an increasingly competitive industry."

On Tuesday, Walmart execs said they would put ads in Sparky, its AI shopping agent, as well as provide generative AI-powered performance insights and creative. There's also Marty, Walmart's agentic advertising assistant, in beta for sponsored search campaigns to help with billing and bidding, with plans to make it available widely later this year. The announcements come on the heels of Walmart's tests last year with Sparky and Marty.

Reddit has launched an AI-powered media-buying tool designed to automate core aspects of advertising on its platform, including audience targeting, bidding, and creative optimisation. The product, called Max Campaign, is positioned as a way to attract performance-focused advertisers while responding to ongoing concerns around transparency in automated advertising tools. Integrated into Reddit Ads Manager, Max Campaigns is intended to simplify how brands plan, set up, and run campaigns.

Behind the scenes at GSMArena HQ, it was just as busy. Testing devices, digging into specs, breaking news as it happens, and turning complex PR terminology into clear, useful information for millions of readers and viewers around the world. In terms of numbers, we added over 780 new devices to our database and published nearly 5,000 news articles. The review team explored over 140 smartphones and tablets in our usual detailed format,

The deal is sure to turn heads too. Manus and its parent company Butterfly Effect are now based in Singapore but were founded in China - a country with a fraught relationship to the U.S tech industry - and maintain operations there. Facebook's parent company will reportedly pay more than $2 billion to acquire the startup, which it hopes will bolster its own lagging AI capabilities.

In this episode, our managing editor Allison Schiff interviews Paul Longo, Microsoft's GM of AI in ads. They discuss the ways AI will transform advertising, from the use of AI technology to create advertising, which Microsoft is doing, to how advertising will become part of agentic AI experiences. (As a writer myself, I also enjoyed hearing him talk about experimenting with AI in some of his work as a screenwriter.)

The problems to solve (and the cost to solve them) jump exponentially at each level, and we posit that, just like fully autonomous self-driving cars at level five that can operate anywhere, we are a far way off from seeing level five agentic AI operating at the "PhD" level as Sam Altman describes it. And the authors both firmly believe that LLMs are not the architecture to get us to level five, but that is a discussion for a separate post.

The aim of the AAIF is to provide a neutral organization to encourage open-source agentic AI technologies and secure long-term community support of projects. Besides the three members contributing founding projects, the foundation's Platinum members are Amazon Web Services (AWS), Microsoft, Bloomberg, Cloudflare, and Google. Dozens of other tech companies have joined as Gold and Silver members. Silver member Obot.ai has donated their MCP Dev Summit events and podcast to AAIF.

AI startups are a bit like podcasts. Which is to say, everyone seems to have one. So how does an AI startup stand out amid so much noise? There's no simple formula for standing out. But, for many founders, the key is a personal connection to the problem their startup aims to solve. That and a belief that humans should stay at the steering wheel, even when the systems run agentically.

For the better part of 2025, agentic AI has been the industry's buzzword. It's defined as "a situation where multiple AI agents work together to complete complex tasks, with minimal oversight or intervention from a human user," as Digiday explains it. The minimal oversight from a human user, however, seems to be the hangup keeping marketers from embracing agentic AI's full autonomy.

In 2026, retailers are facing a major upheaval not only in how customers buy but also in who is actually doing the choosing. With the rise of AI agents, and social platforms continuing to blur the line between shopping and entertainment, capturing the customer's attention and proving that you are a trustworthy place to shop is going to become critical to continued success in retail. The common thread is trust.

While new models with more parameters and better reasoning are valuable, models are still limited by their lack of working memory. Context windows and improved memory will drive the most innovation in agentic AI next year, by giving agents the persistent memory they need to learn from past actions and operate autonomously on complex, long-term goals. With these improvements, agents will move beyond the limitations of single interactions and provide continuous support.

His central message was that reliability comes from combining probabilistic components with deterministic boundaries. Erickson argued agentic AI becomes more interesting when it is treated as a layer over real operational systems rather than a replacement for them. The model can interpret questions, retrieve evidence, classify situations, and suggest actions. Deterministic systems execute the actions, enforce the constraints, and provide the telemetry that allows the whole loop to be evaluated.

Scott Brinker's Martech for 2026 report offers a lucid map of the terrain GTM teams must now navigate: a marketplace no longer defined by sequential buyer journeys, increasingly shaped by agentic AI, destabilized by volatility and governed by nonlinear patterns of evaluation and decision-making. Yet during the same period in which martech blossomed into a sophisticated, multi-layered discipline, GTM effectiveness collapsed.

OpenAI has released GPT-5.2-Codex, a new version of its agentic AI model for software development that focuses specifically on professional software engineering and cybersecurity. The model builds on GPT-5.2 but has been further optimized to work independently within complex development environments. With this release, OpenAI is positioning Codex not just as a programming assistant but as a broader support technology for the entire software development process.

Test-time scaling for AI agents is increasingly shifting from longer thinking to controlling tool calls. In many practical applications, such as web search and document analysis, the number of external actions determines how deep an agent can dig. Each tool call increases the context window, increases token consumption, and incurs additional API costs. For companies, this can quickly add up.

Big Tech has spent the past year telling us we're living in the era of AI agents, but most of what we've been promised is still theoretical. As companies race to turn fantasy into reality, they've developed a collection of tools to guide the development of generative AI. A cadre of major players in the AI race, including Anthropic, Block, and OpenAI, has come together to promote interoperability with the newly formed Agentic AI Foundation (AAIF). This move elevates a handful of popular technologies and could make them a de facto standard for AI development going forward.

The three companies are also transferring ownership of some widely used agentic technologies over to the foundation. This includes Anthropic's Model Context Protocol (MCP), which allows agents to connect and interact; OpenAI's Agents.md, which lets programs and websites specify rules for coding agents; and Goose, a framework for building agents developed by Block. These technologies were already free to use, but through the new foundation it will be possible for others to contribute to their development.

When I read it, I'm like, 'Oh my gosh, this actually is real data [for] the conversations I'm having where, 'Yeah, we bought all these Chats and Claudes and Geminis and people can summarize their emails and look up stuff in their calendar and help me write a nice letter.' But is that real work? It's not.

"We had a clear choice - be the last airline built on legacy technology or be the first built on the platforms that will define the next decade of aviation," said Adam Boukadida, chief financial officer of Riyadh Air. "With IBM, we've stripped out 50 years of legacy in a single stroke. Riyadh Air isn't just built for today; it's built for the future and creating a pathway for many airlines to follow in the years to come."

It's the big trend that's taken the tech industry by storm over the last year, and truth be told, I'm at the point where I've covered the topic so much that I'm dealing with a severe case of semantic satiation. AWS announced a new class of agents at its annual re:Invent conference last week. Known as " frontier agents ", these are more powerful, intuitive, and better equipped to deal with extended periods of operation than the first generation of agents.

Amazon's Nova 2 announcement at AWS re:Invent 2025 is exactly the type of AI offering we expected from AWS and, frankly, exactly what should make thoughtful architects nervous. Nova 2 is positioned as a frontier-grade model, tightly integrated with Amazon Bedrock. It's part of a growing ecosystem of "frontier agents" and the AgentCore framework unveiled at re:Invent 2025. The story is compelling: better models, better tools, and a single platform to build, deploy, and scale agentic AI.

I was asked about this in the wake of Salesforce's recently completed $8 billion acquisition of Informatica. In part, I believe that people are paying attention because deal-making is up in 2025. M&A volume reached $2.2 trillion in the first half of the year, a 27% increase compared to a year ago, according to JP Morgan. Notably, 72% of that volume involved deals greater than $1 billion.

At the low end, this looks like the "deep research" tools AI firms have already released that search the web and synthesize information on your behalf, attempting to automate the task of using Google. More theoretically, it might mean models trained to use productivity software in a work context, which may then be used to attempt to automate increasingly complicated jobs.

Picking up another 20%+ total return next year will likely hinge on valuation improvement for most stocks (especially the mortgage REITs), however we're optimistic there could be some earnings torque in the servicers as a function of AI-driven workflow helping trim expenses, which we think is only partly reflected in valuations, he added. BTIG covers 20 companies in the mortgage sector. As a group, they are expected to originate $750 billion in 2026, representing a 12% year-over-year increase.

My dear friend Jack Ellis is an unending source of founder inspiration. Not only has he recently started embracing AI agentic coding-something he's been holding back on for quite a bit. I think I've mentioned several times on this podcast alone how he and I seem to have quite opposing views on embracing this technology. But something has clicked, and he's been diving headlong into it. So over the next couple months, hopefully he'll explore it more, and after that, I've been trying to get him to come on this podcast and talk about his experiences. Let's give him time to explore it fully.

"Snowflake's most strategic partnerships are measured not just in scale, but in the depth of innovation and customer value that we can create together," he said. "Anthropic joins a very select group of partners where we have nine-figure alignment, co-innovation at the product level, and a proven track record of executing together for customers worldwide. Together, the combined power of Snowflake and Claude is raising the bar for how enterprises deploy scalable, context-aware AI on top of their most critical business data."

AWS claims the vibe coding IDE Kiro is designed to avoid all the pitfalls of letting AI do your development, like surprise drive deletions and database wipeouts. Users will have to put a lot of trust in those claims. Aside from those worst-case scenarios, AWS is fully aware that AI coding tools have "introduced new friction" into developers' workloads. "You can find yourself acting as the human 'thread' that holds work together," AWS said, describing scenarios like contextualizing tasks, manually coordinating cross-repository changes, and collating information across tickets and pull requests.