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AI coding agents are suddenly everywhere, the latest thing Silicon Valley cannot stop talking about. From venture-backed startups to splashy big tech keynotes, the promise sounds the same: just describe what you want, and the AI will build it for you. It is a seductive idea, especially in a world where software projects are notorious for moving slowly. But inside large companies, that vision is already starting to unravel. What looks impressive in a demo often falls apart in the real world. As soon as AI-generated code runs into actual enterprise data, the problems show up. Schemas clash, governance breaks down, and a supposed breakthrough can quickly turn into a liability. Coding agents tend to break down when theyre introduced to complex enterprise constraints like regulated data, fine-grained access controls, and audit requirements, Sridhar Ramaswamy, CEO of Snowflake, tells Fast Company. He says most coding agents are built for speed and independence in open environments, not for reliability inside tightly governed systems. As a result, they often assume they can access anything, break down when controls are strict, and cannot clearly explain why they ran a certain query or touched a specific dataset. This gap between what AI can write and what it actually understands is becoming one of the most expensive problems in enterprise AI. Gartner predicts that 40% of agentic AI projects will be canceled by 2027 because they lack proper governance, and only 5% of custom enterprise AI tools will ever make it into production. Ramaswamy says the core issue in enterprise AI is writing functional code in a way that is secure, transparent, and compliant from the start. He argues that companies need to put trust, accuracy, and accountability ahead of unchecked automation, and that most coding agents today sit outside existing data governance systems instead of being built into them. Snowflakes answer is Cortex Code, a data-native AI coding agent designed to work directly inside governed enterprise data, not as a layer sitting on top of it. It comes alongside with a newly announced $200 million partnership with OpenAI. Together, they reflect a contrarian bet that the real battle for enterprise AI will be won at the data layer. AI Coding Agents Dont Understand Enterprise Context Most AI coding agents are great at writing code on their own, but they struggle once that code has to run inside a real company. Large organizations live with constant constraints, from security rules and uptime demands to shared business logic that evolves over time. Agents trained mostly on public code and synthetic examples rarely absorb those realities, and the disconnect shows up almost right away. Enterprise data also lives across data warehouses, third-party platforms, and legacy systems, and it carries layers of organizational meaning with it. Most coding agents treat that data like any other dataset, instead of the most tightly regulated asset a company has. The fallout shows up fast in production. Some enterprises say they spend weeks cleaning up AI-generated code that ignores internal data standards. In production, agents most often fail due to poor data integration, lax identity and security permissions, and hallucination for complex code workflows,” says Arun Chandrasekaran, vice president and analyst at Gartner. “Vendors often underestimate the gap because they assume that enterprises have centralized data and codified access policies, which isnt true in most large enterprises. Chandrasekaran adds that AI agents are embedded into developer IDEs without grounding in enterprise system semantics, which is the key reason why this issue persists. This can result in trust erosion and security exposure,” he says, “which can hinder production. According to a CodeRabbit study, AI-generated code introduces 1.7 times more issues than human-written code, including 75% more logic errors and up to twice the security vulnerabilities, conflicting with enterprise standards. Likewise, another study found that 45% of AI-generated code samples fail security tests, posing critical web application security risks. Ramaswamy says the most immediate consequence is slowed development. In some cases, teams quietly abandon agents altogether after early pilots fail governance checks. Even when the consequences are minor in nature, the perception of risk alone can cause organizations to roll back or freeze AI initiatives until stronger guardrails are in place, he says. According to Anahita Tafvizi, Snowflakes chief data analytics officer, this pattern points to a deeper design problem: Many coding agents can generate technically correct code, but they do not understand how business rules are applied, how access controls limit what is allowed, or how audit requirements determine whether a system can actually be trusted once it goes live. Meaningful enterprise innovation depends on context, she says. When an agent understands not just how to write code, but why certain controls exist and how decisions are governed, teams can build with confidence. Snowflakes Thesis: Context Beats Cleverness Snowflakes latest product, Cortex Code, is a data-native AI coding agent built directly into its governed data platform, rather than layered on top of it. That distinction matters. Instead of trying to guess enterprise rules from prompts, Cortex Code is designed with built-in awareness of schemas and operational constraints. The company says the goal is to make AI follow the same rules people already do. Ramaswamy says Cortex Code is not just about producing code faster than tools like Claude Code, but about understanding the realities of enterprise environments. Its value, he argues, comes from what he calls its deep awareness of the context and constraints that shape how large organizations operate, which allows a much wider range of employees to build solutions that are safe and reliable, even without advanced technical skills. Snowflake’s $200 million partnership with OpenAI further reinforces its architectural bet. Its a direct, first-party relationship that allows OpenAIs models to operate natively inside Snowflake, on top of enterprise data, Ramaswamy says. By bringing OpenAIs frontier model capabilities into Snowflake, we remove the operational friction of stitching together disparate tools and significantly lower the barrier to deploying advanced AI responsibly. An Inflection Point or a Higher Bar? Industry experts say that while Snowflake is making a big bet on a data-first approach with Cortex Code, it is far from alone. Rivals such as Databricks, Google BigQuery, and AWS Redshift are moving in the same direction, putting governance and auditability ahead of raw speed. Experts say Snowflakes main point of differentiation is how closely Cortex Code is tied to production data. As Doug Gourlay, CEO of data stoage company Qumulo, puts it, most companies have grafted increasingly capable agents onto developer tools and then tried to manage risk after the fact. Snowflake, he says, is flipping that model by treating governance and data semantics as the foundation on which AI operates. (While rivals excel in niche strengths like machine learning flexibility or platform scale, Cortex Code is built for teams that need governed, low-maintenance AI coding directly on live enterprise data.) Over time, this approach is likely to become table stakes. Enterprises will increasingly view AI that operates outside their governed data fabric as an unacceptable risk, regardless of how impressive its capabilities appear in isolation, says Gourlay. Coding tools such as Anthropics Claude Code, for instance, are largely optimized for developer-centric workflows, emphasizing controls like explicit change approvals and tight IDE integrations. Claude Code, in practice, requires being combined with additional governance layers or secure platforms for enterprise compliance. Snowflake and Anthropic recently partnered to enable the direct integration of Claude models into Snowflake Intelligence and Cortex AI, allowing its models to run inside Snowflakes governed data environment. Snowflake says its edge comes from working directly with enterprise metadata and semantic context. The company is betting that as organizations grow more cautious, they will turn away from agents that appear powerful but act unpredictably. If that proves true, those who ignore data context may define todays hype, while those who embrace it will shape what comes next.
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What can viewers expect from Bad Bunny’s highly anticipated Super Bowl halftime performance? So far, all we know is that he’s expected to perform solely in Spanish, bringing Latin identity at the center of America’s most-watched television event.But Bad Bunny could reveal more details Thursday in San Francisco when the Grammy winner speaks ahead of Sunday’s game.Apple Music’s Zane Lowe and Ebro Darden will interview Bad Bunny and pregame performers beginning at 10 a.m. Pacific time on Thursday. The Puerto Rican superstar has become one of the world’s most streamed artists with albums such as “Un Verano Sin Ti” and “Debí Tirar Más Fotos,” which won album of year at Grammys Sunday night. It’s the first time an all Spanish-language album has taken home the top prize.Last year, Bad Bunny’s historic Puerto Rico residency drew more than half a million fans.Apple Music will broadcast the interview on its platform and social media sites like YouTube and Facebook.The pregame media session might reveal some details about the performance, but headliners often keep a few secrets. Rihanna sure did, waiting until her Super Bowl performance in 2023 to reveal she was pregnant with her second child.The Super Bowl will be held Sunday at the Levi’s Stadium in Santa Clara, with the Seattle Seahawks facing off against the New England Patriots. Who else is performing at the Super Bowl? The Super Bowl pregame show will open with several standout performers in Northern California: Charlie Puth will hit the stage to sing the national anthem, Brandi Carlile will take on “America the Beautiful” and Coco Jones will sing “Lift Every Voice and Sing.”The national anthem and “Lift Every Voice and Sing” will be performed by deaf performing artist Fred Beam in American Sign Language. Julian Ortiz will sign “America the Beautiful.”Before the game, Green Day will play a set to celebrate the 60th anniversary of the Super Bowl. The band, which has its roots in the Bay Area, plans to “Get loud!” according to lead singer Billie Joe Armstrong.In a historic first, the halftime show will include a multilingual signing program featuring Puerto Rican Sign Language, led by interpreter Celimar Rivera Cosme. All signed performances for the pregame and halftime shows will be presented in collaboration with Alexis Kashar of LOVE SIGN and Howard Rosenblum of Deaf Equality. For more on the Super Bowl, visit https://apnews.com/hub/super-bowl Jonathan Landrum Jr., AP Entertainment Writer
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Its a hard time to be an XRP investor. The token, the fifth-largest cryptocurrency by market cap, has been on a downward trajectory for nearly half a year. And this week, things have gotten much worse. Heres what you need to know about XRP and the beating the coin is taking. Whats happened? The price of XRP is getting pummeled today. In the last 24 hours, the tokens value has plunged nearly 14.5% as of the time of this writing, falling from above $1.50 per coin to around $1.36. And thats just the most recent price shock for the coin. Looking back over the past month, XRP is down more than a staggering 41%, according to Yahoo Finance data. On January 5, the coin was trading as high as $2.41. Even more astounding: XPR topped $3.60 a coin in July 2025, meaning it’s now down more than 60% from its summer high. For XRP investors, the tokens fall over the past six months is difficult to stomach. Many had high hopes for the rising cryptocurrency star, especially after Donald Trump entered the White House for a second term last January, leading an administration seen as very crypto-friendly. Why is XRP falling? It’s important to note that XRP is not the only token that has been hit hard in the past several months. Most major cryptocurrencies are on the decline as of late, including Bitcoin (down nearly 25% in the past month), Ethereum (down 35%), and BNB (down 25%). As Fast Company previously reported, two main factors are driving the fall of cryptocurrencies this year. The first is the renewed strength of the U.S. dollar (USD). At the end of last month, President Trump announced his pick for the new chair of the Federal Reserve, Kevin Warsh. The news sent the U.S. dollar surging. But because cryptocurrencies are generally priced in U.S. dollars, a stronger dollar means more tokens can be bought with the same amount of fiat currency, making them appear cheaper and thus lessening their value. The rising dollar has led to a selloff in some cryptocurrencies as investors try to protect their digital gains before they fall further. And then there is the seemingly unending geopolitical uncertainty rocking the world, most of it spurred on by Trump himself. First it was Americas attack on Venezuela, then it was Trumps threats to take Greenland from Americas allies by force, and now its the possibility of military strikes on Iran. All this geopolitical uncertainty breeds risk, and increased risk typically sends investors into safe-haven assets: typically gold or U.S. dollars. Given that cryptocurrencies are historically highly volatile, the digital coins are seen as anything but a safe haven. Ripple comments anger XRP ardents Given that XRP is the fifth-largest cryptocurrency by market cap, its no surprise the digital token has a large number of ardent supporters behind it. Recently, some of those supporters were angered by comments made by David Schwartz, CTO emeritus of Ripple. Ripple is a private company that offers software to financial institutions that facilitate international money transfers. Ripple is also the largest owner of XRP tokens in the world. This connection is one of the reasons why some supporters of XRP may have been angered by online comments that Schwartz had made earlier this month. As noted by Benzinga, Schwartz said he thought it was unlikely XRP would ever hit the $50 to $100 price range. But Schwartz noted that his past predictions had been wrong before. While Schwartzs comments dont seem to be a big driver of XRPs price in either direction, they may have contributed to fears that astronomical gains for the coin are out of reach for the foreseeable future. Indeed, as CoinDesk reports, XRP is now at its lowest level since October 2024wiping out all the gains it had achieved after the crypto-friendly Trump administration returned to office. And now there are fears that the token may fall to the $1 mark if its trajectory does not change course. Whether that actually happens remains to be seen.
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