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Artificial Intelligence vs Virtual Intelligence: Complete Comparison Guide Neeraj Mishra The Crazy Programmer

Artificial Intelligence (AI) and Virtual Intelligence (VI) may seem like identical terms, yet they are meant to fulfil different purposes and work differently. With the increasing investment in smart technologies by businesses to enhance efficiency, customer service, and decision-making, there will be differences between these two approaches that should be identified. As a business leader, seeking a solution among digital tools, as an entrepreneur, creating a tech product, or a marketer, thinking about AI and having to make a better decision, it can be helpful to understand how these technologies operate. Now, we can take a more in-depth look at AI and VI, their functioning, their usage in general, and how they can be leveraged to benefit businesses. Aspect Artificial Intelligence (AI) Virtual Intelligence (VI) Core Purpose Enables machines to think and learn Enables machines to interact and ...

Xcode 26.3 adds agentic coding support

Apple is enabling agentic coding within Xcode in the latest version of the development platform (version 26.3). Developers will now be able to use Anthropic’s Claude Agent and OpenAI’s Codex directly in Xcode. “With seamless access to Claude Agent and Codex, developers can bring the advanced reasoning of these models directly into their app-building workflow. This connection combines the power of these agents with Xcode’s native capabilities to provide the best results when developing for Apple platforms, giving developers the flexibility to work with the model that best fits their project,” Apple wrote in an announcement . These agents will be able to do tasks like search documentation, explore file structures, update project settings, and verify work visually through Xcode Preview captures, the company explained. “With agentic coding, Xcode can work with greater autonomy toward a developer’s goals — from breaking down tasks to making decisions based on the project architecture an...

The Shift from Chaos to Controlled Reliability Testing

Chaos engineering, the practice of proactively injecting failure to test system resilience, has evolved. For enterprises today, the focus has shifted from chaos to reliability testing at scale. “Chaos testing, chaos engineering is a little bit of misnomer,” Kolton Andrus, founder and CEO of Gremlin , told SD Times about the term with which he launched the company. “It was cool and hot for a little while, but a lot of companies aren’t really interested in chaos. They’re interested in reliability.” For large enterprises, disaster recovery testing—such as a data center evacuation or testing the failure of a cloud region—is a massive undertaking. Customers have spent hundreds of engineering man-months to put these exercises together, resulting in infrequent tests. This leaves organizations vulnerable to risks that only appear under load. The new focus is on building scaffolding to make this testing repeatable and easy to run across a whole company by clicking a few buttons. Andrus...

Opsera introduces new DevOps agents to address AI-assisted coding issues

Opsera is releasing several new agents as a part of its Agentic DevOps offering that proactively manage DevOps workflows in an attempt to address some of the bottlenecks introduced by AI-assisted coding. According to a recent report from the company, AI-assisted coding can speed up metrics like Time-to-Pull Request or test pass rate, but it is also subject to bottlenecks that slow delivery down, such as longer PR review times. For example, the company found that AI-assisted workflows had a 48-58% faster average Time-to-Pull Request, but that AI-generated pull requests wait 4.6x as long to be reviewed compared to human-written ones. Opera also found that AI-generated code suffered from issues like increased code duplication (13.5% vs 10.5%) and security vulnerabilities (15-18% more) compared to human-written code. “Enterprises require a new approach to govern and manage the velocity of AI-driven development. Agentic DevOps addresses this challenge by introducing autonomous agents th...

Snowflake and OpenAI’s partnership, new insights in Google Play Console, and more — Daily News Digest

Snowflake and OpenAI announce $200 million partnership The two companies will work on building customized AI solutions for their joint customers. Additionally, OpenAI’s models will be natively available on Snowflake Cortex AI across the three major cloud providers, and will also be accessible through Snowflake Intelligence. “By bringing OpenAI models to enterprise data, Snowflake enables organizations to build and deploy AI on top of their most valuable asset using the secure, governed platform they already trust,” said Sridhar Ramaswamy, CEO of Snowflake. “Customers can now harness all their enterprise knowledge in Snowflake together with the world-class intelligence of OpenAI models, enabling them to build AI agents that are powerful, responsible, and trustworthy. Together, we’re setting a new standard for AI innovation, helping businesses transform with confidence, while maintaining strong security and compliance standards.” Android developers get access to new monetization insi...

Survey Says: Container Security Issues Continue to Befuddle Software Developers

Container security incidents are becoming more common, with nearly one in four respondents to a new survey from BellSoft saying they have experienced a security incident. The survey concluded that questions about security practices remain unresolved. According to the survey by OpenJDK provider BellSoft, 62% of participating developers reported that human errors were the biggest contributors to container security mistakes. Among the key findings in the report, BellSoft wrote, are: Developers ranked shells (54%) and package managers (39%) as the most essential tools inside the base container. Package managers present a particularly critical security concern, as they expand the attack surface both directly and by enabling runtime installation of additional unnecessary components. Combined with other non-essential tools, this creates substantial vulnerability exposure in production environments. A more practical approach is using hardened minimal runtime images, paired with fulle...

January 2026: AI updates from the past month

Coder creates AI Maturity Self-Assessment and AI Maturity Curve These new tools will enable software development teams to assess how effectively they have adopted AI. The assessment asks teams questions like how standardized their developer environment is, what their governance approach for AI is, how they handle risks like sensitive data exposure, and more. “As AI agents take on more responsibility inside engineering workflows, organizations need a clearer, more tangible way to understand maturity and governance readiness,” said Eric Paulsen, field CTO at Coder. “Without that baseline, it becomes difficult to scale agentic AI safely or predictably. Our self-assessment gives teams a concrete view of where they stand, so they can plan adoption intentionally, manage risk and scale with confidence.” Anthropic makes tools within Claude interactive Anthropic has announced that users will now be able to directly interact with certain tools within Claude. Claude already had the ability ...

m3ter launches m3sh Workflows to remove barriers to usage-based pricing

M3ter is attempting to make it easier for development teams to adopt usage-based pricing with the launch of m3sh Workflows, a new capability for automating processes between CRM and ERP systems. M3ter acts as an invisible infrastructure layer that provides usage data processing, complex rating, and automation of data flows between monetization systems, and m3sh Workflows gives additional control over how business processes are automated. It offers low- and no-code workflow automation capabilities, including visual workflow design with full API support. According to the company, m3sh Workflows supports advanced use cases such as loading and consolidating pricing and account data from multiple different CRMs, or automatically triggering the renewal of orders when conditions are met, like depleting a usage balance. “m3sh Workflows is key to our vision or automation, putting power in the hands of customers to build and manage automated workflows that connect their quote-to-cash system...

IaC platform formae adds multi-cloud support, Plugin SDK

Platform Engineering Labs announced that its open-source infrastructure-as-code (IaC) platform, formae , now has beta support for multiple cloud providers, including Google Cloud, Azure, Oracle Cloud, and OVHcloud. During this beta period, the core workflows function on these clouds, but not all resources are supported yet. The company said it will expand support based on the real usage it sees. “Public cloud support is table stakes for modern Infrastructure as Code, and mature ecosystems already exist around it. At the same time, cloud APIs are still complex in practice. Behavior differs across services, state transitions don’t always align, and correctness often depends on subtle provider-specific details. We consider it our responsibility to make the core cloud plugins reliable and predictable, so teams don’t have to rediscover the same edge cases over and over again,” the company wrote in a blog post . Additionally, the company added a Plugin SDK to enable users to extend formae...

Security lessons from AgentKit: Guardrails are not a get-out-of-risk-free card

OpenAI’s AgentKit marks a turning point in how developers build agentic AI workflows. By packaging everything, from visual workflow design to connector management and frontend integration, into a single environment, it removes many of the barriers that once made agent creation complex. That accessibility is also what makes it risky. Developers can now link powerful models to corporate data, third-party APIs, and production systems in just a few clicks. Guardrails have been introduced to keep things safe, but they are far from foolproof. For enterprises adopting agentic AI at scale, guardrails alone are not a security strategy; they’re the starting line. What AgentKit Guardrails Actually Do AgentKit includes four built-in guardrails: PII, hallucination, moderation, and jailbreak. Each is designed to intercept unsafe behavior before it reaches or leaves the model. PII Guardrail looks for personally identifiable information, names, SSNs, emails, etc., using pattern matching. Halluc...

Report: AI hallucinates 27% of upgrade recommendations for open source projects

Open-source adoption is being accelerated by AI and automation, but developers need to proceed with caution to ensure they’re not introducing extra risk into their software supply chain. Brian Fox, co-founder and CTO of Sonatype, explained that AI can accelerate good engineering, but it can also scale mistakes faster, especially if it doesn’t have real-world data to pull from. For example, if a model doesn’t know what versions exist or which ones have vulnerabilities, it predicts and fills in the blank, leading to upgrades to versions that don’t exist or recommendations that break builds. In its 2026 State of Software Supply Chain report , Sonatype analyzed over 1.2 million malicious packages, 1,700 vulnerability records, and 37,000 AI-driven upgrade recommendations. It found that AI models recommended over 10,000 non-existent versions, which is a 27.75% hallucination rate. “At scale, that’s not funny. It’s operational drag: wasted developer time, broken pipelines, and people losing...

The leadership principles behind high-performing AI engineering teams

Managing large AI teams today is less like running a traditional engineering organization and more like conducting an orchestra while the music is still being written. Leaders must balance speed, experimentation, risk, and coordination across disciplines that operate at very different tempos. Data scientists optimize for discovery, engineers for reliability and efficiency, security and legal teams for constraint, and leadership ultimately for outcomes. When AI teams are managed using the same structures and decision-making patterns as conventional software teams, friction shows up quickly. The leaders who succeed are those who intentionally redesign structure, alignment, and authority to reflect how AI systems are actually built, deployed, and evolved in practice. A critical starting point is clarity around what an AI system is optimizing for, along with the guardrails that prevent unintended tradeoffs. In practice, AI systems rarely behave uniformly. Performance often varies across u...

Apiiro’s Guardian Agent, Ai2’s Open Coding Agents, and more — Daily News Digest

Apiiro announces Guardian Agent Guardian Agent rewrites developer prompts to make them more secure and ensure they meet current needs of the software architecture, runtime environments, organizational policies, and regulatory requirements. According to the company, because of AI, security debt is being added faster than it can be fixed, and asking developers to fix vulnerabilities after code is written is no longer sufficient. “The reality is clear: Detection will never scale at the speed of AI. Only prevention will,” the company wrote in a blog post . Ai2 releases Open Coding Agents Open Coding Agents are a family of open agents that utilize a training method that makes it easier for developers to build their own coding agent trained on their internal codebases. The first release is SERA (Soft-verified Efficient Repository Agent), which uses a fine-tuning method that can be specialized to any codebase. The company is also releasing SERA’s training data to help researchers study w...

OpenSilver 3.3: Blazor Components Now Run Directly Inside XAML Applications

Userware today released OpenSilver 3.3, introducing native integration between XAML and Blazor. Developers can now embed Blazor components from libraries like DevExpress, Syncfusion, MudBlazor, Radzen, and Blazorise directly inside XAML applications, with no JavaScript bridges or performance overhead. OpenSilver is an open-source framework that runs WPF-style C# and XAML applications in web browsers via WebAssembly. It supports deployment to iOS, Android, Windows, macOS, and Linux through .NET MAUI Hybrid. With version 3.3, developers can also leverage the Blazor component ecosystem while keeping XAML as their primary UI technology. “ Blazor has an incredible component ecosystem. XAML has a powerful layout and binding system that developers love, ” said Giovanni Albani, CEO of Userware. “ With 3.3, you don’t have to choose. Use XAML where it excels, drop in Blazor components where you need them. Your ViewModels and architecture stay the same. ” How It Works Because OpenSilver rende...