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7 Continuous Testing Best Practices That Accelerate Software Delivery Neeraj Mishra The Crazy Programmer

Software teams face constant pressure to release high-quality applications faster than ever before. Continuous testing has become a key practice that helps development teams catch bugs early, reduce risks, and speed up their release cycles. This approach integrates automated testing throughout the entire development process rather than leaving it until the end. Teams that apply proven continuous testing practices can dramatically reduce their time to market while maintaining high software quality. However, many organizations struggle to implement effective testing strategies that truly accelerate delivery. The right practices help teams automate tests efficiently, catch defects earlier, and create smooth pipelines that deliver code with confidence. This guide explores seven basic practices that transform how teams test and deliver software. From automation strategies to team collaboration methods, these approaches help organizations build faster release cycles without sacrificing qua...
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How to Design the Software Engineering Organization to Deliver Business Value

Too often, software engineering organizations evolve reactively and are shaped by precedent or internal politics in a volatile and rapidly changing business environment, hindering intentional design. To deliver real business value, software engineering leaders should proactively optimize their organizational structures and delivery models to achieve both digital optimization and digital transformation. Evaluate Alternatives to Design the Software Engineering Organization and Delivery Model To design an effective software engineering organization that delivers business value, software engineering leaders should begin by understanding the IT operating model (ITOM) targeted by their CIO. This model shapes how talent, performance management, organizational structure and delivery models are configured to achieve business goals.  Software engineering practices must align with the ITOM and apply its principles to address current challenges. Then, they should assess how effectively ...
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This week in AI updates: Claude Opus 4.6, GPT-5.3-Codex, and more (February 6, 2026)

Anthropic launches Claude Opus 4.6 Claude Opus 4.6 is the latest version of the company’s most powerful class of AI models. Anthropic says that this release improves on Opus’ coding skills, and it now plans more carefully, sustains agent tasks for longer, can run more reliably in larger codebases, and has better code review and debugging skills, helping it to more effectively catch its own mistakes. In addition to coding improvements, Claude Opus 4.6 also features improved abilities in tasks like running financial analyses, doing research, and using and creating documents, spreadsheets, and presentations. It also features a 1M context window (beta), which is a first for Opus models, Anthropic said. OpenAI releases GPT-5.3-Codex The latest version of OpenAI’s coding agent builds on the coding performance of the previous release as well as the reasoning and knowledge capabilities of GPT-5.2. It is capable of tackling long-running tasks involving research, tool use, and complex exe...
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Introducing CoreWeave ARENA, New Lab for AI Production Readiness

CoreWeave , Inc. (Nasdaq: CRWV), The Essential Cloud for AI , today announced CoreWeave ARENA (AI-Ready Native Applications), designed to help teams test workloads on purpose-built AI infrastructure and software that mirrors how AI actually runs in high-demand production settings. Replacing traditional sandbox or demo setups, the industry-leading CoreWeave ARENA pairs production-scale compute with a standardized evaluation environment. As AI becomes part of day-to-day operations across industries, the integration from infrastructure to software determines ultimate success. Workloads are becoming more continuous and distributed, and performance or cost differences now matter more as everything from accelerators to agents evolve simultaneously. Organizations need earlier and more accurate insight into how their workloads will perform at scale, without the overhead of bespoke evaluation processes. CoreWeave ARENA provides a low-friction way to evaluate new workload performance through co...
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Google previews Developer Knowledge API, MCP server that will make it easier to access docs for Google services

Google is attempting to make it easier for developers to access its documentation by creating the Developer Knowledge API and corresponding MCP server, both now in public preview. The Developer Knowledge API allows developers to search and retrieve documentation for Google’s services in Markdown. This includes documentation from firebase.google.com , developer.android.com , docs.cloud.google.com , and more. The two main functions that the API supports are SearchDocumentChunks , which finds page URIs and content snippets based on a query, and GetDocument or BatchGetDocuments , which retrieves the full content of the search result. Google is re-indexing all of its documentation within 24 hours of a service being updated to ensure that developers can stay up-to-date with information related to the latest releases. According to Google, a challenge developers face when using AI coding tools is that they may be leveraging outdated documentation, resulting in responses that aren’t aligned...
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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 ...
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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...
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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...
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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...
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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...
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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...
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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 ...
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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...
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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...
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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...
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