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Claude Code’s product lead talks usage limits, transparency, and the “lean harness”

agentic ai, ai, AI (Artificial Intelligence), anthropic, Artificial Intelligence, Cat Wu, claude, Claude Code, Code with Claude, software development

SAN FRANCISCO—Amid an ever-expanding array of surfaces, growing demand for tokens and compute, and a rapidly evolving user base, Anthropic doesn’t have a long-term road map for Claude Code. However, it’s betting that such a plan would be rendered moot by improvements in model capabilities and new signals from developers on how best to use […]

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AI Code Generation Inside ADLC: How It Cuts Dev Time Without Cutting Quality

ADLC, ai, AI (Artificial Intelligence), AI CI/CD, AI Code Generation, AI Coding Tools, ai development, AI Development Lifecycle, AI in Software Development, AI software development lifecycle, AI Workflow Automation, AI-Assisted Coding, Artificial Intelligence, Devops, DevOps & Automation, digital transformation, Enterprise AI Development, Enterprise Technology, GitHub Copilot, Intelligent Testing, LLM in Software Engineering, software development, Spritle Blog, SpritleSoftware

Introduction Development timelines are shrinking, but expectations are rising. US engineering teams are expected to ship faster, iterate more often, and still maintain production-grade quality. According to GitHub’s 2025 developer report, over 70% of teams now use some form of AI-assisted coding, yet many still struggle to translate that into real delivery speed. Here’s the

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Per-token AI charges come to GitHub Copilot

ai, AI (Artificial Intelligence), AI Market Trends, Artificial Intelligence, automation, charging models, GitHub Copilot, Microsoft, software development

As of 1st June 2026, GitHub Copilot will charge its users on the basis of the tokens they use, rather than a flat rate subscription model. The model that’s seeing the shutters closed on it is, or rather was, simple to understand and use. Users were given a set number of ‘Premium Requests’ according to

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Everyone’s an Engineer Now

ai, AI (Artificial Intelligence), AI & ML, Artificial Intelligence, Commentary, software development

Cat Wu leads product for Claude Code and Cowork at Anthropic, so she’s well-versed in building reliable, interpretable, and steerable AI systems. And since 90% of Anthropic’s code is now written by Claude Code, she’s also deeply familiar with fitting them into routine day-to-day work. Last month, Cat joined Addy Osmani at AI Codecon for

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IBM launches AI platform Bob to regulate SDLC costs

agentic ai, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI in Action, AI Market Trends, Artificial Intelligence, automation, coding assistants, Compliance, Cybersecurity AI, Data Engineering & MLOps, Deep Dives, Featured News, Features, governance, Governance, Regulation & Policy, How It Works, ibm, Inside AI, Natural Language Processing (NLP), Open-Source & Democratised AI, orchestration, productivity, SaaS, software development, Trust, Bias & Fairness, World of Work

To regulate software delivery costs and SDLC governance, IBM is launching Bob, an AI platform built to anchor enterprise engineering. Accumulated technical debt, hybrid cloud structures, and rigid compliance requirements clash with the raw speed of coding assistants. Without boundaries, they generate unmanaged liabilities rather than functional progress. Dinesh Nirmal, SVP at IBM Software, explained:

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Integrating AI Apps Into Legacy Systems: Why US Clients Keep Coming Back

ai, AI (Artificial Intelligence), AI app builder, AI app completion, AI app integration, ai development, AI in Software Development, Artificial Intelligence, backend integration, Bolt.new, legacy systems, middleware API, SaaS & Startups, SaaS Development, software development, Spritle Blog, SpritleSoftware, startup tech, System Integration, v0 by Vercel

Introduction You’ve already done the hard part. You used an AI app builder like Bolt.new or v0 by Vercel to build something real. A working dashboard. A customer portal. Maybe even a full SaaS MVP. But now you’re stuck. Your AI apps look great on the surface, but they won’t talk to your existing systems.

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New Codex features include the ability to use your computer in the background

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Codex, Enterprise AI, OpenAI, software development

A new version of OpenAI’s Codex desktop app reaches users today. It brings a smorgasbord of new features and changes, ranging from new developer capabilities to expansion into non-developer knowledge work to laying the groundwork for the company’s “super app.” The most interesting for the moment is the ability to perform tasks on your PC

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Top 10 AI Innovations Driving Quality Assurance

ai, AI (Artificial Intelligence), ai development, AI in QA, AI in Software Development, AI in Software Testing, AI Innovations, AI Testing, Artificial Intelligence, CI/CD Automation, digital transformation, Generative AI, Predictive Analytics QA, Product Engineering, Quality Assurance, Self-Healing Tests, software development, Software Testing, Spritle Blog, SpritleSoftware, Technology & Innovation, Technology Insights, Technology Trends, Test Automation

The way we test software is changing — and it’s changing fast. Over the past couple of years, AI has moved from a buzzword in QA discussions to something teams are actively building into their workflows. If you’re working in software quality or engineering, understanding these shifts isn’t optional anymore. It’s part of staying effective.

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AI Debugging in ADLC: Catching Production Bugs Before They Exist

ADLC, ai, AI (Artificial Intelligence), AI Debugging, ai development, AI Development Strategy, AI in Engineering, AI in Software Development, AI Observability, AI software development lifecycle, Artificial Intelligence, Bug Prevention, DevOps & Testing, DevOps AI, Intelligent Testing, Predictive Debugging, software development, Software Development Life Cycle, Software Quality, Spritle Blog, SpritleSoftware, Technology & Innovation

Introduction Production bugs are expensive—but the real cost isn’t just fixing them. It’s lost revenue, damaged trust, and engineering time spent firefighting instead of building. According to IBM’s Cost of a Data Breach Report (2023), issues caught in production can cost up to 15x more than those identified during development. The uncomfortable truth? Traditional debugging

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Grief and the Nonprofessional Programmer

ai, AI (Artificial Intelligence), AI & ML, Artificial Intelligence, Commentary, software development

I can’t claim to be a professional software developer—not by a long shot. I occasionally write some Python code to analyze spreadsheets, and I occasionally hack something together on my own, usually related to prime numbers or numerical analysis. But I have to admit that I identify with both of the groups of programmers that

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