All posts tagged: Coding

EY hit 4x coding productivity by connecting AI agents to engineering standards

EY hit 4x coding productivity by connecting AI agents to engineering standards

Published by skeptic

Coding agents can generate thousands of lines of code in minutes. The problem: most of it can’t be deployed. It breaks internal standards, fails compliance checks, or creates more cleanup work than it saves. “You can generate a ton of code, but it doesn’t mean really anything, right? It’s got to be code that is integratable, that is compliant, and you don’t want to create more work on the back end just because you sped up the code generation process on the front end,” said Stephen Newman, EY Global CTO Engineering Leader. EY’s product development team solved this by connecting coding agents to their engineering standards, code repositories, and compliance frameworks. The result: 4x to 5x productivity gains across teams building EY’s suite of audit, tax, and financial platforms. But the gains didn’t come from just turning on a tool. Newman’s team spent 18 to 24 months building the cultural foundation and technical integrations that made semi-autonomous coding work at scale. The first step was cultural. EY started with GitHub Copilot-style tools, letting engineers get …

AI ‘Vibe Coding’ Could Put Ethereum Roadmap Ahead Of Schedule: Vitalik Buterin

AI ‘Vibe Coding’ Could Put Ethereum Roadmap Ahead Of Schedule: Vitalik Buterin

Published by Jenni Sidey

Authored by Martin Young via CoinTelegraph.com, Ethereum co-founder Vitalik Buterin says an experiment that used artificial intelligence to prototype the blockchain’s roadmap out to 2030 in just a few weeks could have lessons for developers.  “This is quite an impressive experiment. Vibe-coding the entire 2030 roadmap within weeks,” Buterin posted to X on Saturday after a developer made a bet with Buterin in February that one person could use AI to code a reference implementation of the blockchain’s roadmap. Buterin added that AI is “massively accelerating coding” and that people “should be open to the possibility that the Ethereum roadmap will finish much faster than people expect, at a much higher standard of security than people expect.” Vibe coding is where AI creates the code for an application, allowing developers to quickly create software. The practice has become more popular as AI models have improved at coding; however, some warn that AI-generated code can be insecure. ETH2030 architecture stack. Source: YQ Buterin says AI code would have “critical bugs” Buterin said that there were “massive caveats” to using AI, as the …

Vibe coding with overeager AI: Lessons learned from treating Google AI Studio like a teammate

Vibe coding with overeager AI: Lessons learned from treating Google AI Studio like a teammate

Published by skeptic

Most discussions about vibe coding usually position generative AI as a backup singer rather than the frontman: Helpful as a performer to jump-start ideas, sketch early code structures and explore new directions more quickly. Caution is often urged regarding its suitability for production systems where determinism, testability and operational reliability are non-negotiable.  However, my latest project taught me that achieving production-quality work with an AI assistant requires more than just going with the flow. I set out with a clear and ambitious goal: To build an entire production‑ready business application by directing an AI inside a vibe coding environment — without writing a single line of code myself. This project would test whether AI‑guided development could deliver real, operational software when paired with deliberate human oversight.  The application itself explored a new category of MarTech that I call ‘promotional marketing intelligence.’ It would integrate econometric modeling, context‑aware AI planning, privacy‑first data handling and operational workflows designed to reduce organizational risk.  As I dove in, I learned that achieving this vision required far more than simple …

7 AI coding techniques that quietly make you elite

7 AI coding techniques that quietly make you elite

Published by skeptic

Vertigo3d / iStock / Getty Images Plus Follow ZDNET: Add us as a preferred source on Google. ZDNET’s key takeaways Treat the AI like another developer, not a magic box. Encode design systems and user profiles in system prompts. Every fixed bug becomes a permanent lesson-learned rule in the project’s DNA. Ever since the days of punched cards, I’ve self-identified as a programmer and a computer scientist. The programmer side is the practical side of my engineering identity, the person who crafts code line by line. The computer scientist is the theoretician, the scientist, the strategist, and the planner. While I love the theory and science of computers, I’ve always enjoyed the hands-on feeling of cutting code. I think it’s probably akin to how some woodworkers prefer hand tools over power tools for the visceral feel of working with wood. Also: Worried about AI coding? Why the invention of power tools is the blueprint for your career future Unfortunately, I’ve never had much time to code. My day-to-day job has been as a company executive, founder, educator, and …

Makeblock mBot2 Rover Kit Review : STEM Building & Coding

Makeblock mBot2 Rover Kit Review : STEM Building & Coding

Published by skeptic

The Makeblock mBot2 Rover Kit is an educational robotics platform designed to introduce learners to STEM concepts through hands-on building and coding. As outlined by Core Electronics, the kit features a durable construction system with anodized aluminum parts and M4 bolts, making sure a sturdy framework that can withstand repeated use. Its design accommodates a wide range of users, with the starter version recommended for ages 8 and up and the more advanced Rover platform suited for learners aged 12 and older. This adaptability allows the kit to grow alongside the user’s skills, offering progressively complex challenges. In this overview, you’ll explore the key components of the mBot2 Rover Kit, including the CyberPi microcontroller, which enables wireless connectivity and advanced functionalities like motion detection and real-time data display. You’ll also learn about the mBlock coding platform, which supports both beginner-friendly block coding and Python for more advanced programming. By understanding these features, you’ll gain insight into how the kit fosters critical thinking, creativity, and technical proficiency, making it a versatile resource for both classroom and …

Code Metal Raises 5 Million to Rewrite the Defense Industry’s Code With AI

Code Metal Raises $125 Million to Rewrite the Defense Industry’s Code With AI

Published by skeptic

Code Metal, a Boston-based startup that uses AI to write code and translate it into other programming languages, just closed a $125 million Series B funding round from new and existing investors. The news comes just a few months after the startup raised $36 million in series A financing led by Accel. Code Metal is part of a new wave of startups aiming to modernize the tech industry by using AI to generate code and translate it across programming languages. One of the questions that persists about AI-assisted code, though, is whether the output is any good—and what the consequences might be if it’s not. Over the past two years companies like Antithesis, Code Rabbit, Synthesized, Theorem, and Harness have all secured millions in backing from venture capitalists for their approaches to automating, validating, testing, and securing AI-generated code. These startups are selling the “picks and shovels” of the AI gold rush—tech tools that serve a larger industry. While some of the methodologies behind their technology remain unproven, investors are willing to gamble that at …

For open-source programs, AI coding tools are a mixed blessing

For open-source programs, AI coding tools are a mixed blessing

Published by skeptic

A world that runs on increasingly powerful AI coding tools is one where software creation is cheap — or so the thinking goes — leaving little room for traditional software companies. As one analyst report put it, “vibe coding will allow startups to replicate the features of complex SaaS platforms.” Cue the hand-wringing and declarations that software companies are doomed. Open-source software projects that use agents to paper over long-standing resource constraints should logically be among the first to benefit from the era of cheap code. But that equation just doesn’t quite stick. In practice, the impact of AI coding tools on open source software has been far more mixed. AI coding tools have caused as many problems as they have solved, according to industry experts. The easy-to-use and accessible nature of AI coding tools has enabled a flood of bad code that threatens to overwhelm projects. Building new features is easier than ever, but maintaining them is just as hard and threatens to further fragment software ecosystems. The result is a more complicated story …

Claude Sonnet 4.6 Brings Improved Coding, Computer Use, and Office Tasks

Claude Sonnet 4.6 Brings Improved Coding, Computer Use, and Office Tasks

Published by skeptic

Anthropic today updated its Sonnet model to version 4.6, and the company says it is the most capable Sonnet model to date with upgrades across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. Claude Sonnet 4.6 is the default for users who have Free and Pro plans, and it has an updated 1M token context window. Sonnet 4.6 improves consistency and instruction following for coding, it’s better at computer use tasks, and it can complete office tasks that previously required an Opus model. Sonnet 4.6 has human-level capability for tasks like navigating a complex spreadsheet or filling out a multi-step web form. According to Anthropic, Sonnet 4.6 has a “a broadly warm, honest, prosocial, and at times funny character, very strong safety behaviors, and no signs of major concerns around high-stakes forms of misalignment.” It offers Opus-level intelligence at a more affordable price point, so it is practical for a wider range of tasks. Opus 4.6 is still the better option for agentic coding, agentic code use, and multidisciplinary reasoning, but Sonnet …

Qodo 2.1 solves your coding agents’ ‘amnesia’ problem, giving them an 11% precision boost

Qodo 2.1 solves your coding agents’ ‘amnesia’ problem, giving them an 11% precision boost

Published by skeptic

As AI-powered coding tools flood the market, a critical weakness has emerged: by default, as with most LLM chat sessions, they are temporary — as soon as you close a session and start a new one, the tool forgets everything you were just working on. Developers have worked around this by having coding tools and agents save their state to markdown and text files, but this solution is hacky at best. Qodo, the AI code review startup, believes it has a solution with the launch of what it calls the industry’s first intelligent Rules System for AI governance — a framework that gives AI code reviewers persistent, organizational memory. The new system, announced today as part of Qodo 2.1, replaces static, manually maintained rule files with an intelligent governance layer. It automatically generates rules from actual code patterns and past review decisions, continuously maintains rule health, enforces standards in every code review, and measures real-world impact. For Itamar Friedman, CEO and co-founder of Qodo, the release represents a pivotal moment not just for his company …

Claude Opus 4.6 vs GPT-5.3 Codex for AI Coding Workflows

Claude Opus 4.6 vs GPT-5.3 Codex for AI Coding Workflows

Published by skeptic

Can a single AI model truly balance speed, precision, and adaptability, or are trade-offs inevitable? Greg Isenberg takes a closer look at how Claude Opus 4.6 vs GPT-5.3 Codex tackle this question, offering a detailed comparison of two of the most advanced coding-focused AI systems available today. With Claude Opus 4.6 emphasizing multi-agent orchestration for large-scale projects and GPT-5.3 Codex excelling in lightning-fast prototyping and interactive refinement, this analysis provide more insights into their contrasting approaches to AI-driven development and what they mean for developers navigating modern workflows. This breakdown highlights the unique strengths and limitations of each system, including their performance in building a competitor to Poly Market, a prediction market platform. Whether you’re intrigued by the precision and depth of Claude Opus 4.6 or the speed and adaptability of GPT-5.3 Codex, understanding their differences can illuminate which aligns better with your goals. Beyond technical capabilities, this exploration examines how these models integrate into real-world applications, offering a glimpse into the evolving landscape of AI-assisted coding and its impact on the future of software …