coding

coding on Beyond Market Intelligence: a running collection of 38 stories we have gathered and hand-picked because they are worth your time. Every post here touches on coding in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around coding, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

How to Run 10+ Claude Code Sessions Without a Powerful Computer
Towards Data Science

How to Run 10+ Claude Code Sessions Without a Powerful Computer

Tired of hardware limitations hindering your AI agent explorations? Discover how to effectively run 10+ Claude Code sessions concurrently, even without a high-powered computer. This guide unlocks a practical approach to parallel coding agent workflows, empowering you to leverage AI's potential without significant investment. Explore strategies for optimized resource utilization and efficient session management. Interested in the broader landscape of AI agent development? See our article on Meta’s Muse Spark model for further insights into agent capabilities.

Meta is paying to peek at how you use their latest AI model
TechCrunch

Meta is paying to peek at how you use their latest AI model

Meta is incentivizing user feedback for Muse Spark, its new AI model designed for coding and agent applications, with a substantial discount averaging 95%. Users who share their prompts and model outputs directly contribute to the development of future iterations. This initiative highlights a growing trend of AI developers seeking real-world usage data to refine their models. As AI adoption strains existing infrastructure, as seen with utilities partnering with fusion startups like Realta Fusion, the need for optimized AI solutions becomes increasingly critical.

Meta says Muse Spark 1.3 has frontier performance — but its best results come from a model developers can’t broadly use yet
VentureBeat

Meta says Muse Spark 1.3 has frontier performance — but its best results come from a model developers can’t broadly use yet

Meta's newest AI model, Muse Spark 1.3, delivers notable performance gains over its predecessor, achieving "frontier performance" as CEO Mark Zuckerberg proclaimed. While the most impressive results stem from a "max reasoning" configuration still undergoing safety testing, the broadly available version ranks among the strongest price-performance offerings near the top of independent model evaluations. Though not currently leading the leaderboard—Anthropic’s Claude Fable 5.1 still holds that distinction—Muse Spark 1.3 represents a significant step forward, trading wins with OpenAI and Anthropic on key coding benchmarks.

OpenCode Explained: The Open-Source AI Coding Agent
Analytics Vidhya

OpenCode Explained: The Open-Source AI Coding Agent

OpenCode, the open-source AI coding agent, has evolved beyond simple model compatibility. While integration with various models remains a core strength, its innovative architecture now distinguishes it—particularly for users familiar with Claude Code. This article explores OpenCode’s unique design and the resulting trade-offs, offering a clear understanding of its capabilities. Discover how this agent empowers developers, moving beyond basic functionality to a future-focused approach to AI-assisted coding.

I analyzed 31,352 hourly LLM benchmark scores: within-day variation was 2.8 points, while between-day variation was 8.4 [P]
Machine Learning

I analyzed 31,352 hourly LLM benchmark scores: within-day variation was 2.8 points, while between-day variation was 8.4 [P]

A new analysis of 31,352 hourly LLM benchmark scores reveals critical insights into model stability. Examining coding, reasoning, and tool-calling performance, the research found between-day variation (8.4 points) was approximately three times greater than within-day variation (2.8 points), suggesting sustained daily changes offer a stronger signal for detecting performance drift. This work, underpinning the open-source AIStupidLevel system, now encompasses over 169,000 benchmark runs and powers a model router optimizing for performance and cost—a dimension often missing from standard monitoring.

10 Rules for Getting Better Results from AI Coding Agents
KDnuggets

10 Rules for Getting Better Results from AI Coding Agents

Everyone’s leveraging AI coding agents, but maximizing their utility requires a strategic approach. To move beyond initial excitement and achieve tangible results, consider these 10 rules for effective implementation. We’ve distilled best practices to ensure your AI agent becomes a genuine productivity asset, not just another tool. Explore these guidelines and discover how to harness AI's power for streamlined coding workflows. For a broader perspective on AI's impact, see our article, "Understanding the Impact of AI on Job Markets."

Cursor Releases Origin as an Agent-Native Alternative to GitHub
InfoQ

Cursor Releases Origin as an Agent-Native Alternative to GitHub

Cursor is redefining code hosting with Origin, a git-based platform now integrated directly within its AI-powered editor. Positioned as a compelling alternative to GitHub, Origin offers teams already leveraging Cursor's AI capabilities a seamless and streamlined workflow. Currently in early beta across Pro, Teams, and Enterprise plans, Origin resides within a dedicated "Codebase" tab. This move underscores Cursor’s commitment to an agent-native development experience. For a deeper dive into related AI and coding practices, explore "10 Positions for Enterprise RAG That Mainstream Tutorials Get Wrong."

Amjad Masad, CEO and co-founder of Replit, joins the Disrupt Stage at TechCrunch Disrupt 2026 
TechCrunch

Amjad Masad, CEO and co-founder of Replit, joins the Disrupt Stage at TechCrunch Disrupt 2026 

At TechCrunch Disrupt 2026, gain valuable insights into the evolving landscape of programming with Replit CEO and co-founder, Amjad Masad. He’ll be sharing his vision for the future and Replit’s integral role in shaping it. Masad’s perspective promises to illuminate the transformative potential of accessible coding environments. This appearance follows recent industry shifts, like Stripe’s significant investment in OpenRouter, underscoring the dynamism of the startup ecosystem. Discover how Replit is empowering the next generation of developers.

Podcast: The Human Edge: Why Brownfield Codebases Need Mob Programming, Not Just AI Vibes
InfoQ

Podcast: The Human Edge: Why Brownfield Codebases Need Mob Programming, Not Just AI Vibes

Beyond continuous deployment and pair engineering, Asgaut Mjølne Söderbom and Ola Hast explore the evolving landscape of software development in this episode of *The Human Edge*. They delve into recent experiments with AI coding tools like Claude Code, ultimately finding it valuable for many tasks but not ideal for core coding. The conversation builds directly on their previous discussion, offering a practical perspective on integrating AI into established workflows, particularly within complex, brownfield codebases.

Top 10 Open-Source Benchmarks for AI Coding Agents in 2026
KDnuggets

Top 10 Open-Source Benchmarks for AI Coding Agents in 2026

Evaluating AI coding agents demands rigorous benchmarks. In 2026, several open-source options will be essential for developers. Explore the top 10, including SWE-bench, Terminal-Bench, SlopCodeBench, and ProgramBench, alongside emerging contenders. These benchmarks offer critical insight into agent capabilities across diverse coding tasks. For deeper context on related AI research and development, see our discussion thread for EMNLP 2026 Notifications/Results. Discover how these tools empower informed decisions in the rapidly evolving landscape of AI-powered software engineering.

Cognition CEO denies report that SpaceX tried to acquire the startup
TechCrunch

Cognition CEO denies report that SpaceX tried to acquire the startup

Reports of SpaceX’s acquisition attempt of AI coding startup Cognition have been categorically denied by Cognition CEO, Navneet Alang. While SpaceX has demonstrably accelerated its presence in the AI space with the acquisition of Cursor, this purported deal appears unfounded. The move highlights the intensifying competition among tech giants—including OpenAI and Anthropic—to secure leadership in enterprise AI. For further context on the evolving AI landscape and privacy considerations, explore our recent article, "OpenAI seeks to one-up Anthropic with new customer privacy protections."

Run Qwen3.8-27B as a Local AI Coding Agent in Just 3 Commands
KDnuggets

Run Qwen3.8-27B as a Local AI Coding Agent in Just 3 Commands

Unlock powerful AI coding assistance locally with just three commands. Download Ollama, pull the Qwen3.8-27B model, and launch it seamlessly with OpenCode – no complex setup required. This streamlined process empowers developers to leverage a robust language model for coding tasks directly on their machines. For those exploring the broader landscape of agentic workflows, consider our article on Netflix’s recent open-source agentic workflow for causal inference. Experience the future of local AI development today.

How to Shine as a Data Scientist in the Vibe Coding Era
Towards Data Science

How to Shine as a Data Scientist in the Vibe Coding Era

The rise of AI coding tools like those explored in "How to Install Codex CLI" signals a significant shift for data scientists. Coding proficiency is increasingly becoming a commodity; the future belongs to those who leverage these tools strategically. This post outlines how to thrive in this "Vibe Coding Era," focusing on higher-level skills like problem framing, insightful analysis, and communicating data-driven narratives. Discover how to evolve beyond coding and become the indispensable data scientist of tomorrow.

SpaceX officially closes its Cursor acquisition
TechCrunch

SpaceX officially closes its Cursor acquisition

SpaceX has finalized its acquisition of Cursor, the AI coding startup, integrating its capabilities into the company’s expanding technological ecosystem. This move signals SpaceX’s continued commitment to leveraging artificial intelligence to streamline workflows and accelerate innovation. Cursor’s AI-powered coding assistance tools promise to empower engineers and developers, enhancing productivity across various projects. For those familiar with Codex, Cursor's functionality will feel intuitive – explore a deeper dive into using Codex with our guide, "How to Install Codex CLI."

Microsoft Excel | Help & Support with your Formula, Macro, and VBA problems | A Reddit Community

VBA coding for organizing

Automating task organization in your spreadsheet can significantly boost productivity. You've correctly identified the need to automatically sort your task list (Client, Due Date, Description) by date upon entry. While VBA offers a solution, achieving this reliably can be challenging. Instead of endlessly searching for the "perfect" code, consider leveraging Excel's built-in features—or, as explored in our article "How do you track a large inventory of original artwork in Excel without it getting out of hand?", explore alternative organizational strategies.

GLM-5.3 is here with advanced cyber capabilities — and reportedly already found a 'serious vulnerability' in Cursor
VentureBeat

GLM-5.3 is here with advanced cyber capabilities — and reportedly already found a 'serious vulnerability' in Cursor

Z.ai has released GLM-5.3, a significant advancement in AI-native spreadsheet technology, building upon the 744-billion-parameter base of GLM-5.2 through scaled post-training. Notably, GLM-5.3’s cybersecurity capabilities have rapidly progressed, even identifying a potential vulnerability in Cursor, an AI coding startup. Initially accessible through the GLM Coding Plan and ZCode environment, with broader API access and open weights forthcoming, GLM-5.3 demonstrates considerable headroom for improvement without extensive retraining. For those interested in exploring the broader landscape of AI agents, consider our recent article on Meta’s open-source

Meta Open-Sources Muse Glimmer: A 30B Local Agentic Model Optimised for On-Device Execution
InfoQ

Meta Open-Sources Muse Glimmer: A 30B Local Agentic Model Optimised for On-Device Execution

Meta AI Research has unveiled Muse Glimmer, a significant advancement in on-device AI. This 30-billion-parameter, open-weight model, released under the Apache 2.0 license, empowers autonomous agents and complex task execution directly on consumer GPUs—eliminating the need for cloud dependencies. Utilizing a multi-stage training process, Glimmer delivers efficient performance and supports multimodal inputs, streamlining coding and automation. Explore this future-focused solution, and discover how it transforms local workflows; for broader context on enterprise AI initiatives, see our related article on IBM’s partnership with OpenAI.

Google’s Gemini 3.7 Flash targets coding and agents with a 50% introductory price cut
VentureBeat

Google’s Gemini 3.7 Flash targets coding and agents with a 50% introductory price cut

Google is accelerating AI innovation with the release of Gemini 3.7 Flash, its "most intelligent workhorse model yet" for coding and agentic workflows. This upgrade prioritizes diligent planning and disciplined execution, showing significant gains in debugging, web development, and enterprise automation—potentially reducing human intervention. Notably, Google is offering a 50% introductory price cut through the end of 2026, making it a compelling option for high-volume applications.

SpaceXAI debuts Grok 4.6, overtaking Kimi K3's performance and matching GPT-5.6 Sol for world's third best on Artificial Analysis
VentureBeat

SpaceXAI debuts Grok 4.6, overtaking Kimi K3's performance and matching GPT-5.6 Sol for world's third best on Artificial Analysis

SpaceXAI, formerly xAI, has released Grok 4.6, its latest AI model, focused on long-running agents, coding, and knowledge work, offering a competitive pricing strategy. Scoring 61 on the Artificial Analysis Intelligence Index, Grok 4.6 ties OpenAI's GPT-5.6 Sol for the third-best position globally, surpassing Kimi K3. This upgrade delivers significant gains over Grok 4.

We built the Agentic World Cup - LLMs that compete in 1v1 Soccer. [P]
Machine Learning

We built the Agentic World Cup - LLMs that compete in 1v1 Soccer. [P]

Introducing the Agentic World Cup, a pioneering platform designed to bridge the “embodiment gap” in AI. We’re challenging Large Language Models to compete in 1v1 soccer, creating a unique training and testing ground for true embodied intelligence. Simply sign in, select your LLM, coach it with prompting, and submit it to compete. Final rankings will be published this Friday. This initiative also addresses a critical need for embodied benchmarking, as explored in our recent article, "Producing the World’s Cheapest Tokens."

How to Effectively Deploy Code With Claude Code
Towards Data Science

How to Effectively Deploy Code With Claude Code

Optimizing your CI/CD pipeline for coding agents like Claude Code is critical for efficient development workflows. This post details proven strategies for effective code deployment, moving beyond traditional methods to leverage the power of AI-assisted coding. Discover practical techniques to streamline your processes and maximize productivity. If you're seeking a deeper understanding of foundational concepts, consider “I never understood positional encoding until I read this article,” for valuable insights into related AI principles.

How to Implement Structured Output with Local LLMs
Towards Data Science

How to Implement Structured Output with Local LLMs

Unlock the power of local Large Language Models (LLMs) with structured output – a critical technique for reliable data extraction and automation. This post explores why structured output is essential, detailing implementation strategies and addressing potential failure scenarios. Gain clarity on how to transform LLM responses into predictable, usable formats, empowering more robust applications. Learn how to troubleshoot common issues and maintain system integrity.

Top 10 Skills for Claude Code and Codex CLI
Analytics Vidhya

Top 10 Skills for Claude Code and Codex CLI

Unlocking the true potential of Claude Code and Codex CLI isn't about mastering endless AI skills; it's about strategically guiding these tools to deliver actionable results within your budget. The real expertise lies in crafting clear context and transforming AI output into tangible value. Our list of Top 10 Skills focuses on this core principle. Discover how to empower your data journey—instead of searching through vast skillsets, begin with a focused approach. For deeper insights into AI model performance, explore "Qwen 3.

Machine Learning

Do LLMs make ML research more fair for small teams? [D]

Large language models (LLMs) are reshaping the landscape of machine learning research, offering a compelling opportunity to level the playing field for smaller teams. A solo researcher or a small group can now leverage LLMs for coding assistance, streamlined literature reviews, and improved writing—functions traditionally provided by larger, well-connected labs. While LLMs don’t replace essential mentorship or critical research judgment, they empower those with limited resources to translate promising ideas into impactful publications.