Asana launched Dash, an AI assistant, and upgraded AI teammates to rebrand its work management platform as an operating system for human-agent teams. Dash acts as a personal AI chief of staff, automatically capturing follow-ups from meetings, Slack, and email into trackable tasks. AI teammates now feature expanded skills, integrations, and support for third-party tools via StackAI. Asana emphasizes its harness over models, leveraging its Work Graph. Early customers like FedEx and COS reported significant productivity gains.

A Bain survey of 951 companies shows nearly 40% achieved less than 10% cost savings from AI, despite targeting 11-20%. Only 7% run fully autonomous AI agents, undermining business case assumptions.

IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.

While Google CEO Sundar Pichai boasts that 75% of new code is AI-generated, employees are sharing memes on the internal Memegen board criticizing AI tools like Jetski for fabricating data and adding to their workload. Workers report that AI-generated code creates bottlenecks in review and infrastructure, and that the company's AI-first prioritization is causing burnout and prompting some to seek other jobs.

US tech companies announced 38,242 job cuts in May, the largest monthly reduction in nearly two years, bringing the sector's 2026 total to 123,653, up 65% over the same period in 2025. AI was the most-cited reason for layoffs across all sectors for the third consecutive month. Despite high layoff announcements, unemployment claims have not risen correspondingly, and the May payrolls report is expected to show 85,000 jobs added. Major tech firms like Google, Amazon, Microsoft, and Meta are ramping up AI capital spending to a combined $725 billion for 2026, with some layoffs directly tied to AI infrastructure investments. The debate continues over whether AI is actually replacing the jobs being cut.

An analogy comparing AI-assisted coding (vibecoding) to fast food: quick and easy in the short term, but unsustainable and unhealthy in the long run. The author advises treating AI output as disposable and warns against relying on it for complex tasks.

A comprehensive guide to AI API pricing, covering six key decisions: what to meter, which pricing primitive (tokens, credits, outcomes), cost calculation, tier structure, hard vs. soft caps, and credit wallet design. Includes practical examples and a diagnostic prompt for your own pricing.

VC Boom is an AI-powered tool that scores your pitch deck in under 90 seconds, matches you with relevant investors from 47,000+, and drafts personalized cold emails. Built by an 8-year VC, it has helped founders raise $95 million. Free to start.

When AI inference costs threatened Mate Security's runway, CEO Asaf Wiener didn't just cut costs—he restructured the company so that every backend engineer owns model selection, evaluation, and routing for their workloads. This shift from cloud-era opacity to workload-level cost visibility has enabled quality-cost optimization, with open-source models sometimes outperforming frontier APIs on specific tasks. Wiener argues that an AI-native company's only structural advantage is shipping against the best model available that day, enabled by an 'execution mode' culture that avoids legal-policy review cycles and hires for adaptability.

The author, tasked with exploring practical AI applications, tried using AI for DIY. The AI gave poor advice, but highlighted the value of human judgment.

The article argues that AI will 'solve' software, making it a cheap utility, and the next frontier will be physical world problems like climate change and healthcare. The author is building ProductNow to address alignment challenges in mixed human-AI teams.

KushoAI published a benchmark evaluating 7 AI systems for detecting planted API bugs given only a JSON schema and one valid sample payload. KushoAI ranked first with a composite score of 0.83, significantly outperforming others on complex bugs. The report finds that prompt engineering improves breadth but not cross-field business logic reasoning, and that test composition matters more than volume.

The model, released under the Apache 2.0 license, is another example of how cloud providers are enabling enterprises to run models on local devices for agentic workflows.

Non-profit research consortium — free to read, forever. Open, peer-reviewed research on humanity's most consequential problems. Anyone can contribute with AI assistance or fund the team.

This article explains how AI agents are transforming data science workflows, automating routine tasks, and requiring new skills such as system design, tool integration, and agent observability. It covers frameworks like LangGraph, AutoGen, and smolagents, the shift from procedural to evaluative work, and emerging roles.

The upcoming SpaceX IPO, one of the largest in history, is bending or breaking market rules to favor Elon Musk. X (formerly Twitter) is shrinking by every metric, yet Musk’s wealth and power have only grown. This interview with NYT reporter Ryan Mac explores how Musk’s control over SpaceX, combined with relaxed index inclusion rules and controversial corporate governance, is reshaping the IPO landscape. Starlink remains the only profitable part of SpaceX, while AI and other ventures lose money. Investors are betting on Musk’s promises rather than fundamentals.

Microsoft 365 Premium is the successor to Copilot Pro. At $20/month, with a 50% first-year discount for existing subscribers, it bundles advanced AI features, higher usage limits, and a Family subscription, directly competing with ChatGPT Plus for heavy Microsoft 365 users.

When organizations adopt AI through engineering workflows, design work gets pulled into the pipeline, turned into a prompt generator for code, or just another way to produce artifacts faster. Designers adapt to those workflows because they’re often the only ones available, but that adaptation shifts the focus away from the kind of decision-making design is supposed to do. The article argues for co-leadership across engineering, design, and product to ensure AI improves decision quality, not just speed.

Hello Inbox is an AI-powered email deliverability platform that helps businesses and marketers test and fix email delivery issues, preventing emails from landing in spam. It offers 9 tools and an AI assistant trained by a human expert, including DMARC monitoring, list verification, spam word checking, and more. A free tier is available.

Databricks announces a major update to Agent Bricks Knowledge Assistant, powered by Instructed-Retriever-1, achieving 3x faster search, 2x faster answer generation, and ~2s time to first token through parallel test-time scaling without quality tradeoffs.

OpenAI CEO Sam Altman outlines the next phase of AI products: a "proactive AI" that runs constantly in the background and acts on its own instead of waiting for user prompts. Companies are also wrestling with spiraling AI costs and a basic problem: most employees simply don't know what to ask AI. Altman's promise: "We can help people get more value for less spend."

At Computex 2026, Nvidia announced its RTX Spark processor, launching a wave of new high-performance ultrabooks. Meanwhile, major brands unveiled affordable 'cheap premium' laptops starting at $599 to compete with the MacBook Neo. This article highlights the five most notable products: Nvidia RTX Spark, Microsoft Surface Ultra, ROG XReal R1 AR glasses, Dell XPS 13, and Acer Swift Air 14.

Microsoft is releasing a server Linux, a container Linux, and a Windows 11 built for Linux programmers. Here's why.

NVIDIA introduces Nemotron 3.5 ASR, a 600M-parameter streaming multilingual speech-to-text model supporting 40 language-locales with low latency, high accuracy, and built-in punctuation and capitalization. The article details how to fine-tune the model for specific languages, domains, or accents, showing significant WER reductions for Greek and Bulgarian as examples.

Learn how to perform text classification using locally hosted open-source LLMs like Llama 3, Mistral, and Gemma via Ollama and the Scikit-LLM Python library, all without API costs.

Germany is launching a €125 million AI competition to help Europe build its own frontier AI labs amid a global race.

Ultorg's 'Fill with AI' feature uses LLMs like GPT-4.1-mini to automate data edits in a database view. In a demo, it appraises artworks from the National Gallery of Art by joining timeline entries and other tables, then writing results to Excel. Users provide simple prompts for each column, and the AI processes data in batches if needed. Requires Ultorg 2.2.0+ and an API key from Anthropic or OpenAI.

Digital Intelligence enters a business not as a miracle, but as a developer, revealing the order, chaos, data, responsibility, and gaps already present. This book examines 13 myths that misplace DI, aiming to help organizations place it correctly without blind trust or fear.

Choosing an AI model is no longer simple. This article debunks the reliance on benchmarks and offers a personal workflow-based evaluation framework. The author tests GPT, Claude, and Gemini to show how to pick the best model for your tasks.

It's almost impossible to avoid seeing AI-generated content online, but it doesn't have to be this way. YouTube, Instagram, TikTok, and more have ramped up content authentication efforts over the last year, with many now automatically applying labels to distinguish AI-generated images, videos, and music from those made by real, human creators. That's all very well and good if we're just stumbling across labeled content at random, but you know what would be better? Letting us filter out the AI slop.