AI agents without clear ownership cause silent failures that cascade in multi-agent workflows, according to a new analysis. The article defines four pillars of agent ownership—job definition, consumpt…
Teams deploying multiple AI agents without a structured registry face duplication, permission creep, and compliance risks. The Agent Ownership Card—a lightweight document capturing name, owner, job, d…
IBM deployed AI-powered virtual assistants Ask HR and Ask IT to handle 94% of routine employee queries without laying off any staff, demonstrating the AI augmentation model where AI handles repetitive…
The US government forced Anthropic to pull Claude Fable 5 globally—the first forced shutdown of a commercial AI model. The hypothetical scenario highlights how existing regulations like the EU AI Act …
Major companies including Starbucks, Klarna, and McDonald's are reversing AI deployments that replaced human workers, citing failures in customer satisfaction and operational accuracy. The rollback hi…
Uber engineers burned through $500 to $2,000 per month each on AI tokens, with some teams exhausting their entire quarterly AI budget within four months. The cost explosion is driven by agentic workfl…
Business owners using AI tools must decide whether to build custom solutions or buy existing SaaS. A two-criteria framework—whether a good-enough solution exists and whether the capability differentia…
Google DeepMind published a paper in 2025 outlining four pathways from artificial general intelligence (AGI) to artificial superintelligence (ASI): scaling, algorithmic innovation, recursive self-impr…
Zhipu AI's GLM 5.2 coding model can be used as a cost-effective backend for AI agents via OpenRouter, offering strong code generation and reasoning at 10-20% of the cost of Claude Sonnet or GPT-4o. Th…
A new automated workflow enables developers to run an overnight documentation sweep loop that reviews codebases for documentation gaps, updates outdated docs, and opens a pull request for human review…
Claude Code, an AI coding agent, lacks persistent memory across sessions, forcing developers to re-explain context repeatedly. A new guide outlines building a memory system with short-term session mem…
Half of US adults now use AI chatbots, yet more Americans expect negative societal impact than positive, according to Pew Research. The paradox reflects a split between personal utility and systemic r…
A new automated workflow enables teams to build a nightly production error sweep loop that scans logs, traces errors to root causes, generates fixes, and opens pull requests without human intervention…
A new automated agent loop enables weekly SEO and generative engine optimization (GEO) audits, finding technical issues, ranking them by impact, fixing them automatically, and rerunning until no criti…
Zhipu AI released GLM 5.2, a 744-billion-parameter open-weight language model with an MIT license, achieving coding benchmark scores that rival Claude Fable 5 at a fraction of the API cost. The model'…
Agent loops fail when stop conditions rely on subjective judgment rather than verifiable criteria. Developers must define deterministic, checkable conditions—such as passing a test or reaching a numer…
OpenAI has launched ChatGPT Scheduled Tasks, a feature for Plus, Pro, and Team subscribers that automates recurring prompts such as daily news briefings and email summaries. Users can set tasks to run…
Agentic loop failures often stem from poorly defined goals rather than model limitations. To prevent runaway or prematurely-terminating agent sessions, developers must write objective, verifiable goal…
AI agents can automate the entire content creation workflow from research to social posting in a single loop, reducing manual switching between tools. The agentic loop includes research, copywriting, …
AI agent harnesses—the prompts, parsing logic, and orchestration glue around models—break when models improve, not just when they fail. Better models can change output verbosity, reasoning patterns, o…