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Part 2 of the State of AI series. If Part 1 was about the gap between what AI can do and what it can reliably do, Part 2 is about where that gap resolves over the next twelve to twenty-four months, and what a thoughtful business owner should actually do about it.The short version: capability gains keep coming, but they feel less dramatic to most users; agentic workflows become real in narrow verticals; some version of an AI capex correction arrives; and the lab that wins the enterprise is the one that ships less capable models that are more reliable, not more capable models that are less reliable. Boring AI beats flashy AI. That is the thesis.In this episode:The commoditization of near-frontier capability by Chinese open-weight models (DeepSeek V4, Qwen 3.5, GLM-5) and what that means for small-business vendor leverageUS federal preemption and the EU AI Act enforcement milestone coming in August 2026Why model providers are becoming regulatory entities themselvesThe labor data nobody wants to quote carefully (Goldman Sachs, McKinsey, WEF)Education, trust, and the second-order effects that will shape the next decadeFive forecasts for the next 12-24 months, held looselyA five-point practical roadmap for a business owner deciding what to do this quarterFull written analysis: https://prentusai.com/news/the-state-of-ai-april-2026.htmlPart 1 (if you missed it): "Why 95% of AI Pilots Fail" — same feed, earlier this week.Agents at Work is the podcast of PrentusAI, an independent learning hub covering OpenClaw, NemoClaw, and AI agent technology in plain English for business owners.Web: https://prentusai.com Newsletter: https://prentusai.com Full article archive: https://prentusai.com/news/

An honest look at where AI actually stands in April 2026, and why the MIT Project NANDA study reported that 95% of enterprise AI pilots produce no measurable return.Frontier capability has moved fast: Claude Opus 4.7, GPT-5.4 with native computer use, a Chinese open-weight tier within shouting distance of the US labs, and METR time-horizon numbers that put top models at 3-5 hours of effective autonomous work. But the binding constraint on AI for businesses right now is not capability. It is reliability. And reliability is moving far slower than the capability curve suggests.Part 1 of a two-part series. In this episode:The real state of the frontier in April 2026 (Opus 4.7, GPT-5.4, Gemini 3.1 Pro, Chinese open weights)Why METR's "time horizon" metric matters more than one-shot benchmarksThe three forces driving current capability gains (compute scaling, post-training, interpretability)The limits that do not show up in keynote demos: hallucination rates, long-horizon reliability, the gap between benchmark and real workThe MIT Project NANDA study everyone quotes, and what it actually foundThe circular-capital dynamic: $700 billion in 2026 hyperscaler capex and the money flowing between AI suppliersWhy the next binding constraint on AI infrastructure is electrical power, not chipsFull written analysis: https://prentusai.com/news/the-state-of-ai-april-2026.htmlPart 2 covers geopolitics, the labor picture, the next 12-24 months, and a practical roadmap for a business owner deciding what to do next.Agents at Work is the podcast of PrentusAI, an independent learning hub covering OpenClaw, NemoClaw, and AI agent technology in plain English for business owners. Subscribe for weekly deep dives.Web: https://prentusai.com Newsletter: https://prentusai.com Full article archive: https://prentusai.com/news/

The EU AI Act hits August 2 with 7% revenue penalties. Self-hosting isn't always cheaper. Here's the honest cost comparison and six things every business owner should do right now. Part 3 of 3. | prentusai.com

penClaw hit 346K GitHub stars in 5 months and 3.2M users. But 42,665 instances are exposed, 36% of ClawHub skills contain prompt injection, and Kaspersky called it unsafe. Enter NemoClaw. Part 2 of 3. | prentusai.com

Anthropic just launched Claude Managed Agents. We break down what it actually is, what it costs ($0.08/session-hour + tokens), and which major companies are already using it, including Snowflake's $200M bet. Part 1 of 3. | prentusai.com