The future is future fitness. The advantage isn’t prediction. It’s how fast your team can notice and anticipate change and respond.
How context rot drags down AI and LLM results for enterprises, and how to fix it
Everyone is chasing smarter models. Wrong race. In most businesses, AI does not fail because the model is weak. It fails because the context is broken. So the AI sounds intelligent. But it is reasoning on rotten context.
Intelligence is becoming a commodity. Context is becoming the asset. The winners will not be the companies with the flashiest demos. They will be the ones that build living context.
AI without context is theatre. Context without upkeep becomes rot. Treat context as infrastructure.
- https://thenewstack.io/context-rot-enterprise-ai-llms/
- https://a16z.com/your-data-agents-need-context/
- https://adlrocha.substack.com/p/adlrocha-intelligence-is-a-commodity
The prompt
Where is the critical context in your business still trapped?
The other prompts:
My latests book about books about AI
Data, acceleration, and the future of intelligence: Lessons from 25 core books about AI, technology abstraction, and consciousness.
https://www.ronimmink.com/product/a-book-about-books-about-ai/
Reinventing the data core: The arrival of the adaptable AI data foundry
As agentic AI and regulatory demands accelerate, organizations must reinvent their data core with an adaptable data foundry to ensure scalable, explainable, and compliant AI-driven outcomes
https://www.thomsonreuters.com/en-us/posts/technology/reinventing-data-core-adaptable-data-foundry/
Hype or Inevitable Future: Will LLMs Transform Industrial IoT?
The value of LLMs is clearest in Predictive Maintenance (PdM) systems. IIoT architecture can be thought of in layers: at the lower level — sensors, edge devices, and gateways — specialized ML algorithms handle analytics; at the higher level, where human interaction happens, LLMs interpret and communicate insights.
https://www.iotforall.com/llms-transform-iiot
The Data Team’s Survival Guide for the Next Era of Data
6 pillars to declutter your stack, escape the service trap, and build the missing foundations for the new primary data consumer: the AI agent.
https://towardsdatascience.com/the-data-teams-survival-guide-for-the-next-era-of-data/
Autonomous AI Agents Have an Ethics Problem
AI-powered digital assistants can do many complex tasks on their own. But who takes responsibility when they cause harm?
https://singularityhub.com/2026/03/06/autonomous-ai-agents-have-an-ethics-problem/
How brain networks work together is key to human intelligence
Researchers have conducted a neuroimaging study to investigate how the brain is organized and how that integrated system gives rise to intelligence.
https://www.futurity.org/brain-networks-human-intelligence-3322642/
Explainable AI is making black box models worthless in the agentic era
Explainable AI is essential as organizations embrace AI agents
https://www.techradar.com/pro/explainable-ai-is-making-black-box-models-worthless-in-the-agentic-era
Enterprise AI’s biggest risk isn’t the model — it’s the data
As companies deploy AI agents across core operations, fragmented and unreliable data is emerging as the biggest risk — threatening trust, accuracy and the ability to scale AI responsibly
https://www.ynetnews.com/tech-and-digital/article/hyllp2otbl
The “Last Mile” Problem Slowing AI Transformation
The primary obstacle to progress is rarely model quality or data availability, but rather the “last mile” of transformation where technical capability must meet organizational design. There are seven frictions that contribute to this problem: proliferation of pilots, the productivity gap, process debt, the identity problem of tribal knowledge, agentic governance, architectural complexity, and the efficiency trap
https://hbr.org/2026/03/the-last-mile-problem-slowing-ai-transformation
Management has been a casualty of AI. Now the tech is reviving it.
AI’s infusion in businesses means a reconsideration of the traditional org chart, writes BI’s Lakshmi Varanasi. The “Great Flattening” is still all the rage, but the rise of AI agents requires their management and oversight.
https://www.businessinsider.com/ai-agents-managers-management-business-great-flattening-2026-3
