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Trends for Modern Teams

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When Agents Break

The growing shift in tech reframes traditional software as “AI agents,” promising systems that act rather than simply respond, but in reality these agents operate within guided, probabilistic boundaries rather than true autonomy. Today’s AI agents fail differently from traditional software—not with clear crashes, but through ambiguous, often confident decisions that can be subtly wrong and difficult to trace. This tension, along with the idea that many agents are essentially rebranded SaaS, emphasizes the need to design for visible, controllable failure rather than assuming reliability.

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Emily Mao

May 4

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image of The End of Cold Start: How I used AI to ramp up on a new codebase
The End of Cold Start: How I used AI to ramp up on a new codebase

How has AI changed software development?

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Cheryl Ngai

April 28

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image of The AI Trust Gap: Why Most Americans Are Still Skeptical of Artificial Intelligence
The AI Trust Gap: Why Most Americans Are Still Skeptical of Artificial Intelligence

Public skepticism toward AI stems less from its capabilities and more from a lack of trust, driven by its rapid pace of development, job displacement fears, sensationalized media narratives, and limited transparency. Many people feel uncertain and out of control as AI evolves faster than they can understand or adapt. While AI can enhance productivity, it cannot truly replace human creativity or original thought, making it better understood as a tool rather than a substitute for human intelligence.

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Emily Mao

April 28

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AI in Animatronics

An exploration of how artificial intelligence is transforming animatronics from scripted machines into lifelike, interactive characters. Through personal reflections and the excitement surrounding innovations like the new Olaf animatronic at Disneyland, this article looks at how AI is creating more emotional, immersive, and unforgettable experiences.

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Jonathan Mo

April 28

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Personalized Learning Through AI Tutors

AI tutors are reshaping education through personalized learning experiences tailored to each student’s pace, strengths, and learning style. It also examines the benefits, challenges, and future potential of combining artificial intelligence with traditional teaching methods.

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Jonathan Mo

April 28

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image of Claude Code Explained to a *Business Executive*
Claude Code Explained to a *Business Executive*

The strategic case for Claude Code, written in the register of a board memo. Cost economics, the redeployment thesis, the safety model, and the one question to ask your CTO this quarter.

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Raj Lal

April 28

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image of The *Architecture* of Claude Code
The *Architecture* of Claude Code

AsyncGenerator pipelines, the ReAct core loop, the dependency-injected permission system, write-ahead transcript persistence, and the six patterns composing the whole system.

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Raj Lal

April 28

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image of How Claude Code Works in *Plain English*
How Claude Code Works in *Plain English*

Claude Code in plain English: a system with a brain, a set of hands, eyes, and a memory. The clearest non-technical explainer of agentic AI you will read this year.

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Raj Lal

April 28

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image of How Claude Code *Works*: A Field Guide at Three Altitudes
How Claude Code *Works*: A Field Guide at Three Altitudes

The most consequential agentic AI tool of 2026, explained at three levels of detail. Pick the one that starts at your altitude. Then keep climbing.

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Raj Lal

April 28

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