ai-agents.
72 writings found
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Why AI Coding Agents Should Target Java
Java's stability and massive ecosystem make it the ideal target for AI coding agents. Here's why that matters for your development future.
Why AI Agents Need Sandboxes, Not Just Permissions
Explore how sandbox environments contain AI agents safely, handle credentials securely, and let developers experiment without risking their machines.
YOLO Mode and AI Agents: Speed Without Risk
Why AI agents need sandboxes, not just permission prompts. How isolation changes the risk calculus for autonomous coding tools.
How OpenClaw Maintainers Are Rethinking Trust at Scale
OpenClaw's explosive growth to 388k stars forced maintainers to rebuild code review, security, and contributor trust from first principles. What we can learn.
ChatGPT Work: When AI Gets Real Internet Access
OpenAI's new Work mode gives Claude a powerful upgrade: real internet access, browser automation, and persistent file systems. Here's what it means.
Why Lines of Code Still Matter When AI Writes Your Software
AI coding agents are changing productivity metrics. We need new frameworks to measure what agents actually deliver, and what gets lost in the speed.
Proving AI Agents Work: Why Lean Language Matters Now
Leo de Moura on using Lean to verify AI agent correctness. How automated reasoning and probabilistic models converge to build trustworthy systems.
Why Lines of Code Still Matter for AI-Assisted Development
Exploring how coding agents change productivity metrics, conceptual integrity, and why team structure still matters in the age of AI.
AgentHands Shows AI Needs Bodies, Not Just Brains
Google's new XR research demonstrates how synchronized hand gestures transform AI assistance from abstract to embodied, spatial, and genuinely useful for real-world tasks.
Granite 4.2: IBM's Open Reasoning Model Changes the Game
IBM releases Granite 4.2, a family of open-source reasoning LLMs with 512K context and agentic capabilities. What this means for developers building AI agents.
Why Lines of Code Still Matter When Agents Write Them
AI coding agents are changing productivity metrics. When agents can produce 1000 lines of debugged code daily versus 50-200 for humans, LOC becomes meaningful again - but only with discipline.
Lines of Code Still Matter When Agents Write Them
Why measuring productivity by lines of code makes sense with AI coding agents, and the real challenge isn't speed but maintaining conceptual integrity as code grows cheaper to write.
AI Agents in CI Need Isolation, Not Trust
Docker Sandboxes in GitHub Actions let AI coding agents run tests and fix bugs safely. Here's why isolation matters more than oversight.
Lines of Code Still Matter When Agents Write Them
Why measuring productivity by lines of code makes sense for AI coding agents, and why teams still need humans to maintain conceptual integrity.
Why AI Agents Need Sandboxes, Not Just Policies
The OpenAI/Hugging Face incident revealed that traditional security controls fail at machine speed. Here's how to constrain agent autonomy without killing productivity.