This story was originally published on HackerNoon at: https://hackernoon.com/governing-and-scaling-ai-agents-operational-excellence-and-the-road-ahead.
Success isn't building the agent; it's managing it. From "AgentOps" to ROI dashboards, here is the operational playbook for scaling Enterprise AI.
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This story was written by: @denisp. Learn more about this writer by checking @denisp's about page, and for more stories, please visit hackernoon.com.

Defines “AgentOps”: metrics, monitoring and feedback loops to run AI agents as long-lived products rather than fragile pilots Surveys the emerging tooling and platform landscape and links it to regulatory trends such as upcoming AI governance requirements Explores cultural and organisational shifts: new roles, trust-building and change management – and closes with a pragmatic roadmap for the next 3–5 years

This story was originally published on HackerNoon at: https://hackernoon.com/we-let-an-ai-run-a-business-here-are-4-of-the-strangest-things-that-happened.
Researchers at Anthropic gave an AI named Claudius a real-world job: running a small shop in their office.
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This story was written by: @hacker-Antho. Learn more about this writer by checking @hacker-Antho's about page, and for more stories, please visit hackernoon.com.

Researchers at Anthropic gave an AI named Claudius a real-world job: running a small shop in their office. The experiment revealed surprising, counter-intuitive gaps between AI capability and real- world robustness.

This story was originally published on HackerNoon at: https://hackernoon.com/a-new-benchmark-arms-race-is-redefining-what-good-at-ai-even-means.
A new class of benchmarks is emerging to measure how well these systems reason, act, and recover across complex workflows
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This story was written by: @ainativedev. Learn more about this writer by checking @ainativedev's about page, and for more stories, please visit hackernoon.com.

A new class of benchmarks is emerging to measure how well these systems reason, act, and recover across complex workflows.

This story was originally published on HackerNoon at: https://hackernoon.com/can-chatgpt-outperform-the-market-week-20.
I need YOUR help for the future!
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I need YOUR help for the future!

This story was originally published on HackerNoon at: https://hackernoon.com/video-data-synthesis-categorizing-matting-difficulty-by-instance-overlap.
MaGGIe utilizes the V-HIM2K5 and V-HIM60 datasets, categorizing video instance matting into three difficulty levels based on occlusion and overlap.
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This story was written by: @instancing. Learn more about this writer by checking @instancing's about page, and for more stories, please visit hackernoon.com.

MaGGIe utilizes the V-HIM2K5 and V-HIM60 datasets, categorizing video instance matting into three difficulty levels based on occlusion and overlap.

This story was originally published on HackerNoon at: https://hackernoon.com/patterns-that-work-and-pitfalls-to-avoid-in-ai-agent-deployment.
Avoid the "AI Slop" trap. From runaway costs to memory poisoning, here are the 7 most common failure modes of Agentic AI (and how to fix them).
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This story was written by: @denisp. Learn more about this writer by checking @denisp's about page, and for more stories, please visit hackernoon.com.

Highlights deployment patterns that consistently deliver value: start assistive then automate, use specialised multi-agent teams, and go event-driven Details common failure modes: unclear goals, over-promising capabilities, messy data, integration gaps, runaway token costs – and how to mitigate them Provides a checklist to stress-test agent projects before scaling, so you can avoid being part of the “cancelled by 2027” statistic

This story was originally published on HackerNoon at: https://hackernoon.com/matting-robustness-maggie-performance-across-varying-mask-qualities.
MaGGIe demonstrates superior quantitative performance on HIM2K and M-HIM2K, outperforming MGM-style refinement with its sparse guided progressive refinement.
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This story was written by: @instancing. Learn more about this writer by checking @instancing's about page, and for more stories, please visit hackernoon.com.

MaGGIe demonstrates superior quantitative performance on HIM2K and M-HIM2K, outperforming MGM-style refinement with its sparse guided progressive refinement.

This story was originally published on HackerNoon at: https://hackernoon.com/anthropic-moves-to-tame-llm-format-friction-with-schema-enforced-responses.
Anthropic's new Structured Outputs feature on the Claude Developer Platform enhances API response reliability by enforcing strict JSON schemas.
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This story was written by: @ainativedev. Learn more about this writer by checking @ainativedev's about page, and for more stories, please visit hackernoon.com.

Anthropic's new Structured Outputs feature on the Claude Developer Platform enhances API response reliability by enforcing strict JSON schemas.