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Anthropic introduces Managed Agents on Claude, a managed execution layer for agent-based workflows. It separates agent logic from runtime concerns like orchestration, sandboxing, state management, and credentials. The system supports long-running multi-step workflows with external tools, error recovery, and session continuity via a meta-harness architecture.
Slack has rebuilt its notification system with a unified architecture that separates activity from delivery, improving consistency across platforms. The redesign simplifies preferences, preserves legacy settings through transformation, and resulted in a 5x increase in user engagement with notification settings along with reduced support tickets.
GitHub has publicly addressed a series of recent availability and performance issues that disrupted services across its platform, attributing the incidents to rapid growth, architectural coupling, and limitations in handling system load.
Sudeep Das and Pradeep Muthukrishnan explain the shift from static merchandising to dynamic, moment-aware personalization at DoorDash. They share how LLMs generate natural-language "consumer profiles" and content blueprints, while traditional deep learning handles last-mile ranking. This hybrid approach allows the platform to adapt to short-lived user intent and massive catalog abundance.
PDF table extraction often looks easy until it fails in production. Real bank statements can be messy, with scanned pages, shifting layouts, merged cells, and wrapped rows that break standard Java parsers. This article shares how we redesigned the approach using stream parsing, lattice/OCR, validation, scoring, and selective ML to make extraction more reliable in real banking systems.
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Anthropic Introduces Managed Agents to Simplify AI Agent Deployment
Anthropic introduces Managed Agents on Claude, a managed execution layer for agent-based workflows. It separates agent logic from runtime concerns like orchestration, sandboxing, state management, and credentials. The system supports long-running multi-step workflows with external tools, error recovery, and session continuity via a meta-harness architecture.
By Leela KumiliSlack Rebuilds Notification System, Reports 5X Increase in Settings Engagement
Slack has rebuilt its notification system with a unified architecture that separates activity from delivery, improving consistency across platforms. The redesign simplifies preferences, preserves legacy settings through transformation, and resulted in a 5x increase in user engagement with notification settings along with reduced support tickets.
By Leela KumiliGitHub Acknowledges Recent Outages, Cites Scaling Challenges and Architectural Weaknesses
GitHub has publicly addressed a series of recent availability and performance issues that disrupted services across its platform, attributing the incidents to rapid growth, architectural coupling, and limitations in handling system load.
By Craig RisiPresentation: Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash
Sudeep Das and Pradeep Muthukrishnan explain the shift from static merchandising to dynamic, moment-aware personalization at DoorDash. They share how LLMs generate natural-language "consumer profiles" and content blueprints, while traditional deep learning handles last-mile ranking. This hybrid approach allows the platform to adapt to short-lived user intent and massive catalog abundance.
By Sudeep Das, Pradeep MuthukrishnanArticle: Redesigning Banking PDF Table Extraction: A Layered Approach with Java
PDF table extraction often looks easy until it fails in production. Real bank statements can be messy, with scanned pages, shifting layouts, merged cells, and wrapped rows that break standard Java parsers. This article shares how we redesigned the approach using stream parsing, lattice/OCR, validation, scoring, and selective ML to make extraction more reliable in real banking systems.
By Mehuli Mukherjee