Ornith, a new family of open source LLM models from the DeepReinforce research collective, takes a novel approach to executing coding and debugging tasks: It generates an architectural framework to give the user’s harness a structured instruction set – a scaffold – to create an agent to complete the job. Available in a set of four variants, the Ornith family was trained to work comfortably with complex software repositories undertaking complicated long-horizon jobs. Sure, LLMs can do these tasks now – until the job gets too complex. Ornith’s self-generated scaffolding ensures that it doesn’t forget the plot along the way. “The model continuously improves not only its code generation abilities but also the orchestration strategy used to solve software engineering problems,” wrote AI tutorial engineer Mehul Gupta, in an introductory post . Deep Reinforcement Expansion Pack Ornith reads the user’s instruction, but instead of executing it directly it builds a scaffold, a learnable ob...
Anthropic introduced a self-hosted gateway this week that lets enterprises run Claude Code on Amazon Bedrock and Google Cloud without the credential sprawl and manual setup that have typically come with deploying AI coding tools at scale. The Claude apps gateway is a single, stateless container that organizations deploy on their own infrastructure and back with a PostgreSQL database. It centralizes identity, policy enforcement, usage tracking, and spend management for Claude Code, addressing a problem that will sound familiar to anyone who has tried to roll out a developer tool across a large engineering org: Every new hire needs a cloud credential, every laptop needs the right settings pushed to it, and finance needs a way to see who’s spending what. Before the gateway, none of that was centralized. IT teams provisioned a credential per developer, manually distributed configuration, and stitched together separate tooling just to get visibility into spend. That’s a lot of ...