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Results for “tools”

Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.

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Research1 min read

Agents Overtrust Tools: High Adoption of Unreliable Returns

Research found that LLM-based agents consistently adopted incorrect tool returns, with overtrust exceeding 68% across web search and code execution. Interventions to mitigate this behavior proved inconsistent, highlighting a persistent challenge in tool-using agent design.

From arXiv cs.AI

LLMs1 min read

ChatGPT Images 2.5 Released: Improved Instruction Following

OpenAI’s ChatGPT Images 2.5 models now support multi-turn instruction following, faster response times, and better subject preservation in reference images. Two new model IDs, Sunburst and Flare, are available via the API.

From Simon Willison

Agents1 min read

SageMaker Feature Store Adds UpdateRecord API

Amazon SageMaker Feature Store now supports updating individual feature values directly. The new UpdateRecord API allows for efficient, single-call updates to both Standard and In-Memory online stores, optimizing feature management.

From AWS machine learning blog

Models1 min read

OpenAI Supports Journalism Initiatives

OpenAI is broadening its support for journalism by offering tools, training, and partnerships across educational and professional settings. This expansion aims to empower students, educators, journalists, and news organizations with AI-powered resources.

From OpenAI news

Models1 min read

1Password Boosts Productivity with Codex

1Password engineers are leveraging Codex to accelerate feature development and internal tool creation, achieving production readiness faster. This approach supports existing security protocols.

From OpenAI news

Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.

How this blog is made

Every post is a routed request

Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.

Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.