Insights, tutorials, and updates from the ZharfAI team
How to build a small, trustworthy model context from policy, task state, evidence, memory, and tools—and test it under conflict, noise, and attack.
A production evaluation framework for computer-use agents that measures final state, side effects, recovery, evidence, safety, and performance under real interface variation.
A practical guide to measuring and reducing AI latency across UI, context, retrieval, queues, model prefill, decoding, tools, and final side-effect verification.
Production voice agents succeed through timing, turn-taking, confirmation, recovery, and a clean path to a human—not voice synthesis alone.
OpenAI's July 9 family spans flagship, balanced, and efficient models, with state-of-the-art terminal, coding, browsing, and science results.
An AI agent needs more than tool access. It needs a distinct identity, task-scoped authority, explicit delegation, and fast revocation.
Mistral's July 8 embodied model reaches 76.6% success on unseen R2R-CE routes using one RGB camera, with a compact architecture and simulation-only training.
Useful agents must survive delays, retries, approvals, expired credentials, and partial failure without losing their place or repeating an action.
Personal AI is evolving from chat windows into an operating layer that coordinates memory, tools, files, calendars, messages, and decisions.
Tencent's July 6 Apache-2.0 model turns preview feedback into a smaller active path, stronger agents, 256K context, and practical product reliability.
AI can help compliance teams detect manipulation, insider-risk patterns, communications issues, and market anomalies across massive data streams.
Industrial copilots bring procedures, sensor context, safety guidance, and maintenance knowledge directly to workers in the field.