Introducing workspace agents in ChatGPT (9 minute read)
OpenAI introduced workspace agents in ChatGPT, allowing teams to create shared AI agents for complex tasks and workflows. These agents, powered by Codex, perform tasks like generating reports, writing code, and managing communication, while integrating with various tools like Slack. Workspace agents are currently available in research preview for select ChatGPT plans, aiming to streamline collaboration and improve productivity.
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Google debuts Workspace Intelligence for Gemini Workspace (4 minute read)
Google launched Workspace Intelligence, enhancing Google Workspace with a semantic layer to integrate emails, chats, files, and projects for Gemini-powered agents. This update includes major product enhancements like natural-language spreadsheet building in Sheets and AI-driven features in Docs, Slides, Gmail, and Drive. Workspace Intelligence aims to make Workspace a centralized control layer for business operations, emphasizing security, context integration, and cross-application functionality.
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Advancing Search-Augmented Language Models (19 minute read)
Perplexity's two-stage pipeline for search-augmented language models uses initial Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) to optimize factual accuracy, user preference, and tool-use efficiency. This approach, starting with Qwen3 models, separates compliance from search improvement to achieve accuracy without compromising guardrails. The models showed enhanced accuracy on benchmarks like FRAMES and FACTS OPEN with reduced cost per query and improved efficiency in tool usage over existing models like GPT-5.4.
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Benchmarking Inference Engines on Agentic Workloads (9 minute read)
Agentic workloads are reshaping inference engine benchmarks, demanding multi-turn, tool-using scenarios that strain KV cache management and scheduling due to longer traces and varied token distributions. Applied Compute introduced three workload profiles to aid in optimizing engine and accelerator performance. They released an open-source benchmarking tool to replay these scenarios, highlighting the need for solutions such as KV cache offloading and workload-aware routing to improve throughput and efficiency.
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Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model (2 minute read)
Qwen3.6-27B delivers flagship-level agentic coding performance. The Qwen team claims that it surpasses the previous-generation flagship Qwen3.5-397B-A17B across all major coding benchmarks. The model is 55.6 GB on Hugging Face, and there are even smaller quantized versions available. Tests show that the model delivers outstanding results, even when quantized.
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Introducing Gemini Enterprise Agent Platform, powering the next wave of agents (17 minute read)
The Gemini Enterprise Agent Platform is a comprehensive platform for building, scaling, governing, and optimizing agents. It brings together model selection, model building, and agent building capabilities together with new features for agent integration, DevOps, orchestration, and security. Agent Platform is a single destination for technical teams to build agents that can transform products, services, and operations. The agents can be delivered to employees through the Gemini Enterprise app.
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Building agents that reach production systems with MCP (14 minute read)
Agents can connect to external systems through direct API calls, CLIs, and MCP. This post looks at where each fits and the patterns for building those integrations effectively. MCP becomes the critical compounding layer as production agents move to the cloud. Every integration built on MCP strengthens the ecosystem.
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When LLMs Get Personal (20 minute read)
Personalization in LLM responses introduces variation but often retains a stable semantic core across answers. This shared foundation results from common model priors, overlapping retrievals, and product constraints, with differences emerging in examples and emphasis. Understanding this allows businesses to optimize their presence in AI-generated content by focusing on being part of the model's core knowledge.
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You're the Bread in the AI Sandwich (4 minute read)
AI is enhancing engineering workflows by handling execution, leaving humans to plan, review, and ensure quality output. Humans excel at diagnosing problems from multiple angles, a challenge for AI. Organizational AI strategies in the future will likely include personalized assistants for employees or a singular super-agent with departmental plugins.
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How to really stop your agents from making the same mistakes (7 minute read)
Relying on prompts to correct recurring AI agent mistakes is an unreliable, "vibes-based" approach that decays as soon as conversations become complex. To solve this, Y Combinator CEO Garry Tan advocates for "skillification." Instead of letting an agent waste compute attempting to solve deterministic tasks (like historical calendar lookups) in its latent space, this framework forces the AI to execute precise local scripts.
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