Vibe gets to work.
Mistral upgraded Le Chat to Vibe, a unified AI agent covering work and coding, retaining all existing conversations, settings and subscription plans.
AI agents
All topicsModels that plan, call tools and finish multi-step tasks on their own: from Claude Code and Manus to agent frameworks and benchmarks.
107selectedRelated topicsMCP and tool useAI codingReasoning
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81–100 of 107May 28
May 22
Remote agents in Vibe. Powered by Mistral Medium 3.5.
Mistral released Mistral Medium 3.5, its first 128B dense model combining instruction following, reasoning and coding. Its weights are available under a modified MIT licence, with a 256k context window and self-hosting possible on a minimum of four GPUs.
Connect the dots: Build with built-in and custom MCPs in Studio
Mistral released Connectors in Studio. Built-in connectors and custom MCP are available through API/SDK for all model and agent calls, currently in public preview.
May 20
Empirical Research Assistance (ERA): From Nature publication to catalyzing Computational Discovery
Google released Empirical Research Assistance (ERA), a research tool using Gemini to write and optimise scientific code. Its paper was published in Nature today, and the tool is available to scientists worldwide as part of Gemini for Science.
May 18
Simulate real-world places with Project Genie and Street View
Google DeepMind added Street View grounding to experimental prototype Project Genie. Users select a real US location with a Maps pin, choose a style and describe a character, then Genie creates an interactive world whose starting location is grounded in real imagery.
May 17
Gemini for Science: AI experiments and tools for a new era of discovery
Google DeepMind released Gemini for Science, launching three experimental tools on Google Labs: Hypothesis Generation based on Co-Scientist.
May 16
Gemini 3.5: frontier intelligence with action
Google DeepMind launched the Gemini 3.5 family with 3.5 Flash, focusing on agents and coding. It is available from today in the Gemini app, Google Search AI Mode, Google Antigravity, Gemini API and Gemini Enterprise.
May 12
Co-Scientist: A multi-agent AI partner to accelerate research
Google DeepMind published Co-Scientist research in Nature, describing a Gemini-based multi-agent AI system that iteratively generates, debates and evolves scientific hypotheses.
May 6
AlphaEvolve: How our Gemini-powered coding agent is scaling impact across fields
Google DeepMind published a year’s progress for AlphaEvolve. The Gemini-powered coding agent has expanded from open problems in mathematics and computer science into genomics, power grids, quantum physics and AI infrastructure.
Apr 30
Enabling a new model for healthcare with AI co-clinician
Google DeepMind announced AI co-clinician research to explore AI agents assisting patient care under clinical supervision. In blinded assessments of 98 real primary-care queries, 97 responses had no critical errors, and doctors preferred them to existing evidence-synthesis tools. Across 140 consultation skills, AI matched or exceeded primary-care doctors on 68, but expert doctors were better overall at recognising red flags and guiding key physical examinations.
Four ways Google Research scientists have been using Empirical Research Assistance
Google Research described how scientists use Empirical Research Assistance (ERA) to advance research in four areas: epidemic forecasting, cosmology, carbon monitoring and neuroscience.
Apr 27
Workflows for work that runs the business
Mistral AI released Workflows in public preview, positioning it as an enterprise AI orchestration layer with durable execution, observability and fault tolerance to take AI workflows from proof of concept to production.
Apr 22
ReasoningBank: Enabling agents to learn from experience
Google Research released the ICLR paper ReasoningBank, an open-source agent memory framework that distils high-level reasoning patterns from successful and failed experiences.
Mar 29
Reimagining the mouse pointer for the AI era
Google DeepMind unveiled an experimental Gemini-powered AI pointer that understands not only what it points at but what it means to the user. The team proposed four interaction principles: avoiding workflow interruption, capturing nearby visual and semantic context, supporting natural shorthand such as “this” and “that”, and turning pixels into actionable entities such as places, dates and objects.
Mar 25
Vibe Coding XR: Accelerating AI + XR prototyping with XR Blocks and Gemini
Google released Vibe Coding XR, combining Gemini with the XR Blocks framework based on WebXR, three.js and LiteRT.js to turn natural language prompts directly into physically aware Android XR apps, reportedly in under 60 seconds.
Mar 18
Introducing Forge
Mistral AI launched Forge, a system for enterprises to build frontier-class AI models on proprietary knowledge, supporting pre-training, post-training and reinforcement learning. It handles dense and MoE architectures and, when needed, multimodal inputs, with training and governance on companies' own infrastructure.
Mar 11
Rails testing on autopilot: Building an agent that writes what developers won't
Mistral built an autonomous agent on its open-source coding assistant Vibe to read Rails source files, generate or improve RSpec tests and run within CI/CD without human intervention.
Jan 28
Terminally online Mistral Vibe.
Mistral released the terminal coding agent Mistral Vibe 2.0, powered by the Devstral 2 model family, adding custom subagents, multiple-choice clarifications, slash-command skills, unified agent modes and automatic updates.
Dec 9
Introducing: Devstral 2 and Mistral Vibe CLI.
Mistral AI released the next-generation Devstral 2 coding family, including 123B Devstral 2 under a modified MIT licence and 24B Devstral Small 2 under Apache 2.0, both open-source.
Oct 24
Introducing Mistral AI Studio.
Mistral released Mistral AI Studio, a production AI platform for enterprise teams built on three pillars: Observability, Agent Runtime and AI Registry.