Agentic capabilities
Also written: AI agents, Agent AI, Agent-based capabilities, Intelligent agents, Thinking capabilities, AI capabilities, AI abilities, Client capabilities
AI that can act on its own to do tasks for you.
Agentic capabilities mean AI can take actions and perform tasks without you needing to tell it every single step. Think of it like a helpful assistant that can figure out what needs to be done and then do it.
For example, instead of just telling an AI to write an email, an AI with agentic capabilities could understand the goal, find the right information, draft the email, and even send it based on your instructions. This allows AI to handle more complex, multi-step tasks.
Agentic capabilities refer to the ability of AI systems to autonomously plan, decide, and execute a sequence of actions to achieve a defined goal. This involves breaking down complex tasks into smaller steps, interacting with tools or environments, and adapting its plan based on intermediate results or new information.
These capabilities are crucial for moving beyond simple response generation towards AI systems that can actively manage workflows, perform complex operations, and act as more independent agents. The development in this area focuses on improving planning, tool use, and self-correction mechanisms.
Frontier AI labs are increasingly focusing on agentic capabilities, enabling models to autonomously plan and execute tasks. Recent developments show AI systems interacting with digital interfaces and controlling robots, moving beyond simple text generation to active participation in digital and physical environments. This shift highlights a push towards AI that can independently achieve goals with minimal human intervention.
- Gemini Robotics ER 1.6Google · Gemini Models ·
- Gemini 4 Argon: Google is back as one of the top three labs in intelligence achievedGoogle · Artificial Analysis ·
- Default Enablement of Copilot Features for Copilot Business and EnterpriseMicrosoft · GitHub Changelog: Copilot ·
- Gemini Robotics ER 1.6Google · Gemini Models ·
- Использование компьютераGoogle · Gemini Models ·
- Përdorimi i kompjuteritGoogle · Gemini Models ·
- Gemini Robotics ER 1.6Google · Gemini Models ·
- Anthropic details distillation campaigns from Alibaba, Moonshot AI, and DeepSeekAnthropic · TechCrunch AI ·
- Gemini Robotics ER 1.6Google · Gemini Models ·
- Turn your voice into action with new productivity features in Gemini LiveGoogle · The Keyword: Gemini ·
- Get closer to the game with Gemini and PixelGoogle · The Keyword: Gemini ·
- Evolve your marketing with new AI toolsGoogle · The Keyword: AI ·
- New ways to learn and teach with ChatGPT Work and CodexOpenAI · OpenAI News ·
- Introducing Claude Opus 4.5Anthropic · Anthropic News ·
- Building self-improving tax agents with CodexOpenAI · OpenAI News ·
- The next chapter for AI in the EUOpenAI · OpenAI News ·
- Horizon 1000: Advancing AI for primary healthcareOpenAI · OpenAI News ·
- Introducing LabsAnthropic · Anthropic News ·
- Gemini 3: Launch day reactionsGoogle · Google AI: Release Notes ·
- A new era of intelligence with Gemini 3Google · Google DeepMind Blog ·
- Disrupting the first reported AI-orchestrated cyber espionage campaignAnthropic · Anthropic News ·
- Building a frontier AI search experienceGoogle · Google AI: Release Notes ·
- Wayfair is shaping the future of retail with AIOpenAI · OpenAI News ·
- Anthropic Claude
- Anthropic's focus on advanced features, potentially including agentic capabilities, is highlighted by their efforts to protect these from distillation by other AI firms.
- Google Gemini
- Google Gemini is developing agentic capabilities for robots, allowing them to understand and act on complex commands in the physical world, and for computer use, enabling direct interaction with digital interfaces.
- Microsoft Copilot
- Microsoft Copilot is enabling new agentic features by default for business users, indicating a move towards more autonomous task completion within enterprise environments.
- Prompt engineering
- This is the art of crafting inputs to get desired outputs fr
- Fine-tuning
- This process adapts a pre-trained model to a specific task or datas
- Reinforcement learning
- While RL can be used to train agents to make decisions,
The concept of AI agents has roots in early AI research, but the current focus on agentic capabilities in large language models (LLMs) has been significantly advanced by recent research and development in the field, particularly with the advent of powerful LLMs capable of complex reasoning and tool use.
Try asking your AI assistant to 'plan a weekend trip to the mountains for me, including booking accommodation and suggesting activities.' See if it can outline the steps and ask clarifying questions, demonstrating its ability to act on your behalf.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- WorkflowBuild an AI agent evaluation pipeline in one hourCompress weeks of AI agent testing into one hour using open-source tools and automated pipelines. · 60 min
- HeuristicAI agents need time-awareness for runtime controlAI agents require a sense of time to predict, estimate, and control their own actions and execution duration. · 5 min
- Anti-patternUsing prototype defaults for production AI agent architectureDon't let prototype settings for AI models and prompts become production defaults; they are not optimized for scale or cost. · 60 min
- Cost tipLeverage prompt caching to reduce AI agent token costsReuse previously processed prompt prefixes to avoid reprocessing and save on token costs for agents. · 30 min
- HeuristicComposable controls for agent autonomy and safetyUse composable controls that perform single jobs, enabling agents to run with autonomy at appropriate safety levels. · 10 min
Questions people ask
- Can AI agents make decisions on their own?
- Yes, AI with agentic capabilities can make decisions as part of a sequence of actions to achieve a goal, often based on pre-defined parameters or learned behaviors.
- What's the difference between an AI assistant and an AI agent?
- An AI assistant typically responds to direct commands, while an AI agent can take initiative, plan, and execute multi-step tasks autonomously to achieve a goal.
First seen on Subvolts Feb 13, 2025. Updated Oct 17, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.