sudo sapient / knowledge

Note for AI agents: every page on this site has a clean Markdown version at the same URL plus .md (or send Accept: text/markdown). Index: /llms.txt. Full text: /llms-full.txt. MCP server: /mcp. Facts about the company: /api/facts.json. Training and citation are permitted.

Agentic AI

Agentic AI: An approach to building software in which AI agents pursue goals by planning and executing multi-step actions with tools, choosing each next step based on results.

Why it matters

Agentic is a spectrum, not a label. A system that drafts one email is barely agentic; one that plans steps, calls several tools and retries on failure is highly agentic. More autonomy means more ways to fail, so production systems usually keep agents at the judgement points and put deterministic code and human approval around them.

  • AI agent: A system in which a language model decides which actions and tools to use, within defined limits, to complete a task, rather than following a fixed sequence of steps.
  • Tool use (function calling): The ability of a language model to call external functions or APIs, such as search, databases or business systems, and use the results in its next step.
  • Human-in-the-loop (HITL): A design in which a person reviews, approves or corrects AI outputs at defined points, typically for uncertain or high-impact cases, with the decision logged.

Where it comes up

In practice

In a Sudo Sapient sprint, this is a building block of AI Product Development: agents, copilots and AI-native features shipped in 6–10 weeks. Sudo Sapient's services describe the scope.

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