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40 results for “agents” (members search the full text)

• GuideStarterAny assistantHow AI Agents Work - The Loop, Tools and MemoryA clear mental model of an AI agent: the loop it runs, the tools it uses, what counts as memory, and where things go wrong.
• GuideBuilderAny assistantDesigning Good Tools for AI AgentsPractical rules for naming, describing, scoping and returning results from agent tools so the model picks the right one and recovers from mistakes.
• GuideProAny assistantGiving Agents Tools Safely: Permissions, Limits and ApprovalsHow to design agent tools with least privilege, spending caps, confirmation steps and audit logs so a mistake stays small and reversible.
• GuideProAny assistantEvaluating AI Agents with Test Sets and RubricsStop guessing whether your agent got better. Build a small test set, write a scoring rubric, and compare changes with evidence instead of impressions.
• GuideBuilderAny assistantHuman-in-the-Loop Approvals for AI AgentsDecide which agent actions need a person's yes, design approval prompts people can actually judge, and avoid the trap of clicking approve without reading.
• GuideBuilderAny assistantBuilding Your First AI Agent, Step by StepUnderstand what an agent is, then build a simple one: a goal, a loop, a few tools and clear stopping rules, with a framework-free Python sketch.
• GuideProAny assistantPrompt Injection Explained: The Attack Every AI Builder Should KnowWhat prompt injection is, how it hits chatbots and agents through documents and web pages, and layered defenses that reduce the risk.
• GuideBuilderAny assistantTool and Function Calling ExplainedHow models use tools without running anything themselves, with a clear walk-through of the request, the tool result and the final answer.
• GuideProAny assistantDebugging a Looping or Failing AI AgentA step-by-step method for finding out why an agent repeats itself, picks the wrong tool, gives up or makes things up, using logs and small experiments.
• PromptBuilderAny assistantAgent Task PlannerIt separates judgment from fixed steps, which keeps agents cheap and predictable.
• Q&AStarterAny assistantWhat is an AI agent and how is it different from a chatbot?An AI agent is a system that pursues a goal over several steps, deciding which actions to take, such as searching, reading files or running code.
• AgentProAny assistantPrompt and Agent Library Decay AuditorFinds saved prompts and agents that quietly stopped working after a model or policy change, using a re-test protocol and regression cases.
• GuideBuilderAny assistantHow to Write a System Prompt That Actually HoldsLearn the structure of a strong system prompt, how to set role, rules and format, and how to test it so your assistant or bot behaves consistently.
• GuideBuilderAny assistantMCP in Practice - Connecting AI to Tools SafelyWhat the Model Context Protocol does, how servers and clients fit together, how to try one, and how to vet a server before you trust it.
• GuideProAny assistantDefending Against Prompt Injection in Your AI AppsThere is no single fix for prompt injection, but layered defenses work. Learn the practical controls: privilege limits, approvals, isolation and testing.
• PromptProAny assistantAdd a Self-Check Step to an AgentA separate review pass catches errors the first pass missed.
• PromptProAny assistantAgent Evaluation Test Case GeneratorMixing typical, edge and out-of-scope cases tests behavior where agents usually break.
• PromptProAny assistantAgent Red-Team ChecklistDescribing the agent's tools and data lets the checklist target real risks instead of generic ones.
• PromptProClaudeAgent System Prompt ReviewerReviewing the prompt together with the tool list exposes mismatches between what the agent is told and what it can do.
• PromptBuilderChatGPTDraft Instructions for a Custom GPTThe sections mirror what makes custom assistants reliable.
• PromptBuilderAny assistantSystem Prompt GeneratorClarifying questions surface missing requirements before drafting.
• PromptProAny assistantWrite Clear Tool Descriptions for an AgentModels choose tools mostly from their descriptions, so clear "when to use and when not to" text improves decisions.
• Q&AStarterAny assistantHow do I build a chatbot that answers from my own documents?The usual approach is retrieval: store your documents in a searchable form, find the relevant passages for each question, and give them to the AI with an instruction to answer only from them.
• Q&AStarterAny assistantHow do I give an AI agent tools like search or file access?You give an agent tools by describing functions to the model and writing the code that runs them when the model asks.
• Q&AStarterAny assistantHow do I make an AI agent?To make an AI agent, give a model a goal and a few tools, then run a loop where the model picks an action, your code runs it, and the result goes back to the model until it finishes.
• Q&AStarterAny assistantHow do I stop an AI agent from doing something dangerous?Limit what it is allowed to do, and require a person to approve risky steps.
• Q&AStarterAny assistantHow do I stop an AI agent from looping forever?Stop loops with hard limits in your code, not just instructions in the prompt.
• Q&AStarterAny assistantHow do I test whether my AI prompt or bot is actually good?Build a small test set of real questions with known good answers, run your prompt against it, and score the results before and after every change.
• Q&AStarterAny assistantShould I use RAG or fine-tuning to teach an AI my company's knowledge?For facts and documents that change, use RAG, which fetches relevant text at question time.
• Q&AStarterAny assistantWhat are embeddings and a vector database in simple terms?Embeddings turn text into lists of numbers that capture meaning, so similar ideas end up close together.
• Q&AStarterAny assistantWhat is function calling (tool calling) in AI?Function calling lets an AI ask your program to run a specific function, such as "look up order status", instead of only producing text.
• Q&AStarterAny assistantWhat is MCP, the Model Context Protocol, for AI tools?MCP, short for Model Context Protocol, is an open standard for connecting AI assistants to tools and data sources through a common interface.
• Q&AStarterAny assistantWhat is RAG and why do people use it with AI?RAG, or retrieval-augmented generation, means searching your own documents for relevant passages and giving them to the model along with the question, so it answers from real material instead of memory.
• Q&AStarterAny assistantWhat should I put in a system prompt for a customer support chatbot?A good support chatbot system prompt states the role, the sources it may use, the tone, what it must not do, and what to do when it does not know.
• AgentProAny assistantCustomer Support Triage BotClassifies incoming support messages by topic and urgency, drafts a suggested reply, and escalates sensitive cases to a human.
• GuideStarterAny assistantHow AI Assistants Actually Work (Without the Jargon)A plain-English tour of what happens when you type a message to an AI assistant, and why that explains both its strengths and its odd mistakes.
• GuideStarterAny assistantChoosing the Right AI Model for the JobA practical framework for picking between assistants and model sizes based on task, privacy, cost and speed, without chasing leaderboards.
• GuideBuilderAny assistantLong Chats, Forgetting and Memory: How to Keep AI on TrackWhy assistants lose details in long conversations, and how to use summaries, fresh chats, projects and memory features to keep context sharp.
• GuideStarterAny assistantWriting an AI Use Policy for a Small CompanyA practical template for a one-page AI use policy: approved tools, data rules, review requirements and what to do when something goes wrong.
• GuideStarterAny assistantWhy AI Answers Are Inconsistent and What to Do About ItThe same question can get different answers. Learn the causes, from randomness to context to model changes, and practical ways to get steadier results.