The outcome

Provide persistent assistance without cross-user memory leakage, unauthorized tools, or uncontrolled stored context.

Agno is a Agent platform formerly known as Phidata for Python agents, teams, workflows, memory, knowledge, evaluation, tracing, and AgentOS operations. Building Python agents, specialist teams, and deterministic workflows, then serving and managing them through AgentOS with sessions, memory, knowledge, tracing, evaluation, RBAC, and approvals. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define surfaces, users, tenants, agent role, data classes, model, knowledge, tools, session and memory policy, retention, approvals, SLO, budget, and audit ownership.

  2. 02

    Deploy AgentOS privately with authenticated routes, a production database, least-privilege service accounts, encrypted transport and storage, scoped secrets, and separate environments.

  3. 03

    Derive user and session IDs from verified identity, apply tenant filters to knowledge and state, register narrow tools with current authorization, and require approval for consequential effects.

  4. 04

    Test forged IDs, cross-tenant retrieval, memory poisoning, prompt injection, stale permissions, concurrent sessions, tool denial, model failure, database outage, deletion, and key rotation.

  5. 05

    Review traces and evals with redaction, monitor storage growth and cost, canary versions, audit roles and tools, and support user export, correction, memory reset, and deletion.

Working standard

What good use looks like.

  • Derive session identity server-side.
  • Filter all knowledge by tenant.
  • Support memory reset and deletion.

Phidata is the former name; current code and documentation use Agno and AgentOS, and older tutorials may reference removed or deprecated APIs. Persistent sessions, memory, knowledge, traces, callable caches, teams, and tools create privacy and cross-user risks. Bind state to authenticated identities, authorize tools independently, use narrow roles and approvals, pin versions, redact logs, cap loops and cost, and test migrations and deletion.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.