> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-docs-whatsapp-interface-documentation.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Building Agents

> Start simple: a model, tools, and instructions.

To build effective agents, start simple: a model, tools, and instructions. Once that works, layer in more functionality as needed. For example, here's the simplest possible agent with access to `HackerNews`:

```python hackernews_agent.py theme={null}
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.hackernews import HackerNewsTools

agent = Agent(
    model=Claude(id="claude-sonnet-4-5"),
    tools=[HackerNewsTools()],
    instructions="Write a report on the topic. Output only the report.",
    markdown=True,
)
agent.print_response("Trending startups and products.", stream=True)
```

## Run your Agent

Use `Agent.print_response()` for development. It prints the response in a readable format in your terminal.

For production, use `Agent.run()` or `Agent.arun()`:

```python theme={null}
from typing import Iterator
from agno.agent import Agent, RunOutputEvent, RunEvent
from agno.models.anthropic import Claude
from agno.tools.hackernews import HackerNewsTools

agent = Agent(
    model=Claude(id="claude-sonnet-4-5"),
    tools=[HackerNewsTools()],
    instructions="Write a report on the topic. Output only the report.",
    markdown=True,
)

# Stream the response
stream: Iterator[RunOutputEvent] = agent.run("Trending products", stream=True)
for chunk in stream:
    if chunk.event == RunEvent.run_content:
        print(chunk.content)
```

## Dynamic Agent Configuration

In Agno, callable factories are a first-class pattern for dynamic runtime configuration. For agents, callables are used to build tools and knowledge from live run context instead of fixed configuration.

Teams can dynamically compose members, tools, and knowledge per user or task with [callable factories](/teams/building-teams#callable-factories). Tools expose only what is relevant at that moment to keep execution focused. In case of knowledge, callables route retrieval to the best source per request for more precise, up-to-date responses.

## Next Steps

After getting familiar with the basics, add functionality as needed:

| Task                               | Guide                                        |
| ---------------------------------- | -------------------------------------------- |
| Run agents                         | [Running agents](/agents/running-agents)     |
| Debug agents                       | [Debugging agents](/agents/debugging-agents) |
| Manage sessions                    | [Agent sessions](/sessions/overview)         |
| Handle input/output                | [Input and output](/input-output/overview)   |
| Add tools                          | [Tools](/tools/overview)                     |
| Manage context                     | [Context engineering](/context/overview)     |
| Add knowledge                      | [Knowledge](/knowledge/overview)             |
| Handle images, audio, video, files | [Multimodal](/multimodal/overview)           |
| Add guardrails                     | [Guardrails](/guardrails/overview)           |
| Cache responses during development | [Response caching](/models/cache-response)   |