How to Find Agno (PhiData) AI Agent Developer Leads on GitHub

Who Are Agno Developers?

Agno (formerly PhiData) is a Python framework for building multi-agent AI systems. Developers using Agno define agents with tools, knowledge bases, memory, and team orchestration — then route them through workflows to handle complex tasks. Agno developers are production-focused AI engineers building on top of LLMs like Claude, GPT-4, and Gemini.

On GitHub, Agno developers leave strong intent signals: they star agno-agi/agno, open issues about Agent tools and Team orchestration, and build cookbook-style repos showing their agentic patterns. These signals identify engineers who are actively building production AI products — a high-value audience for AI infrastructure, LLM APIs, and developer tooling.

GitHub Signals That Identify Agno Developers

• Stars on agno-agi/agno — direct signal of evaluation or adoption
• Stars on agno-agi/agno-cookbook — developers building production agentic patterns
• Issues mentioning "Agent tools", "Team orchestration", "AgentStorage", or "Workflow" — active builders
• Keywords "from agno.agent import Agent", "agno.tools", "agno.models" in repos — confirmed Agno users
• Issues about Agno + specific LLMs (Anthropic, OpenAI, Gemini) — identifying their model preferences for targeting

Configuring GitLeads to Capture Agno Signals

// Agno repos to track
const agnoRepos = [
  'agno-agi/agno',          // Core framework
  'agno-agi/agno-cookbook', // Recipes and examples
];

// Keywords for Issues, PRs, Discussions
const agnoKeywords = [
  'from agno.agent import Agent',
  'agno.tools',
  'agno.models',
  'agno Team orchestration',
  'agno Knowledge base',
  'agno Workflow',
  'agno storage postgres',
];

// Enriched Agno developer lead
const agnoLead = {
  github_username: 'autonomous_builder',
  name: 'Sebastián Reyes',
  email: 'sebastian@agentstack.io',
  company: 'AgentStack',
  bio: 'Multi-agent AI | Python | LLMs in production',
  followers: 673,
  top_languages: ['Python', 'TypeScript'],
  signal: 'keyword_match',
  signal_context:
    'Opened issue on agno-agi/agno: "Team handoff fails when AgentStorage is PostgresStorage on concurrent requests"',
};

Agno Developer Segments and Their Buying Signals

• Production agent builders — engineers shipping multi-agent pipelines to end users. Signal: agno repos with Docker/K8s deployment configs and CI pipelines. Target: LLM API providers, GPU inference, observability tools.
• Enterprise AI integrators — teams using Agno to automate internal workflows. Signal: issues about "AgentStorage postgres", "Team enterprise patterns", "Agno async". Target: enterprise LLM access, security, compliance tools.
• Developer tool builders — engineers creating Agno-based products. Signal: repos with agno as a dependency alongside FastAPI or Streamlit. Target: AI developer platforms, agent hosting, API management.
• Framework evaluators — developers comparing Agno with CrewAI, AutoGen, or LangGraph. Signal: issues mentioning other frameworks + agno/phidata stars. Target: developer education, LLM benchmarking tools.

Routing Agno Leads Into Your Sales Stack

• HubSpot: tag "agno-agent-developer" with model preference (claude-agno, openai-agno, gemini-agno) for provider-targeted sequences
• Slack: alert #ai-agent-gtm when an engineer with 300+ followers stars agno-agi/agno
• Clay: enrich to detect company size and industry — Agno users in fintech, legal, and healthcare are highest-value enterprise targets
• Apollo: enroll Agno cookbook contributors in partnership sequences for AI infrastructure products
• Smartlead: cold outreach to Agno developers at companies with active hiring for "AI engineer" or "ML engineer" roles