Agno

Agno is the programming language for agentic software.

Build, run, and manage multi-agent systems at scale.

[Agno @AgnoAgi]

https://t.co/EUo3VD3zD7

[Agno @AgnoAgi]

https://t.co/Vh5O4Xz2sT

[Agno @AgnoAgi]

https://t.co/UQgkm0o5rb

[Parallel Web Systems @p0]

Get familiar with Agno using this simple web search agent cookbook: https://t.co/P0XI8RvlD0

[Parallel Web Systems @p0]

Parallel’s free web search MCP is now live in @AgnoAgi, the Python SDK for building production-grade agents: https://t.co/fPHZQsIwmp

[Agno @AgnoAgi]

https://t.co/dKF6N9KYMf

[Agno @AgnoAgi]

Cookbooks: https://t.co/TbPlTfLLd3
Docs: https://t.co/rmGHjUyEky
Agno on GitHub: https://t.co/FKaEP5Jvs9

@GoogleDeepMind

[Agno @AgnoAgi]

🚀 Agno v2.6.8 just shipped with native support for Managed Agents in the Gemini API.

Here's 3 ways to use them with Agno.

[Agno @AgnoAgi]

3. Use the AntigravityAgent class directly. A purpose-built BaseExternalAgent that exposes the full API: native sessions, streaming, and UI through AgentOS.

[Ashpreet Bedi @ashpreetbedi]

Image search using text classification

Image search has generally been a HARD problem but not every use-case needs google photos like infrastructure.

Some just need a quick and dirty image search and now that's possible in about 100 lines of code.

Link below

[Agno @AgnoAgi]

https://t.co/TUBflIOwFU

[Ashpreet Bedi @ashpreetbedi]

18 data labeling workloads powered by gemini-3.5-flash

Convert text, image, audio, video, PDFs to structured data.

40+ recipes covering classification, extraction, span labeling, preference pairs, bounding boxes, transcription, image embeddings + search, llm-as-judge, quality review.

It's a good model. Links below

[Yash @yashpsolanky]

Excited to release v2.6.8 with native support for Google Gemini’s Antigravity agent 🚀

There are multiple ways to make full use of Antigravity and its capabilities with Agno. More in the thread 🧵

[Yash @yashpsolanky]

Try out Gemini 3.5 Flash⚡️with your Agno Agent! Now available to use with both Gemini and GeminiInteractions

[Agno @AgnoAgi]

https://t.co/OF9zpBRfbt

[Ashpreet Bedi @ashpreetbedi]

A git-backed LLM wiki, built with @AgnoAgi

> Ingest web pages via @p0
> Compile into a markdown wiki (stored in a git repo)
> Every write auto-commits and pushes
> Query it using the same agent

Git gives you the history, storage, all the good stuff.

Code below, video next.

[Agno @AgnoAgi]

https://t.co/EWG5QNSqvy

[Agno @AgnoAgi]

Read the full story here: https://t.co/eSIUKGwgd4

[Agno @AgnoAgi]

An epidemiologist with no software engineering background built a production multi-agent healthcare analytics platform with Agno.

His early prototypes used raw API calls. Each step took 30 seconds. Fragile, slow, impossible to extend.

He evaluated LangChain, OpenAI Agents SDK, and others. Most added complexity or required vendor lock-in.

Agno clicked in a day. He validated his core hypothesis and now ships new features from idea to production in a single week.

The results:
→ Multi-step queries: under 60 seconds (was minutes)
→ Users get answers 10x faster than manual analysis
→ Scaled without adding engineering headcount
→ Architecture ready for PHI/PII use cases

"It had the main things I was looking for: simple implementation, a community to help onboard, and pragmatism, not the fluffy language"