kanungle

Developer Relations at Qdrant 🚀

[Adam / AJ Chan @itsajchan]

What changes when vector search means 20B+ vectors, trillions of messages, and fresh results in seconds?

At Vector Space Day SF, HubSpot and Slack will share hard-won production lessons from search infrastructure at scale.

Register: https://t.co/nAsgv3kajA

[kanungle @kanungle]

No plans this weekend? There's still time to compete in our virtual hackathon! Submission deadline is Monday, $10k up for grabs

https://t.co/DsZXTqMvJH

[Adam / AJ Chan @itsajchan]

𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗰𝗮𝗻𝗻𝗼𝘁 𝘀𝘁𝗼𝗽 𝗮𝘁 "𝗺𝗼𝘀𝘁 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗿𝗲𝘀𝘂𝗹𝘁."

At Vector Space Day SF, @Adobe and @neo4j will show how governed retrieval, GraphRAG, and context graphs make agents faster, safer, and more explainable.

Register: https://t.co/VgxELoVEH4

[kanungle @kanungle]

Join us in Berlin! Going to be a good, open-format meetup. There will be great panel discussions and follow-up roundtables with attendees. Come, bring your ears, and your ideas!

[Qdrant @qdrant_engine]

We’re hosting Vector Space Meetup: Retrieval in the Age of Agents on June 11.

RAG is the architectural foundation of production AI, and retrieval has fundamentally changed over time. Agents don’t just retrieve anymore - they decide when to search, what to search for, and whether results are good enough to act on.

We’re gathering builders shaping this shift: @cognee_, @n8n_io, @deepset_ai, and @llama_index for a panel driven entirely by YOUR questions.

You’ll also hear from Qdrant’s Co-Founder & CTO, @generall931, who will join for open discussions and networking with attendees.

Join us! Register (approval required): https://t.co/BnEdTYQBkr

[Adam / AJ Chan @itsajchan]

Agent demos are easy. Agents that remember, adapt, and improve are the real work.

At Vector Space Day SF, @mem0ai's @taranjeetio and @GoogleDeepMind's @DynamicWebPaige will get into memory, state, and dynamic agent tooling.

Register: https://t.co/nAsgv3kajA

[kanungle @kanungle]

Going live with our webinar on #TurboQuant in less than 15 minutes!

https://t.co/piOLCWy3TD

[Qdrant @qdrant_engine]

Meet a few of our speakers for Vector Space Day on June 11 at The Midway.

They will cover:
- Taranjeet Singh from @mem0 Continual Learning Starts with Memory
- Paige Bailey from @GoogleDeepMind Literal Skill Issue: Are SKILLS.md Holding Your Agents Back?
- @HubSpot Scaling to Billions
- @neo4j Free Your Agent's Mind...with Context Graphs
- @llama_index The Document Harness: What Your AI Misses in the 90%
- @twelve_labs Beyond the Single API Call: Agentic Video Intelligence

And more. Join us for a full day of single-track technical content covering search and AI retrieval, agents and memory, and edge and robotics AI.

Get your ticket: https://t.co/a190Cwv5EF

[kanungle @kanungle]

Search. Agents. Robotics.

Vector Space Day's Early Bird pricing ends on Monday. DM me for a coupon code 😉

https://t.co/Ru6PqDoOp6

[James Le @le_james94]

Stoked to speak at @qdrant_engine Vector Space Day 2026 in San Francisco next month 🛰️

I will show some new model capabilities from @twelve_labs and something new for agentic developers working with video.

Register: https://t.co/AVG3YCE5pI

@kanungle @ptdamiba

[Qdrant @qdrant_engine]

The call for proposals for Vector Space Day 2026 in San Francisco closes May 6. You’re almost out of time!

If you're building something worth talking about in retrieval, agents, memory, or edge AI, we want to hear from you.

300+ engineers will be gathered at The Midway on June 11. This is the audience that will actually understand what you built, ask hard questions, and remember your talk.

Submit your proposal before May 6: https://t.co/kmGWBqO7bO

Event details: https://t.co/a190CwvDud

[kanungle @kanungle]

really hoping @AnthropicAI figures out this Claude token bleed situation. Hitting limits so fast these days

[kanungle @kanungle]

We're hosting a live session on Tuesday with @ptdamiba on Qdrant's new Agent Skills!

We'd love to hear from you and share thoughts/ideas on these new Skills.

Thierry was lead design for these and can share a lot of our learnings.

Join us on Discord on Tuesday!

https://t.co/aD8Ov3lKem

[kanungle @kanungle]

Agent Skills for Qdrant are now available, as well as a new CLI for Qdrant Cloud 🚀

These skills were built by Qdrant's Senior DevRel @ptdamiba and CTO @generall931, along with many Solution Architects. Leverage their knowledge with your @qdrant_engine workflows today.

Download: https://t.co/uYYGsCUfZS

[kanungle @kanungle]

"#pgvector doesn't scale" is what most vector database companies say to postgres users. But there's more to it...

#Postgres is great, and there are plenty of reasons to use it. However, through a careful community analysis of 110+ posts, we've distilled down to 6 conditions that must hold true for pgvector to make sense for your search needs.

Read more: https://t.co/Rv7OND5ENL

[Qdrant @qdrant_engine]

⏳ Just a few days left!

🇩🇪 Join us in Munich for “Unconference: Context Engineering with Open-Source” - an evening of open discussions on building better context layers for AI systems.

Instead of traditional talks, we’ll dive into interactive conversations around:
• Retrieval and vector search
• Memory systems for AI agents
• Designing robust context layers
• Building production-grade AI with open-source tools

Explore how tools like @deepset_ai, @qdrant_engine, and @cognee_ help engineers design better context pipelines for real-world AI applications.

📍 smartvillage Bogenhausen, Munich

🔗 https://t.co/vzhUJfVjdA

See you there! 👋

[Thierry Damiba @ptdamiba]

Tomorrow at @NVIDIAGTC I'm at the @Vultr stage to talk about edge to cloud video anomaly detection with @qdrant_engine Edge, @twelve_labs Marengo 3.0, and @nvidia Metropolis.

Traditional video classifiers need labeled examples of every anomaly you want to catch. That breaks in the real world. So I took a different approach..

[Thierry Damiba @ptdamiba]

https://t.co/DvTOkRphNH

[kanungle @kanungle]

@SouptikSen08 Could you tell me more about the issue you ran into?

[Qdrant @qdrant_engine]

Most vector databases treat retrieval as a single operation. That's the wrong abstraction.

Storing embeddings and returning nearest neighbors is a solved problem. The hard problem is what happens next. We solve it through composable vector search, built in Rust.

Today, led by AVP, with Bosch Ventures, Unusual Ventures, Spark Capital, and 42CAP, we're announcing our $50M Series B to accelerate it.

Learn more about Qdrant’s composable vector search and our latest funding round here: https://t.co/oUfi99APjt