Sean Falconer

About

👋 Hi, my name is Sean Falconer. I currently lead AI product and strategy at Confluent, where my team is responsible for Confluent Intelligence: a platform for building real-time, context-aware AI systems. That work spans streaming-native ML, event-driven agents (including the open-source Flink Agents project), and the Real-Time Context Engine which connects live data, stream processing, and low-latency serving so AI systems can reason over what’s happening now, not what happened yesterday. Earlier in my career, I was a hands-on engineer and researcher: competing in the ACM ICPC world programming finals, publishing academic research in AI and data-intensive systems, teaching computer science, and writing production code that has processed billions of events.

Badges

Tastemaker
Tastemaker
Gone streaking
Gone streaking

Forums

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8d ago

How do you take your product-ready startup from stage 0 to something everyone is talking about?

I have built plenty of amazing products, some of which are public on my GitHub (https://github.com/afrotechboss). But I always find it difficult to scale from there. I enjoy the building process, sometimes I even onboard a couple of first users, they love it, but after a while it dies off. I feel like I have a lot to learn. Any advice?

CNY 100,000 in bounties to give open-source AI agents better search

We ve just launched the AnySearch Open Source Bounty Program.

We re opening CNY 100,000 in bounties for individual developers to help bring AnySearch to more open-source AI agent projects. This round includes 30 selected projects. For most of them, integration will happen through a Pull Request, while the exact process depends on each project s architecture and contribution guidelines.

How do you tell whether low activation is caused by targeting or onboarding?

I recently ran my first small paid acquisition experiment for a workout-tracking mobile app.

The campaign targeted Android users in Poland and produced:

  • 27 installs

  • 3.47 PLN cost per install

  • 8,705 impressions

  • 4,481 accounts reached

  • 1.94 average frequency

The campaign was planned to run for seven days, but I stopped it after four because the number of daily installs appeared to be declining.

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