AgentCon - Mukono

Overview

AgentCon - Mukono is a one-day in-person event that forms part of the AI Agents World Tour, a global series of conferences designed for developers, engineers, researchers, and builders who are creating the future with autonomous AI agents. The Mukono edition is described as in-person only, with a venue in Uganda that aligns with the Mukono region. Attendees can expect a focused deep-dive into AI agent design, deployment, and integration, with emphasis on practical code, hands-on demos, and real-world use cases. The event is positioned as a collaborative gathering for developers who want to explore cutting-edge techniques and tools in a live setting, with opportunities to connect with a global community of peers.

Agenda

The page highlights a robust agenda designed to equip attendees with both theory and practice. The program includes:

• Deep-dive talks from AI pioneers and industry leaders that explore current design patterns, architectures, and deployment strategies for AI agents.
• Technical workshops focused on building, deploying, and scaling AI agents in real-world environments.
• Live demonstrations of powerful open-source frameworks and tools that support agent development and orchestration.
• Networking opportunities with a global community of developers and innovators to share experiences and collaborate on projects.
• Complimentary lunch

A schedule is presented that designates a full-day window from morning to afternoon, with a specific local time frame and a time zone reference (East Africa Time, EAT). The event appears to be structured to allow attendees to plan sessions that align with their interests, whether they focus on research, product development, or hands-on experimentation.

Venue and attendance

The event location is Uganda Christian University Mukono, located on Bishop Tucker Road in Mukono, Uganda. The page identifies the event as in-person only, signaling a face-to-face format that supports live talks, demonstrations, and in-person networking. The registration link is available on the page, indicating a formal process to secure attendance.

Format and content

AgentCon - Mukono emphasizes an experiential format that favors practical knowledge and real code. The agenda mentions deep-dive talks, technical workshops, and live demos, suggesting a blend of theoretical learning and hands-on sessions. The page also highlights the role of speakers and sessions, with a later, dynamic component for speaker details that appears to be loaded from an external source. Attendees should anticipate a compact, information-dense program that prioritizes actionable insights and tangible outcomes, rather than purely theoretical discussions. The event is part of a larger world tour, which may offer continuity with other chapters and opportunities to engage with a global AI community.

FAQ and who should attend

The description signals that the event is targeted toward developers and engineers working on AI agents, as well as researchers and creators contributing to AI-enabled tooling and platforms. It is suitable for individuals interested in practical deployment, developer tooling, and hands-on demonstrations of AI agent capabilities. Networking and community-building are also emphasized as core components of the experience.

Speakers and program details

While the page points to an external API that hosts speaker data, specific speaker names and bios may be loaded from that source during the event planning or on-site. The presence of a dedicated speakers section implies a curated lineup and the potential for sessions covering a range of topics within AI agents. The event is organized by Global AI Community, with collaboration from the Mukono chapter, and is associated with supporting organizations indicated on the page.

What you gain

Attendees can expect practical knowledge that translates into real-world coding and deployment practices for AI agents, networking with peers, exposure to open-source tools, and opportunities to see live demonstrations. The event aims to accelerate the learning curve for developers building autonomous or semi-autonomous AI systems and to foster collaboration within a global AI developer community.