Cover Image for How advanced tool calling transforms agentic use cases: A conversation with Moonshot AI
Cover Image for How advanced tool calling transforms agentic use cases: A conversation with Moonshot AI
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How advanced tool calling transforms agentic use cases: A conversation with Moonshot AI

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​Join Feihu Tang from the Moonshot AI team and Zain Hasan from Together AI for a technical session on how the Moonshot team post-trained Kimi K2 Thinking for agentic tool calling interleaved with its reasoning traces — and how to actually run it on Together.

​Most models “think” and then make one tool call, then think again. This forces you to build complex orchestration layers with many API calls for each task. For real-world tasks like deep research, multi-step planning, or anything requiring multiple sequential tool calls, this architecture becomes brittle fast.

​Kimi K2 Thinking takes a different approach: it can make 300 tool calls while it’s thinking, significantly simplifying complex tasks. This session will focus on how this agentic setup works in practice, how it differs from earlier open-source releases from the likes of DeepSeek and Qwen, and how to harness it to power your own agentic applications on Together.

​This is a learning-first webinar — ideal for folks building and scaling LLM-powered apps, tools, and agents who need to understand what’s different about this architecture and how to use it in production.

​What we’ll cover

  • ​Why tool calling is the bottleneck for agentic apps: the limitations of single-turn workflows and why they force you into complex orchestration patterns that don’t scale.

  • ​Why this model is special: what “tool calling inside the thinking trace” actually means, and why K2 doing 200–300 tool calls in one run is so powerful.

  • ​What Moonshot learned from training Kimi K2 Thinking for heavy tool use: high-level lessons from their agentic post-training work and how it shaped K2’s behavior.

  • ​Agentic workflows in one call: examples of tasks that used to need multi-step orchestration (research, planning, tool fan-out) and how K2 can keep that inside the model loop.

  • ​Live demo on Together AI: a “before/after” comparison showing a regular thinking model vs. Kimi K2 Thinking with interleaved tool calling on the same problem, and how to run it in production on Together.

​Register to join the webinar live, ask questions, and receive a recording of the talk.

​⚠️ Note: Only company (non-Gmail, etc.) email addresses will be accepted. Please provide your valid corporate email upon registration.

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