Tutorials Port Kimi K2 Agents to K3: The Reasoning-History Trap
kimi-k3 is not a drop-in swap. Map the params right and dodge the trap that breaks tool loops.
How-to content for builders, indie hackers, and AI engineers. Less theory, more shipped code.
Tutorials kimi-k3 is not a drop-in swap. Map the params right and dodge the trap that breaks tool loops.
Tutorials Point the OpenAI SDK at Meta's agent model, add tools, let it self-manage a 1M-token context.
Tutorials Use reasoning.context to reuse GPT-5.6's chain of thought across turns and cut redundant tokens.
Machine Learning Run the first 27B-class model on a phone: MLX, llama.cpp, tool calls, and the memory math.
Tutorials Reproduce GPT-Live's full-duplex voice and background delegation using the GA Realtime API.
Machine Learning Run Google's TabFM on real tabular data. No tuning, no feature engineering, one forward pass.
Tutorials Structure prompts, set prompt_cache_retention, and read cached_tokens to slash GPT-5.6 input costs.
Tutorials Use GPT-5.6's Responses API so the model writes JavaScript to run your tools in one call.
Tutorials Use Grok 4.5's server-side X Search on the xAI API to build a cited, real-time trend agent.
Tutorials Build an agentic Grok 4.5 tool loop in Python: route reasoning_effort and cache to slash cost.
Tutorials Use Anthropic's compact-2026-01-12 beta so long agentic loops survive past the 200K context window.
Tutorials Give Claude agents a token countdown so long agentic loops finish gracefully instead of burning your bill.