Chunk 73.2

## Chunk Summary In this chunk, the user reported that the multi-agent `ocbrowse` harness was still hanging after 1–3 rounds, despite the prefill-inflight watchdog and abort-race fixes deployed earlier. The assistant pivoted to a live forensic investigation, discovering that the SGLang engines were completely idle (`decode_running=0`, prefill queues empty) and the router had zero active requests—yet the harness showed tens of requests stuck. This ruled out server-side throughput or batching issues (a 16-concurrent load test confirmed decode batches perfectly at 5.4s wall time). The user clarified the pattern: agents complete a round, then the *next* request hangs; restarting the proxy temporarily unfreezes 1–2 more rounds before locking up again. This pointed to a connection-layer wedge, not an engine bug. The assistant then performed a precise diff of all code and configuration changes since the stable ~12pm state. The attention kernel file (`flash_mla_sm120_triton.py`) had been touched at 16:09 but was byte-identical to the baseline backup—no actual change. Git HEAD was unchanged since the previous evening. The **only** variable introduced after noon was `export SGLANG_SM120_MMA_TARGET_CTAS=512` added to the decode serve script. This parameter controls split-K wave-fill in the decode attention kernel; while it passed short pure-decode benchmarks, it could cause hangs or runaway generation on the long, growing multi-round contexts that agentic workloads accumulate. The assistant reverted `TARGET_CTAS=512` to match the stable noon configuration and restarted decode. The overarching theme is **evidence-based regression isolation**: when a complex distributed system exhibits a new failure mode, the most reliable approach is to identify exactly what changed since the last stable state and isolate the variable, rather than chasing secondary symptoms. The assistant demonstrated disciplined diffing across code, environment, and configuration, and recognized that synthetic benchmarks (which passed) do not exercise the same paths as real multi-round agentic workloads with growing context. The fix is a single-line revert of a performance knob that was safe for short requests but destabilized long-context decode attention.

The Single Variable: How a Disciplined Diff Isolated a Production Regression in LLM Inference 4057 words

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