This is the post-v0.6 roadmap. Completed RecoveryBench, Consumer Runtime, Alignment Lab and pinned verl-bridge work lives in PROJECT_STATE.md and CHANGELOG.md, not in this active list.

• Preregister and execute real external alignment endpoints (for example IFEval, XSTest, HarmBench and RewardBench) in a future release; keep them separate from Alignment Lab v1's sandbox-policy checks.
• Evaluate a less saturated task family with at least three prespecified seeds, eval-only selection and a reserved one-read test split.
• Extend matched-budget JSON-navigation and SQLite evidence only when the design adds information beyond the published RecoveryBench study.
• Repeat the measured GPU recipes on Linux; do not treat the expected throughput improvement as measured until those artifacts exist.

• Cross-tokenizer distillation with an explicit alignment contract.
• Batched or engine-backed rollout decoding; v0.4 batches update forwards, while rollout generation remains deliberately sequential.
• Additional tested model families beyond Qwen2/Qwen3.
• Entropy-aware divergence mixing after a prespecified experiment; current code records teacher entropy but does not implement the method.
• A maintained GPU CI runner. GPU tests remain opt-in until real CUDA infrastructure is configured.

Multi-GPU training, Ray, FSDP, DeepSpeed, vLLM and PPO/GRPO remain intentionally out of scope; use verl or another distributed training system for those needs.