AutoBE harness lifts Qwen3.6-27B from 9.91% to 100%

Hot take: the thesis is strong and memorable, but the draft will land better if it is tightened around methodology and scope so it does not read like a leap from coding benchmarks to financial or clinical reliability.

• –The best part is the framing: “schema as a harness” is concrete, testable, and easier to believe than generic “better prompting.”
• –The investment-memo example is useful as an analogy, but you should be explicit that backtesting the schema is not the same thing as validating real-world decision quality.
• –The 9.91% to 100% jump is the hook; keep the measurement setup front and center so readers understand what exactly improved and under what constraints.
• –The draft’s strongest audience is AI builders, not general meetup attendees, so technical specificity is an asset rather than a liability.
• –Consider adding one sentence that distinguishes “CoT compliance” from “reasoning quality,” otherwise readers may conflate structured completion with better judgment.
• –The “no compiler” angle is a good extension of the earlier post, but it will be more convincing if you name the fallback validator in each target domain, not just the abstraction.