The fastest path is narrow, not comprehensive
Teams lose time when they treat fine-tuning as an exploration playground instead of a constrained production path. The 48-hour route works when the task is well scoped, evaluation is ruthless, and deployment constraints are part of the plan from the first hour.
The most important early choice is not which adapter method sounds exciting. It is which business behavior you are actually trying to improve.
What the working path looked like
The strongest sequence was: pick one narrow task, quantize conservatively, run LoRA for one disciplined objective, evaluate on real prompts, and only then optimize inference cost. That order prevents teams from polishing an unclear target.
Where teams got stuck was excessive experimentation before establishing a trustworthy evaluation set.
Production readiness is mostly about operational honesty
A model is not production ready because it generated one impressive output. It is ready when latency, fallback behavior, monitoring, and rerun patterns have all been considered.
Lab should cover open-source guides in this way because it keeps practical control attached to deployment reality.
