I'm considering trying a different brushing method.

First, let's talk about the core data of the three plans (based on 40U per round of airdrop):

• Old plan (16 basic + 2 extra per day = 18 points × 15 days): Total 270 points → 5 rounds of airdrop, cost about 52.5U. Net profit = 5×40 − 52.5 = 147.5U.

• My new plan (divided into two segments: 18 points per day for the first 5 days, 17 points per day for the next 10 days): Total 260 points → 5 rounds of airdrop, cost 34.5U. Net profit = 5×40 − 34.5 = 165.5U.

• Aggressive plan recommended by a certain blogger (19 points for the first 5 days, 18 points for the next 10 days): Total 275 points → 6 rounds of airdrop, cost 69U. Net profit = 6×40 − 69 = 171U.

From a purely numerical perspective, the blogger's aggressive plan has the highest gross profit, but the net profit is only 5.5U more than my new plan; compared to the old plan, the new plan saves 31U in costs and yields 18U more in profit. This means that the new plan has an advantage in the efficiency of 'cost input → net return'.

Now, let's discuss some finer trade-offs (why I lean towards the new plan):

1. Diminishing marginal utility is evident: Raising the points from 260 to 275 incurs a cost increase greater than the marginal benefit of the additional round of airdrop (only 5.5U more in net profit), making it less cost-effective.

2. Capital occupation/risk: The blogger's plan requires a larger expenditure (69U), which means higher short-term capital occupation and error costs; the new plan is easier and has a larger margin for error.

3. The implicit value of high points: Indeed, high points can increase the probability of winning large rewards—this is an important selling point of the blogger's strategy. If you particularly value the possibility of 'taking a chance for a big prize,' the aggressive route is more logical.

4. Stability vs. luck: The new plan leans towards 'safe and economical,' while the old plan and the blogger's plan lean towards conservative and aggressive respectively. According to my risk preference (pursuing cost-effectiveness and not wanting to be dragged down by a single mistake), I prefer the new plan. #alpha