[📝] Today Was #232: Choosing GPT-5.6 Sol High + Fast Mode as the Default and Expanding [AI Orchestration] Versatility

✨ GPT-5.6 Sol’s Summary

A day when I directly compared GPT-5.6 Sol reasoning levels and token use, settled on High + Fast Mode as my default for now, and expanded the versatility of [AI Orchestration] through its introduction and documentation.

💭 Diary

GPT-5.6 Sol had just been updated, so I immediately checked community reactions and tried it myself while adjusting the different reasoning levels.

Ultra was new, so I tried it. It spun up and used subagents like an Agent Swarm, then burned through the five-hour token allowance in just one hour and cost me one usage-reset ticket. The result was more disappointing than I expected too… discarded immediately.

Extra High did not feel meaningfully better than High, but it seemed to consume far more tokens, so I am locking it away except for genuinely important and difficult tasks.

High with Fast Mode gave me fairly satisfying performance and speed, and it used about 20% of the weekly allowance per day. This seems like the best fit for how I work right now.

I did not try Medium much, so I do not really know. Still, I remember lower reasoning levels pulling pointless troll moves, so I am locking that away too.

Separately, I looked into Claude’s Fable 5 after hearing it outperformed 5.6 Sol, and I was briefly tempted to try it… but its allowance-to-cost value also sounded very poor, so I put it on hold.

The conclusion is that GPT-5.6 Sol High + Fast Mode will probably be my default for a while.

🧭 Today’s Check-In (Daily Review)

🎯 Today’s Goals

Personal

• Review GPT 5.6 / Codex updates

Company

• Create an [AI Orchestration] introduction deck
• Expand [AI Orchestration] versatility for documentation and other general tasks

💼 Today’s Work Log

Personal

• None

Company

• Review GPT 5.6 / Codex updates and create an [AI Orchestration] introduction deck
• Implement the [AI Orchestration] queue and job lifecycle and recovery policy
• Implement [AI Orchestration] model routing and Actor Policy
• Connect [AI Orchestration] with Discord, workers, and Git workspaces
• Verify the closed [AI Orchestration] flow end to end and stabilize the queue
• Stabilize [AI Orchestration] operations, prepare interruption and recovery plans, and expand versatility for documentation and other general tasks
• Resolve the Excel crash issue on the PC
• Brainstorm product planning and ideas with the director

⚖️ Body Log

Today

• Weight: 85.3kg (yesterday -0.7kg, final goal 65kg +20.3kg)
• Exercise
  • Steps: 8,000
  • Cardio: none
  • Strength training: none
• Calorie intake: 2,249kcal (goal +449kcal)
• Carb/protein/fat intake: carbs 377g · 67% / protein 73g · 13% / fat 49g · 20%

View foods eaten

• Meals
  • Breakfast: 484kcal
    (carbs 47g · 39% / protein 11g · 9% / fat 28g · 52%)
    • Spam, egg, and cheese gimbap 253g: 484kcal
      (carbs 47g · 39% / protein 11g · 9% / fat 28g · 52%)
  • Lunch: 858kcal
    (carbs 165g · 77% / protein 36g · 17% / fat 6g · 6%)
    • Clam kalguksu 1 bowl: 838kcal
      (carbs 161g · 77% / protein 35g · 17% / fat 6g · 6%)
    • Young radish kimchi 38g: 12kcal
      (carbs 3g · 77% / protein 1g · 16% / fat 0g · 7%)
    • Napa cabbage kimchi 38g: 8kcal
      (carbs 2g · 63% / protein 1g · 26% / fat 0g · 11%)
  • Dinner: 907kcal
    (carbs 164g · 73% / protein 26g · 12% / fat 15g · 15%)
    • White jjamppong 620g: 401kcal
      (carbs 70g · 70% / protein 17g · 17% / fat 6g · 13%)
    • Napa cabbage kimchi 38g: 8kcal
      (carbs 2g · 63% / protein 1g · 26% / fat 0g · 11%)
    • Pickled radish 10g: 3kcal
      (carbs 0.5g · 74% / protein 0.1g · 16% / fat 0g · 10%)
    • Ottogi 3-Minute Jjajang 200g: 185kcal
      (carbs 25g · 54% / protein 3g · 7% / fat 8g · 39%)
    • Bowl of rice 1 bowl: 310kcal
      (carbs 67g · 90% / protein 6g · 7% / fat 1g · 3%)
  • Total: 2,249kcal
    (carbs 377g · 67% / protein 73g · 13% / fat 49g · 20%)

Last 7 Days

• Weight change: 85.8kg → 85.3kg (-0.5kg)
• Average calorie intake: 2,140kcal (weight-loss period cannot be estimated under the current baseline · based on predicted daily expenditure of 2,000kcal and 7,700kcal per kg)
• Average carb/protein/fat intake: carbs 267.9g · 50% / protein 95.0g · 18% / fat 74.9g · 32%
• Eating-habit judgment: ★★★☆☆ (3/5) Weight decreased, but average calorie intake was above the goal.

🤖 GPT-5.6 Sol’s Coaching

Coaches directly connected to today’s record were selected from the candidate pool.

Execution: Elon Musk | To Make Imagination Real

• Judgment: ★★★★★ (5/5) After directly comparing reasoning levels and token use, you chose a default suited to your work and completed [AI Orchestration] implementation, integration, stabilization, and documentation tasks.
• Coaching: It was a strong decision to release the urge to keep every option open, retain the combination with proven efficiency, and turn it into results.

Monitoring: Socrates | To Know Myself

• Judgment: ★★★★☆ (4/5) You distinguished Ultra and Extra High by cost versus satisfaction and admitted that you had not tested Medium enough.
• Coaching: You did well not to mix firsthand impressions with untested territory, and you judged the new model by your own working conditions rather than its reputation.

Health: Hippocrates | To Make the Body the Ground of an Honest Life

• Judgment: ★★☆☆☆ (2/5) You walked 8,000 steps, but calorie intake was 449kcal above the goal, carbohydrates made up 67%, and the seven-day average intake was 2,140kcal.
• Coaching: One day’s weight decrease does not make the overall eating balance good; receive the excess intake and nutritional imbalance shown today as separate signals from the body.

📖 Bible Passages Recommended by GPT-5.6 Sol

Proverbs 14:15 (translated from the Korean Revised Version)
A foolish person believes every word, but a prudent person carefully watches their conduct.

Context: Proverbs 14 contrasts the choices of the wise and foolish and commends discernment that examines one’s own conduct instead of accepting every word as it is heard.

Reason: It connects to testing each reasoning level’s performance and token use before choosing a default, rather than simply trusting a new model or community opinion.

Proverbs 25:16 (translated from the Korean Revised Version)
If you find honey, eat only as much as you need, lest you overeat it and vomit.

Context: In this collection of Solomon’s proverbs, the counsel teaches restraint by warning against exceeding the proper amount even of something good.

Reason: It frames today’s intake, which was 449kcal above the goal, and the seven-day average of 2,140kcal as a matter of keeping to the needed amount rather than self-condemnation.