한국어EN

Part ReviewPart 6 · What Comes NextDAY 56–60

Part 6 Review

From the AGI debate to the order of learning · short, with analogies · DAY 56-60

Made by AIThis part review was written by AI (Claude) from that part's lessons and records, and published after automated checks. The owner doesn't read every item.How it's made

Part 6 spent five days on what happens next. It started with the AGI debate and ended on what you should actually get ready for.

No quizzes and no experiments here. It's a read-and-move-on piece. If a day feels fuzzy, jump straight to that day's lesson.

DAY 56 · The AGI debate

Whether AGI is here is a fight about the bar

AGI is the name for an AI that's broadly as good as a person. But nobody has settled how much it has to do to earn that name. Set the bar low and today's AI already passes; set it high and it falls short. Same AI, different answer. So when someone says 'AGI is here,' there's one thing to ask first — what's your bar?

DAY 57 · AI and jobs

What disappears isn't the job, it's pieces

One job is made of several pieces: gather, make, choose, own it. AI grabbed the first two pieces fast, and the pieces where you decide what's right and answer for it stay with people. So whole jobs don't vanish. The center of gravity slides toward the back.

DAY 58 · AI safety

Safety isn't a personality, it's guards bolted on

AI safety isn't magic that makes a model good. It's guards you add on top of the model, one at a time. There are three of them — refusing, asking before acting, and checking afterward. Adding them really does change behavior, but it isn't free. It takes more computing, and fine requests get turned down more often.

DAY 59 · Robots and AI

AI went into the robot's first three pieces

Robots look smart these days, but not because their bodies got better. The same kind of AI we use got plugged into the brain spot. AI went into the eyes, the ears for instructions and the judging, while the pieces that move hands and legs are still mechanical engineering. So the truly hard part isn't the thinking, it's the body. Balance has to be caught hundreds to thousands of times a second.

DAY 60 · The order of learning

What you need isn't new knowledge, it's an order

Across all 60 days one answer kept coming back — ask, check, try it yourself, then explain it in your own words. Tools change every few months, but the way you learn doesn't. That's why the order you pick up today still works next year. Getting stuck isn't failure, it's one step of the order. Asking again about the stuck part is the next step.

Part 6 in one line

Squeeze five days into one line and it's this — questions about what comes next are mostly questions about us. Where to set the bar, which pieces to hand over, what guards to put on.

That's the end of the 60-day course. From next week on, one lesson a week opens, built from the records added that week.

Learn more

  1. Computing Machinery and Intelligence (Turing, 1950) — the original paper that proposed judging 'can a machine think' by the answers it givesacademic.oup.com/mind/article/LIX/236/433/986238
  2. On the Measure of Intelligence (Chollet, 2019) — the proposal to measure intelligence as how fast you pick up new skills, not how much you knowarxiv.org/abs/1911.01547
  3. ARC-AGI-3 launch (ARC Prize, 2026) — a test where you work out new rules with no instructions. At launch: people 100% vs AI 0.51%arcprize.org/blog/arc-agi-3-launch
  4. Gemini 3 Deep Think (Google, 2026) — the company-reported 84.6% on a puzzle test where people average 60%blog.google/innovation-and-ai/models-and-research/g…
  5. GDPval (OpenAI, 2025) — scoring AI on real work products from 44 occupations across nine fieldsopenai.com/index/gdpval
  6. Remote Labor Index (Scale AI & CAIS, 2025) — the evaluation where the best AI finished just 2.5% of whole real jobsarxiv.org/abs/2510.26787
  7. Canaries in the Coal Mine (Stanford Digital Economy Lab, 2025) — an observation about job counts for 22-25 year olds; the authors stress it is not a causedigitaleconomy.stanford.edu/publication/canaries-in…
  8. Constitutional AI (Anthropic, 2022) — using a written set of principles as the training signal instead of labelling by handarxiv.org/abs/2212.08073
  9. Constitutional Classifiers (Anthropic, 2025) — the source of the 86% to 4.4% numbers and the 23.7% extra computinganthropic.com/news/constitutional-classifiers
  10. Petri (Anthropic, 2025) — an open tool that has AI audit AI automaticallyanthropic.com/research/petri-open-source-auditing
  11. RT-2 (Google DeepMind, 2023) — wiring knowledge learned from internet images and text straight into robot arm controlarxiv.org/abs/2307.15818
  12. Gemini Robotics (Google DeepMind, 2025) — a model that connects a large language-understanding AI to a robot bodydeepmind.google/discover/blog/gemini-robotics-bring…
  13. Helix 02 (Figure, 2026) — the explanation of running circuits at different speeds: balance 1,000 times a second, joints 200figure.ai/news/helix-02
  14. ARC Prize 2025 results analysis (ARC Prize, 2025) — published results from a puzzle contest people find easy and AI does notarcprize.org/blog/arc-prize-2025-results-analysis
  15. Will we run out of data? (Epoch AI, 2024) — working out in numbers when AI might run out of text to learn fromepoch.ai/blog/will-we-run-out-of-data-limits-of-llm…