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Do This Before Fable 5 Goes API Only (Extract Its Intelligence to Opus 4.8) — Transcript

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0:00Right now, sitting inside your Claude
0:02plan is the single smartest model money
0:04can rent. Tomorrow, it walks out the
0:06door. Fable 5 goes paper token, and if
0:10you are on a normal plan, that is the
0:12same word as gone. So, here is the move
0:14almost nobody is going to make today.
0:16You cannot keep the model.
0:18You can keep the way it thinks. A way of
0:20thinking can be written down, pulled
0:22out, and run on a cheaper model that is
0:24not going anywhere. That right there is
0:27the whole video. Look at the list going
0:29around. Build a website, ship a few demo
0:32apps, generate a month of content. Every
0:35one of those is a way to burn your last
0:37frontier hours, and every one of them
0:39flunks the only test that should rank
0:40your day. One question sorts everything
0:43you could do today. Can a cheaper model
0:45redo this tomorrow? If the answer is
0:47yes, skip it. Opus, the everyday Claude
0:50that stays in your plan, rebuilds a demo
0:52app next week for nothing. Run your own
0:54list through it right now. A landing
0:56page? A cheaper model builds that next
0:58Tuesday. Skip. A batch of social posts?
1:02Same answer. Skip. But a standard that
1:04encodes how your business makes
1:05decisions? No cheaper model can author
1:08that. That one you keep. The filter is
1:10that blunt and that useful. Spending the
1:12final hours of a frontier model on work
1:15a mid-tier model handles is like hiring
1:17a surgeon to take your blood pressure.
1:19It gets done. Nothing is wrong with the
1:21result. It is just a spectacular waste
1:23of the one thing you are about to lose
1:25for good. What a cheaper model cannot
1:27redo tomorrow is the good stuff. A
1:29standard written down, a road map
1:32already reason through, a vault of
1:34knowledge already distilled, a skill
1:36that fires on its own. Those keep their
1:38full value long after the model behind
1:40them is gone. Five moves do the
1:41extraction, and I am handing you every
1:43prompt ready to paste. If you remember
1:46one thing, remember the order. Move five
1:48first because it runs itself. Start with
1:51why today specifically is different.
1:54Here is the arithmetic straight off
1:56Anthropic's own rate card. Fable runs
1:58about $10 per million tokens in 50 out.
2:01Opus 4.8, the model that stays in your
2:04plan, is half of that, near 5 and 25.
2:08Sonnet is cheaper still on intro pricing
2:10near 2 and 10 through the end of August.
2:12Today, inside your plan, Fable is flat
2:15rate. Tomorrow, every single call it
2:17makes has a meter running on it, and
2:19that meter is unkind to Fable.
2:22It eats your weekly limit roughly twice
2:24as fast as Opus, and only half of that
2:26weekly limit applies to it in the first
2:27place. So, you do not get 10 swings at
2:29this today, you get two, maybe three.
2:32Spend them on the jobs with the most
2:34value locked up inside. This is the part
2:36people miss while they argue about
2:37whether the model is worth keeping. The
2:39argument is beside the point. Opus 4.8
2:42is not going anywhere. It is genuinely
2:44great, and starting tomorrow, it is what
2:46you actually run on. Fable is only here
2:49to leave it instructions. So, sort
2:51everything you do into two piles.
2:53Anything you will still be using in a
2:54month, a system prompt, a skill, a big
2:57irreversible decision, is an asset. Pay
3:00Fable once to make it. Anything you
3:02throw away by Friday is throughput. Run
3:04that on the cheap model without a second
3:06thought.
3:07The people who win the next repricing
3:09are not the ones mourning the model.
3:11They are the ones harvesting it. So, let
3:13us harvest. Five moves, every prompt
3:15included. Here is the first. Move one.
3:18Plant Fable's judgment right into your
3:19workspace. The highest value thing a
3:22frontier model leaves behind is not an
3:24answer. It is a standard. Your
3:26Claude.md, your skills, your memory
3:29files, that is the layer every future
3:31model reads before it touches a line of
3:32your work. An answer helps you once. A
3:35standard upgrades every answer that
3:37comes after it. And today, Fable can
3:39write that layer at a level Opus can
3:41follow perfectly, but could never have
3:43authored on its own. That gap is exactly
3:46the thing you are banking. So, run this
3:48in every project you care about. Read
3:50this entire project and how I work in
3:51it, then rewrite my Claude file as the
3:54operating manual a less capable model
3:56would need to work here at my level.
3:58Name the conventions I follow, name the
4:00mistakes a weaker model will make in
4:01this codebase, each one with the rule
4:03that prevents it. Then the line that
4:05carries the whole thing. Write the
4:07quality bar for each deliverable as
4:09checkable criteria, not adjectives. A
4:12cheaper model cannot invent a quality
4:14bar out of thin air, but hand it a
4:16written one and it applies that bar just
4:18fine every time. Close the prompt by
4:21asking Fable for the three skills that
4:22would save you the most hours written
4:24out in full. You are not asking for
4:26advice about skills. You are asking it
4:28to build them right now while the meter
4:30still says free. Move to the consultant
4:33audit. Fable's real edge shows up on
4:36hard messy problems, the kind with no
4:38clean answer waiting at the back of the
4:40book. On the hardest tier of the coding
4:42benchmarks, it roughly doubles the next
4:44model and the gap only widens as the
4:46problems get uglier.
4:48So give it the ugliest problem you
4:49actually own, your business. Open a
4:52session with your projects, your
4:53numbers, whatever context you can feed
4:55it and say, "Act as the consultant I
4:57cannot afford. Audit everything, offers,
5:00pricing, workflows, where my hours go,
5:03then hand me a road map I can execute
5:05with a weaker model ranked highest
5:07return first." The deliverable rule is
5:09the whole point. For every move, Fable
5:11writes down the why, the exact steps,
5:14what done actually looks like, and what
5:16a weaker model needs told to execute it
5:18today while the model that can reason it
5:20out is still flat rate. Opus does not
5:23need to be brilliant next week. It just
5:25needs to follow a brilliant document and
5:27make it name the three things you should
5:28stop doing with the reasoning spelled
5:30out in full. A cheaper model will
5:32happily keep you busy. It takes frontier
5:35judgment to tell you, with receipts,
5:37which of your work is quietly worthless.
5:39Quick aside because I know someone will
5:41ask. If you want the full training on
5:43turning this kind of output into actual
5:44income, there is a real-time AI ops
5:47community built for exactly that over at
5:49weeklyaiops.com.
5:51That is the only plug-in this video.
5:53Back to the moves. Move three, build a
5:56second brain. If judgment is Fable's
5:58edge, deep research is where that edge
6:00runs deepest. Long multi-step synthesis
6:03is its single widest measured lead over
6:05every other model out there. So, today
6:08you spend a real slice of your hours on
6:09sheer volume. Run deep research on your
6:12niche, your competitors, the problems
6:14your customers keep hitting, the methods
6:16you have been meaning to study for a
6:17year. Then mine every run into an
6:19Obsidian vault, the free notes app where
6:22each note links to the notes around it.
6:24One insight per note. And whatever you
6:26do, do not let it hand you a 40-page
6:28report. A report gets read once and
6:31buried. A hundred small linked notes get
6:33retrieved and reused for years. So,
6:35atomize everything. The vault quietly
6:37becomes the context that every future
6:39session reads before it answers you.
6:41Here's why this works, and it is
6:43honestly my favorite story in all of AI.
6:46Back in the llama era, the most copied
6:48training set of them all was built by
6:50pulling 52,000 answers out of a frontier
6:52model for under $500 and training a tiny
6:55open one on them. That frontier model,
6:58text-davinci-003,
7:00was shut down in January 2024. The
7:02teacher is dead. Everything it taught
7:04still runs. That is the entire strategy
7:07for today. Extraction, not conversation.
7:10Move four, fire off the goals. The first
7:12three moves bank what Fable knows. This
7:15one spends the thing you actually lose
7:16tomorrow, unattended hours. Fable's
7:19signature trick is holding a single job
7:21for hours without once losing the plot.
7:24That endurance is the exact thing that
7:26stops being free tomorrow. So, today you
7:28point it at your backlog and you walk
7:30away from the desk. Two commands do this
7:33inside Claude code, the terminal app the
7:35model runs in. /goals sets a finish line
7:38instead of a prompt. You describe what
7:40done looks like and the model works turn
7:42after turn, while a second, smaller
7:44model checks the condition after every
7:46turn, and only stops the run when it is
7:48genuinely met. Dynamic workflows are the
7:51scale layer on top. Fable writes an
7:53orchestration script for your task, and
7:55that script fans out dozens of sub
7:57agents in the background in parallel,
7:59cross-checking each others findings
8:01while your own session stays completely
8:03free. A goal holds the finish line. The
8:05workflow does the fan out.
8:07A real one reads like this. /goal Every
8:11module in this repo has a test file. The
8:13full suite passes with the complete
8:15green run pasted here in the chat, and a
8:17migration note documents every change,
8:19or stop after 25 turns and paste me the
8:21failures. Two rules keep this safe
8:23instead of terrifying. First, demand
8:26pasted proof in the finish line. The
8:28judge model only reads the conversation.
8:30It cannot run your tests or open your
8:32files, so the condition asks for the
8:34green run pasted, never promised.
8:36Second, cap every run, turns, or wall
8:39clock written right in. One uncapped
8:42loop quietly builds someone $6,000 by
8:44morning. So, do not fire off 10 loops in
8:47a panic. Pick the two or three goals
8:49with the most value locked up inside
8:50them, and let Fable grind those all the
8:52way to done while you are asleep.
8:55If you want a running start, this
8:56pattern already has a library. Whole
8:58collections of ready-made loops and
9:00workflows, each one paired with a prompt
9:02and the exact tool it plugs into, built
9:04the same way Carpathia talks about. The
9:06model writes the plan, then executes it.
9:09Steal the loops that fit your backlog
9:11and point them at your own repo tonight.
9:13Move five, and if you only have 1 hour
9:15left today, do this one first. Every
9:18time Fable cracks a genuinely hard
9:20problem, its approach evaporates the
9:22second the session ends. You keep the
9:24answer, and you lose the thinking. This
9:26move installs a recorder so you never
9:28lose it again. Create a single file
9:30.claude skills extract approach skill.md
9:34that captures how a problem was actually
9:36solved, not just the fix. Then wire it
9:39into your Claude file with one line of
9:41learning law. After every non-trivial
9:43solve, run the extract approach skill
9:45before moving on. From now on, a
9:48solution without its learnings note is
9:50unfinished work. So go work Fable hard
9:52on your real backlog, the gnarly bug,
9:55the architecture call you keep circling,
9:57and every single solve drops a note
9:59behind it as it goes. And these notes
10:01are not summaries. A good one reads like
10:04a field report. Here was the trap. Here
10:06is why the obvious fix was wrong. Here
10:08is the approach that actually held, and
10:10here is the check that proves it. That
10:12is the reasoning a weaker model could
10:14never generate, sitting in plain text
10:16where it can simply read it. Those notes
10:18are the distillate, Fable's reasoning
10:20sitting in your own repo, readable by
10:22every model that comes after it. That is
10:24why this one compounds, and why it goes
10:26in first. It turns all your remaining
10:29Fable time into permanent assets
10:31automatically in the background. Step
10:33back and look at what those Fable moves
10:35actually leave behind. A standard in
10:37your workspace, a ranked roadmap, an
10:39atomized vault, a shelf of unattended
10:42loops, a recorder that documents every
10:44solve, five artifacts, and not one of
10:47them cares which model you are running
10:48next month. That is the system. Now let
10:51me make the transplant completely
10:52literal. This is the sharpest version of
10:54the whole idea. 10 minutes today and you
10:57walk away owning the reasoning instead
10:59of renting the model. There is even a
11:01short script at the end that does the
11:03entire thing over the API. And save the
11:05result to a file you keep. Start from
11:07the uncomfortable truth. The model was
11:09never the asset.
11:11Attaching your workflow to one specific
11:13model is building on rented land. It
11:15always gets deprecated, repriced, or
11:17replaced. What survives every single
11:19time is the thinking system you can
11:21describe in plain words, and Fable's
11:23edge really is describable. Reading what
11:26a request is actually asking for.
11:28Breaking a hard problem into pieces you
11:30can each check on their own. Verifying
11:32its own work instead of trusting what
11:34merely sounds right, refusing to guess
11:36when it does not know. All of that is
11:38just language, which means all of it is
11:40portable. Step one, extract the manual,
11:43not a summary. Most people ask Fable to
11:46explain how it thinks and get back a
11:48page of pleasant fluff. You do not want
11:50a description of the thinking, you want
11:52the procedures. Check your work is a
11:53vibe. For any percentage, find both
11:56endpoints yourself and divide, because
11:59that is where flip sides hide. That is a
12:01procedure a model can actually run. So,
12:03the prompt is exact. You are the most
12:05capable model on my account, and access
12:07to you narrows tomorrow.
12:09Write the operating manual your
12:10replacement will run on, Opus 4.8,
12:13strong but a step below you. Write it as
12:16a senior operator handing their craft to
12:18a sharp junior. How to read intent, how
12:20to verify by re-deriving, how to attack
12:23your own conclusion before you ever hand
12:24it over. Step two, transplant it. A
12:27manual does nothing sitting in a chat
12:29window. Open a project in Claude, paste
12:32that manual into the project
12:33instructions, and set the model to Opus.
12:36Now, every conversation inside that
12:37project inherits Fable's way of working
12:40before it reads a single word of your
12:41actual task. Step three is the one
12:44everybody skips, and it is the one that
12:46proves the whole thing. Give both
12:48versions the same trap.
12:50A report says revenue grew from 4
12:51million to 4.2 million and calls it a
12:5420% gain. Ship it? Plain Opus often
12:57waves it through because the sentence
12:59reads smoothly. Opus running Fable's
13:01manual stops, re-derives the number,
13:04catches that it is 5%, not 20, and
13:06refuses to ship. If it catches the
13:08error, the transplant took. You just
13:11watched reasoning move from one model
13:12into another with your own eyes. And if
13:14it does not catch it, then your manual
13:17was too vague on verification, and that
13:19is useful information, not a failure.
13:21You go straight back to Fable and tell
13:23it to make the verification section
13:24procedural, exact steps, not
13:27encouragement. You are debugging a
13:28document and you can do that all day
13:30while the model is still free. The money
13:33makes the whole thing obvious. A full
13:35extraction run today inside your plan
13:37cost you nothing. Run the very same
13:39extraction after the switch and it is a
13:41few dollars of credits.
13:43That is the tell for every decision from
13:45here.
13:45Pay the frontier model once to mint an
13:47asset, then let the cheap model spend it
13:50a thousand times over. One bonus while
13:52you are still in there. For each thing
13:54you do every week, tell Fable,
13:56"Interview me about this workflow one
13:58question at a time until you understand
14:00it cold, then write it up as a complete
14:02skill my future assistants will follow."
14:05Answer honestly and you walk out with
14:07your own judgment frozen into a file
14:08that runs on any model for free forever.
14:12After tomorrow, this exact situation
14:14just repeats. A frontier model appears,
14:16gets repriced, gets pulled. One was even
14:19yanked with no notice, brought back
14:21after the backlash, then retired anyway
14:23six months later. Outputs you did not
14:25save while you had access cannot be
14:27reconstructed once it is gone. Every
14:29teacher leaves. What you extracted is
14:31what you keep. So keep this playbook.
14:34The test. Can a cheaper model redo it
14:36tomorrow? If yes, skip it. One, rewrite
14:40your Claude file and skills as checkable
14:42standards. Two, the consultant audit and
14:45its road map. Three, deep research mind
14:47into an atomized vault. Four, goals and
14:50workflows on your highest value backlog
14:53with pasted proof and hard caps. Five,
14:55the recorder skill wired in to fire on
14:58its own. The panic is optional. The
15:00manual is forever. Remember the order if
15:02you are short on time. Five first, then
15:05four because it runs alone, then one,
15:08two, three. And the next time a frontier
15:10window swings open, you will not spend
15:12it on demo apps. I will see you in the
15:14next one. Cloud codes, extract
15:17everything worth keeping.

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