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Claude Code With Claude Fable 5.1 And Long– Running Agents
Claude Code With Claude Fable 5.1 And Long– Running Agents
Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With Claude Code With Claude Fable 5.1 And Long– Running Agents, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
Published 9/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.31 GB | Duration: 2h 37m
Do work you never imagined you could do. Pick the right model, opitmise Claude Code, run it overnight. DRIP course
What you'll learn
Pick the Claude model and the effort level for any task, and back the choice with a price and a measured result.
Make your first Claude API call, read every field of the response, and work out what that call really cost you.
Set effort, size the output limit, and stream long calls so a slow answer never looks like a crash.
Write prompts that name the outcome you want, and cut the extra instructions that now make output worse.
Build your own Claude Code setup: memory rules, skills, hooks, subagents, and connections to outside systems.
Answer the data retention and safety questions your security team asks before Claude goes anywhere near your code.
Read your context window live, control what compaction keeps, and hold the durable facts in files.
Hand Fable hours of work with spend guards and checks in place, then audit its report against the evidence.
Requirements
You can write and run basic Python. The exercises use Python 3.10 or newer.
A Claude API key for the early sections, and Claude Code installed from the daily workflow section onward.
No prior Claude Code experience. The first Claude Code lesson is a five minute refresher.
Description
This course contains the use of artificial intelligence. Some of the videos use an AI voice trained on my own voice. I use it because on-camera delivery has never been my greatest strength, so I chose a narration style that lets me focus fully on teaching.This course is a DRIP course. I am updating, adding, and editing the course as we go along. Message me what you want me to cover; I want to make this course as useful as possible for you.This is a hands-on course about Claude Fable 5.1 and Claude Code for developers who already ship code. You learn to decide which Claude model, which effort level, and which Claude Code mechanism a piece of work needs. Then you hand hours of work over and check what comes back. Here is where you are going. Developers are describing going to sleep and waking up to a project eighty percent done, and you want that too. After this course, you stop watching every step, and you start handing over. You give Fable the long work, or you let it guide the cheaper models while you keep two sessions open, and you finish in days what used to take weeks. You leave a project running overnight and go to sleep, because you set the gates, and in the morning you check the report in ten minutes and move on. You give Fable exactly the work it earns, so you get the most capable model at a cost you decided. And your Claude Code setup does the repeating for you: the rules you keep typing live in memory files, the steps you keep explaining become a skill you call by name, subagents take the side work on a cheaper model, and a hook makes the check happen every time. Not because you work more hours, but because Fable works those long hours for you.Here is what makes this course different. Most Claude Code teaching shows you the tool. In this course I teach you how to decide: which model gets the work, which effort level, how much to specify, and when to hand hours of work over and walk away. Hooks, skills, subagents, and long-running agents each get their own lessons, not a single lecture inside a general course.The second difference is where the facts come from. Every number on screen is read from a public page you watch load, with its date visible, not from my memory and not from a slide. Every capability you see is a recorded run, including the runs that go against the sales pitch. Twelve of those runs were on a repository with a real bug planted in it, and in several of them a much cheaper model fixed it just as reliably as the expensive one did. You see those results in full. When Fable is the wrong choice, the course says so, and shows the cheaper model finishing the job.The third difference is cost. Fable is expensive, and nobody likes surprises. An early lesson states the cost of following along before you spend a cent and gives you a cheaper path if you want one. Every lab ships with a recorded replay mode, so you can practice the whole thing without spending anything and switch to live mode with your own key when you are ready. Prices and plan rules change, so every number you see carries the date it was read.Here is what you do, section by section.Section one, Your first win with Fable. You see what hours-long autonomous work actually looks like, you place Fable next to the other Claude models, you learn the rule that decides which model gets which work, and you find out what the whole course costs to follow. You also get the Fact Tracker, a one page habit for checking things yourself instead of taking anyone's word for it.Section two, Access and your first API call. You reach Fable through every route there is, and you learn which routes start billing without asking. Then you write a first Claude API call line by line, read every field that comes back, and set up streaming and timeouts so a call that takes minutes never looks like a crash.Section three, Thinking and effort: the settings you control. You find out what raising the effort level actually changes in observable behavior, how to size the output limit so a long answer never truncates halfway, and why your bill is bigger than your estimate. Then you move an existing project onto Fable with three changes.Section four, Safety measures and what they mean for your code. You learn the safety design in Anthropic's own words, the one instruction that reliably gets ordinary work refused, and what to do in code when a perfectly normal prompt comes back rejected. You also get the data retention answer exactly right, in the words a security officer needs to hear.Section five, Prompting Fable: outcomes, not steps. Your old prompt collection was written for older models and it is holding you back. You learn the five current prompting recommendations, you cut the over-prescription that now makes output worse, and you watch an outcome prompt beat a step-by-step prompt on the same task. One exception still requires you to be explicit, and you learn that too.Section six, Fable in Claude Code: the daily workflow. This is where your day changes. You set and switch model and effort deliberately; you repair a wrong result with the one move that fixes it; you hand work to subagents and keep working yourself; and you audit what you spent after real work. You also decide who approves what, use plan mode and checkpoints so a risky attempt costs nothing to undo, and pick up yesterday's session where you left it.Section seven, Make Claude Code yours: memory, skills, hooks, connections. You structure the memory files Claude reads about you every session, then test what actually loads instead of assuming. You write your first skill. You rebuild an expensive built in tool so each stage runs on the cheapest model that can handle it. You define your own subagents, enforce a rule that has to hold every time with a hook, connect an outside system, and learn to pick the right mechanism from the symptom you have.Section eight, Context: what Claude sees and what compaction keeps. You read your context window live, control what compaction keeps rather than discovering later what it threw away, and keep durable facts in files so a long session survives compaction.Section nine, Long-running work. This is the strongest part of the course. You learn which long-run capability statements hold up and which are testimonials, you run multi-day work as handed-off sessions with checkpoints, and you give Claude a check it can run itself. You learn the four verification levels, the failure modes to expect and the fix for each, and the gates you set before you walk away: the spend guard, the progress audit, the stop check, and the fresh context review.Section ten: making Fable more creative. Five patterns that get you genuinely different ideas instead of the same five suggestions rephrased.Section eleven, Wrap-up and what is coming. Five questions that carry every decision you made in this course, and what arrives next.After launching the project sections, join the course: real projects built with Fable across days of handed-off sessions, and one unattended overnight run on real code, with the gates set and the status report checked line by line against the transcript.This course is released one lesson at a time. Today it holds the first 22 lessons, across the first five sections, with the code for each demo attached. The remaining sections are already planned and listed in the curriculum, marked coming soon, and each lesson is added as soon as it is finished. Every lesson that lands is yours, including the ones that arrive after you enroll, and when a new section is ready I announce it.Practice is added the same way. As the sections are finished, coding exercises, labs in a browser workspace, quizzes, and role plays where you defend your model choice to a skeptical tech lead join the lessons they belong to, in the resources under the video. Today you already get the guidance PDF on which model and which effort level to use for which work, the Fact Tracker, the code for every demo, and the reading links for each lesson.You need to be able to write and run basic Python. You need a Claude API key for the early sections and Claude Code from the daily workflow section onward. You do not need any Claude Code experience, because the first Claude Code lesson is a five minute refresher.A few things this course deliberately leaves out, so you know before you enroll. It does not teach you to build production agent systems for a team, it does not cover administration for enterprises, and it does not go into visual design tooling.Here is what you can do at the end. You decide which model gets every task, and you can defend that choice, with a price and a measured result behind it. You stop watching every step, and you start handing over. You come back in the morning to a status report and a diff, and in ten minutes you know whether it did what you asked. Do work you never imagined you could do, and have more free time than you have had in years.
Software engineers and developers who already ship code and want the most capable Claude model on the tasks that deserve it.,Developers who use Claude Code every day and still paste the same instructions into every session.,Engineers who want to hand over hours of work and know exactly how to check what comes back.,Anyone who has to decide which model and which effort level goes behind a task, and defend that choice.
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