How to Get the Most Out of Fable 5
We’re hosting two live camps for paid Every members to put the latest frontier tools to work: Fable 5 Camp this Friday, June 12, followed by a rescheduledCodex for Power Users Camp on Friday, June 26. If you already registered for this Friday’s camp, your seat is saved for the Fable deep dive, and you can RSVP for the Codex Camp.
‘AI & I’:How Anthropic uses Claude Fable 5 with Mike Krieger
Today, we’re releasing a new episode of our podcast AI& I. Dan Shipper sits down with Mike Krieger , the cofounder of Instagram and head of Anthropic Labs, to discuss what it feels like to build with Fable 5 , a model powerful enough that it’s forcing him to rethink the very definition of productivity, engineering, and creative agency.
As someone who built one of the most popular consumer apps in the pre-GPT era and has had access to Fable 5 for months, Krieger has a rare vantage point on what the radical compression of the product development arc means for builders.
Watch on X or YouTube , or listen on Spotify or Apple Podcasts. You can also read the transcript.
Here are the highlights:
- More work is happening overnight. Fable 5 is the first model capable enough that you can hand it a complex task, walk away, and trust it will be completed by morning. When it hits an obstacle—a remote service goes down, say, or a tool stops working—it writes a workaround and forges ahead. That resilience has changed the daily rhythm of Krieger’s work: He now ends his workday by briefing the model on what needs to get done while he sleeps, rather than sitting down to do it himself.
- The gap between what’s in your head and what exists in the world is closing. Given access to Fable 5 and a set of internal MCPs, an Anthropic recruiter described the experience as, “The first time in my life where I feel like the thing that’s in my head and the thing that exists in the world are right next to each other. I can just do it.” This is the most meaningful thing about the new model class, Krieger says—it allows non-engineers to create the exact products they need to get more done.
- Software engineering is dead. Long live software engineering. Engineers now spend less time writing code and more time setting direction, reviewing what their AI agents have built, and making judgment calls when something breaks in production. The divide between product managers and engineers has blurred. “There is a feeling of loss, I think, in some of the better engineers that I talk to, as well as the feeling of, ‘Oh my God, but I can do insane amounts of work now at the same time.’ We’re holding both ideas in our heads at once,” Krieger says.
- All eyes are on verification. If we can delegate more to the model, it becomes more important to check what it has built works in practice. Krieger’s approach combines regression testing on known workflows, visual checks—including giving the model video captures of its own work so it can catch animation glitches screenshots would miss—and mock backends for anything too complex to test live. When a bug arrives via Slack, Fable 5 makes the fix, posts the pull request, then follows up hours later.
Miss an episode? Catch up on Dan’s recent conversations with LinkedIn cofounder Reid Hoffman ; the team that built Claude Code, Cat Wu and Boris Cherny ; Vercel cofounder Guillermo Rauch ; podcaster Dwarkesh Patel ; and others, and learn how they use AI to think, create, and relate.
How the Every team is using Fable 5
The easiest way to be disappointed by Fable 5 is to use it as if it were GPT-5.5 or Opus 4.8 , smart models that require specific instructions and careful prompting for the best results.
Instead, Fable 5 feels like working with a capable coworker—at least that’s Every’s consensus after a week of testing.
“It feels like you have an engineer on your team that you just gave a problem to, and they’ll figure it out,” says Cora general manager Kieran Klaassen.
That means, to get the most out of Anthropic’s first Mythos-class model available to the public, you have to think like a manager : Equip the model with context, goals, and a way to verify the work, then step aside. It may even stumble on a solution you hadn’t considered.
Not every task deserves this treatment. Smart colleagues don’t come cheap, and neither does Fable 5. Here’s how to get the most out of this powerful new model and some of the workflows the team is using.
Pick the right tasks
Tasks that are good candidates for Fable 5 have four qualities: You’re able to give the model organized and deep context, a well-defined goal, and a clear definition of what good or done looks like, and the importance of the task justifies the cost.
The model is smart enough to reason its way through complex problems and likes to carry tasks through to the end, but if your data is wrong or out of date, or your goals conflict, it will likely reach the wrong conclusion. That’s less of a concern on earlier, less powerful models, where you’re giving feedback more frequently during a task and could catch those mistakes.
Advanced users of AI—who operate at Level 7 or Level 8 on our AI adoption curve —are already comfortable delegating to their agents. For everyone else, using the model demands a mental reframing. Instead of iterating back and forth, the work gets frontloaded into providing the right context and establishing clear directives, letting Fable 5 do its thing, and only reviewing the results once it’s completed the entire task. The examples below are entry points to get you started.
Example 1: Fix a broken workflow
Senior engineer Nityesh Agarwal built a Claude Code skill to help Every’s consulting team create first drafts of PowerPoint decks. It worked, but it kept hitting the same snags: Boxes were slightly misaligned, images weren’t the right size, and sometimes a footer would be updated on one slide but not another. One run with Claude Code took about 30 minutes, used roughly 100 million tokens, and still came back with errors.
Nityesh pointed Fable 5 at the Claude Code session log and asked it to review where the PowerPoint skill was breaking down.
Fable 5 found the root problem. Under the hood, a PowerPoint file is a bundle of XML files that store the position, size, styling, and order of everything on a slide. Claude was being asked to edit those hidden files directly, so a simple request like “change this phrase” or “move this image two inches left” required the model to find the right hidden text and rewrite the surrounding layout code without disturbing anything else.
Fable 5 built a command-line tool that gives agents a more natural way to work with PowerPoint— if the text on a specific slide needs to be updated, for example, or an image has to be resized, the agent can use the tool to make these targeted changes instead of having to rewrite the entire XML file.
Nityesh’s takeaway: Use Fable 5 to diagnose broken workflows, create the tools or skills that fix them, and then let cheaper models use that infrastructure going forward.
Nityesh's prompt
Here is a session log from an agent trying to complete this workflow: [describe workflow]. It struggled in these ways: [time, cost, errors, bad outputs, repeated failures]. Take a step back and analyze where the current tool, skill, or workflow is breaking down. What is the root cause of the failure, and how would you fix it? Make a plan first. Then build or specify the upgrade. Test it against the same kind of task, and explain how cheaper models could use it later.