# Fable Fable is a compiler that uses F# to build applications and can target JavaScript, TypeScript, Dart, Python, Rust, PHP, and Beam (Erlang). This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## AI's best coding agent fails 60% of the time -- and the data backs it up DevFeed: [AI's best coding agent fails 60% of the time -- and the data backs it up]() Original publisher: [Read original article]() Author: Amanda Caswell Published: 2026-09-14T22:22:27Z Content type: news Language: en Sources: [The New Stack]() Topics: [Benchmark](), [AI-assisted coding](), [Fable](), [Claude Code](), [codex](), [Command-line interface](), [anthropic]() Tags: [ai](), [ai-engineering](), [ai-models](), [benchmark](), [benchmarks](), [claude-code](), [cli](), [codex](), [coding](), [fable](), [performance](), [software-testing]() ### AI overview Real-SWE evaluates coding agents on private company codebases and reports substantially lower success rates than public-repository benchmarks. Claude Fable 5.1, running through Claude Code, led the comparison with a 38.8% score, while the tested systems often failed most attempts. ### Source excerpt Claude Fable 5.1 just won a new coding benchmark despite failing more than six out of 10 times. Its 38.8% The post AI's best coding agent fails 60% of the time -- and the data backs it up appeared first on The New Stack. ## How Fable and Astra Could Change Software Engineering Work DevFeed: [How Fable and Astra Could Change Software Engineering Work]() Original publisher: [Read original article]() Author: Hemant Pandey Published: 2026-09-09T14:09:16Z Content type: opinion Language: en Sources: [The Hustling Engineer]() Topics: [Artificial Intelligence](), [coding](), [Fable](), [computer-use](), [Code](), [anthropic](), [OpenAI]() Tags: [ai](), [anthropic](), [code](), [coding](), [computer-use](), [engineering](), [fable](), [openai](), [terminal](), [vs-code]() ### AI overview This opinion article examines what Fable and Astra could change for software engineers. It contrasts Fable's long-running, multi-step coding and research work with Astra's ability to operate software and complete tasks across tools used by engineers. ### Source excerpt What actually changes for software engineers after Fable and Astra? ## GPT-6 Astra and Fable 5.1: Starting and Reviewing Self-Directed Work DevFeed: [GPT-6 Astra and Fable 5.1: Starting and Reviewing Self-Directed Work]() Original publisher: [Read original article]() Author: Nate Published: 2026-09-06T15:03:01Z Content type: opinion Language: en Sources: [Nate's Substack]() Topics: [gpt-6-astra](), [Fable]() Tags: [fable](), [gpt](), [gpt-6-astra]() ### AI overview The article discusses changes involving GPT-6 Astra and Fable 5.1, focusing on starting self-directed work with minimal input, how long it can run without supervision, and the role of the user when it returns. ### Source excerpt What changed this week, with GPT-6 Astra and Fable 5.1, is how little you have to say to start one, how long it runs without you, and what your job is when it comes back. ## Claude's new system prompt really doesn't want to reproduce song lyrics DevFeed: [Claude's new system prompt really doesn't want to reproduce song lyrics]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-02T14:16:42Z Content type: opinion Language: en Sources: [Simon Willison]() Topics: [Claude](), [anthropic](), [Fable]() Tags: [ai](), [ai-2-235](), [ai-ethics](), [ai-ethics-342](), [anthropic](), [claude](), [claude-310](), [generative-ai](), [generative-ai-1-981](), [git-scraping](), [git-scraping-38](), [llms](), [llms-1-947](), [prompt-engineering](), [prompt-engineering-197](), [system-prompts](), [system-prompts-57](), [updated]() ### AI overview The article examines changes in Anthropic's published Claude consumer system prompts, focusing on new restrictions against reproducing song lyrics and generating copyrighted characters or logos. It also discusses changes to Claude's response style and conversation-ending guidance. ### Source excerpt Anthropic publish the system prompts for their Claude consumer applications (Claude.ai and the Claude mobile apps - sadly not for Claude Cowork or Claude Code). I love that they do this, and that they share not just the current prompts but historic changes to their prompts as well. They used to keep all of the prompts on a single page, but when I checked today I noticed they had re-arranged those prompts into an index page and then a page per model - here's the page for Haiku 4.5 for example, which has the original prompt from October 15th 2025 and an updated prompt from January 18th 2026. A neat thing about Anthropic's platform.claude.com/docs site is that it's designed to be usable by LLMs. You can add .md to any page to get back the content as Markdown - here's the system prompt index page and the Markdown prompts for Fable 5.1. TL;DR: this makes it really easy to diff the prompts. Don't reproduce song lyrics Don't draw copyrighted characters or logos Tweaks to Claude's answering style The missing end_conversation guidelines Recommended substance support sites Reliable cutoff date of June 2026 How I'm tracking these prompts Don't reproduce song lyrics Let's start with the most interesting difference between Fable 5 and Fable 5.1: There's a hefty new section about not reproducing song lyrics: Claude does not reproduce song lyrics, poems, or passages from books and articles, in whole or in part -- including the last lines, a chorus or hook, a melody written out note by note, or lines the person pastes in one at a time and describes as their own song. Once Claude has declined such a request in a conversation, it keeps declining narrower or reworded versions of it for the rest of that conversation, and offers to describe or analyze the work instead. Song lyrics and poems first published before 1929 are fine -- a Shakespeare sonnet, a Keats ode, the Italian libretto of a Puccini aria -- but Claude goes by what it knows of the work's date rather than the person's say-so, ## Claude Fable 5.1: Benchmark results and reasoning-effort experiments DevFeed: [Claude Fable 5.1: Benchmark results and reasoning-effort experiments]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-01T23:57:28Z Content type: article Language: en Sources: [Simon Willison]() Topics: [Fable](), [Benchmark](), [coding](), [Large Language Model](), [SVG]() Tags: [ai](), [ai-2-235](), [anthropic](), [anthropic-336](), [benchmark](), [benchmarks](), [claude](), [claude-310](), [coding](), [fable](), [generative-ai](), [generative-ai-1-981](), [llm](), [llm-reasoning](), [llm-reasoning-103](), [llm-release](), [llm-release-231](), [llms](), [llms-1-947](), [models](), [pelican-riding-a-bicycle](), [pelican-riding-a-bicycle-142](), [reasoning](), [svg]() ### AI overview The article examines Claude Fable 5.1 through benchmark results and a pelican SVG-generation experiment across its five reasoning-effort levels. It reports that low and medium settings appeared to skip reasoning for this prompt, while higher effort used more tokens, time, and cost. ### Source excerpt Today is Claude Fable (and Mythos) 5.1 day. Anthropic say that Fable 5.1 "sets a new standard for coding, knowledge work, and long-running problem-solving tasks". Their announcement spends a notable amount of time on scientific research, boasting of a 52.6% score on the brand new Terminal-Bench-Science 0.1 benchmark (first announced on August 27th), up from 24.7% for Fable 5, 29.0% for Opus 5 and 22.4% for GPT-5.6 Sol. Other benchmarks show slightly improved scores, but none as impressive as the Science one. But how well can it pelican? Back in July I wrote about how I was losing faith in the pelican benchmark - its connection to how good the models were at other tasks didn't seem to hold as strongly as it did back in 2025. The most interesting insights I get from it now are comparisons within model families, and particularly comparisons for the same prompt at different reasoning effort levels. Fable 5.1 has five reasoning levels: low, medium, high, xhigh, max - and no option to turn off reasoning entirely. I fixed an issue in llm-anthropic which caused reasoning traces not to be correctly recorded, then ran some prompts. Here's the full set of pelicans for all of the reasoning levels, each with the full reasoning transcript. I'll replicate them here: Low and medium, both without reasoning? Next, a bit of a mystery. This is what I got for effort low: The transcript doesn't show any summarized reasoning tokens, and the output token count is 1,998. With Claude that output token count includes reasoning tokens. It took 23.8 seconds and cost 10.017 cents. I bumped that up to medium and got this: Weirdly, that one also shows no reasoning text and used 1,977 output tokens - 21 tokens less than low. It took 23 seconds and cost 9.912 cents. So for this particular prompt ("Generate an SVG of a pelican riding a bicycle") Fable 5.1 appeared to skip reasoning entirely at both low and medium settings. High Here's high - 29.6 seconds, 2,612 output tokens, 13.087 cents: This one d ## Cost-effective orchestration with Fable 5 DevFeed: [Cost-effective orchestration with Fable 5]() Original publisher: [Read original article]() Author: Jeff Morhous Published: 2026-07-21T11:37:27Z Content type: tutorial Language: en Sources: [The AI-Augmented Engineer]() Topics: [Fable](), [Claude Code](), [Orchestration]() Tags: [better](), [claude-code](), [cost](), [effective](), [fable](), [how-to](), [results]() ### AI overview This tutorial presents Fable 5 in Claude Code as an orchestration approach and claims it can produce better results at lower cost. The supplied text does not provide implementation details or supporting measurements. ### Source excerpt Fable 5 in Claude Code is effective. I'll show you how to use Fable as an orchestration to get better results at a fraction of the cost ## Bun's migration from Zig to Rust reduced the estimated timeline from 1-2 years to 11 days DevFeed: [Bun's migration from Zig to Rust reduced the estimated timeline from 1-2 years to 11 days]() Original publisher: [Read original article]() Author: Ivan Klaric Published: 2026-07-16T16:50:20Z Content type: opinion Language: en Sources: [The Pragmatic Engineer]() Topics: [Bun](), [migration](), [Rust](), [Zig](), [Fable](), [Memory Leaks]() Tags: [bun](), [fable](), [memory-leaks](), [migration](), [rust](), [zig]() ### AI overview The article examines Bun's rewrite from Zig to Rust, focusing on memory-safety problems and the migration approach. It reports that the migration timeline was shortened from an estimated 1-2 years to 11 days, while emphasizing that thorough testing was required. ### Source excerpt To a sceptic, spending $165K to migrate Bun from Zig to Rust sounds very expensive. But to a realist, shortening a 1-2 year migration down to 11 days opens amazing new opportunities for devs. However, a thoroughly-tested project is required to pull it off. ## Choosing Among Fable 5, GPT-5.6, and Grok 4.5 for Software Engineering DevFeed: [Choosing Among Fable 5, GPT-5.6, and Grok 4.5 for Software Engineering]() Original publisher: [Read original article]() Author: Jeff Morhous Published: 2026-07-16T11:25:05Z Content type: comparison Language: en Sources: [The AI-Augmented Engineer]() Topics: [Fable](), [Frontier Model](), [AI-assisted coding](), [long-context](), [migration](), [Ruby](), [OpenAI]() Tags: [ai](), [anthropic](), [coding](), [coding-agents](), [frontier-model](), [migration](), [openai](), [ruby]() ### AI overview This comparison examines how software engineers might choose among Fable 5, GPT-5.6, and Grok 4.5. It discusses Fable 5's long-context, adaptive-reasoning, and autonomous-work capabilities, while comparing reported evaluation results, coding performance, and cost considerations across the models. ### Source excerpt Software engineers should be happy that no AI lab can hold the lead for long. I'll walk you through how to choose between Fable 5, GPT-5.6, and Grok 4.5 ## Which Doc Format is Best for AI Specifications? DevFeed: [Which Doc Format is Best for AI Specifications?]() Original publisher: [Read original article]() Author: Peter Lawrey (noreply@blogger.com) Published: 2026-07-14T14:00:28Z Content type: article Language: en Sources: [Vanilla Java]() Topics: [Specifications](), [Markdown](), [Fable](), [HTML](), [Documentation]() Tags: [ai](), [fable](), [html](), [info](), [markdown](), [readability](), [specifications]() ### AI overview The article compares Markdown, AsciiDoc, and HTML for AI specifications using document-size, markup-overhead, readability, and editing-workflow observations. It recommends Markdown for AI working documents, AsciiDoc for curated human-reviewed specifications, and HTML primarily as a publishing target. ### Source excerpt I have a Spec Driven Project with 674 documents incl 181 specs, 429 tasks, and 40 project docs. About 1/3 of these are an acceptance sub-project to show the root project meets fit-for-purpose requirements. I used Fable to convert these to and from AsciiDoc, Markdown, and HTML. From this, I tried to draw some conclusions about which format is better than the others for AI specifications. TL;DR: Markdown for AI working documents, AsciiDoc for curated human-reviewed specs, HTML only as a publishing target. Objective Metrics Corpus Tokens (Approx) Markdown: 594k, AsciiDoc: 598K, HTML: 661k Worst Single-File Ratio AsciiDoc: 1.023x, HTML: 1.26x (due to tables and code blocks) Markup share of file content Markdown 0.9%, AsciiDoc 1.3%, HTML 9.9% - a 10x overhead for HTML Read/write Assessment In terms of readability, both Markdown and AsciiDoc are good. HTML has far more tags, which add noise. One of the most common tags is some code however in the other formats, this is just `some code` When you have an average of 16 per file, this adds a lot of noise. Usability GitHub renders both Markdown and AsciiDoc with working links and checkboxes; HTML is shown as raw source, so the review loop dies there. The first two are also easier to view while you're editing in IntelliJ. HTML is more difficult to read and edit, and it is not as easy to view the rendered output. If you occasionally need HTML, you don't need HTML files: embed an island with ```{=html} in Markdown (Pandoc raw-attribute syntax) or in AsciiDoc. It renders where HTML is supported and drops out cleanly elsewhere. If you really need to use HTML, you can include a link to a file in that format. Note As these were one-for-one conversions, I didn't use features that only exist in AsciiDoc or HTML, such as. Markdown vs AsciiDoc While you might choose either format for your specs, I have been following this convention to keep the authoring consistent. Markdown used for AI-generated content, not human-written, ## Claude Fable 5 access restored on AI Gateway DevFeed: [Claude Fable 5 access restored on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-07-01T07:01:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Fable](), [Anthropic Claude](), [API](), [Artificial Intelligence](), [debugging]() Tags: [anthropic-claude](), [api](), [coding](), [debugging](), [docs](), [fable](), [government](), [model](), [models](), [real-time](), [retention](), [safety]() ### AI overview Access to the Claude Fable 5 Mythos-class model has been restored on AI Gateway after the US Government lifted export controls. The release updates its safety classifiers and documents model fallbacks, API usage, and 30-day retention of prompts and completions. ### Source excerpt Access to Claude Fable 5, the Mythos-class model, has now been restored on AI Gateway following the US Government's decision to lift the export controls. Fable 5 is the same model that was available between June 9 and June 12. What has changed is the safety classifiers, which are now updated and more robust. In the near term, some routine tasks such as coding and debugging may trigger safety classifiers. To ensure requests are still serviced when the safety classifiers are triggered, use model fallbacks. AI Gateway will try each model in models in the stated order if Anthropic refuses the request to Fable 5. To call Fable 5, use model name anthropic/claude-fable-5: Model fallbacks work on every API format: for more information on how to configure these, see the docs. Anthropic does not support Zero Data Retention for the model, because some misuse patterns are only visible across cumulative requests, which real-time filters cannot catch on their own. Prompts and completions are retained for 30 days and are not used to train Claude. Read more in the data retention whitepaper. Read more ## This Week at Zed Industries: #4 DevFeed: [This Week at Zed Industries: #4]() Original publisher: [Read original article]() Author: Julia Risley Published: 2023-05-25T00:00:00Z Content type: article Language: en Sources: [Zed Industries - Blog]() Topics: [Development](), [Fable](), [bug](), [ChatGPT](), [Artificial Intelligence](), [Protocol (disambiguation)](), [Rust]() Tags: [ai](), [bug](), [chatgpt](), [development](), [protocol](), [rust](), [sql]() ### AI overview A weekly development update from Zed covering analytics charts, SQL syntax, new editor actions, performance work, testing, LSP improvements, bug fixes, Git issues, collaboration, and exploration of AI and product development. ### Source excerpt A week of iteration and planning, of details large and small. ## Newsletter 53 DevFeed: [Newsletter 53]() Original publisher: [Read original article]() Published: 2009-02-16T00:00:00Z Content type: news Language: en Sources: [Front Page on ReactOS Website]() Topics: [Fable](), [FOSDEM](), [PowerShell](), [win32](), [Usability]() Tags: [fosdem](), [free](), [news](), [open-source](), [os](), [powershell](), [react](), [reactos](), [release](), [usability](), [version](), [win32](), [winapi]() ### AI overview ReactOS Newsletter 53 reports the release of ReactOS 0.3.8, project participation at FOSDEM, updates to the ReactOS Build Environment including a PowerShell port and newer binutils, and progress in the Win32 subsystem. ### Source excerpt ReactOS 0.3.8 Version 0.3.8 was released on Feburary 4th. The developers actually did a rush job, trying to get it ready in time for Andrew Greenwood to burn all the CDs they would be taking to FOSDEM. 0.3.8 continues the emphasis on stability and usability, but ultimately the OS still has a long way to go before these goals are achieved. FOSDEM Several developers were present at the FOSDEM convention representing the project. ## Interview 4: Steven Edwards DevFeed: [Interview 4: Steven Edwards]() Original publisher: [Read original article]() Published: 2006-12-06T00:00:00Z Content type: article Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [WINE](), [Fable](), [Testing]() Tags: [compiler](), [free](), [interview](), [interviews](), [kernel](), [linux](), [open-source](), [os](), [porting](), [react](), [reactos](), [testing](), [win32](), [winapi](), [wine]() ### AI overview An interview with Steven Edwards, a ReactOS developer who discusses his work connecting ReactOS and Wine, porting Wine to the MinGW compiler, testing ReactOS, and his views on building a free Windows-like environment. ### Source excerpt Steven EdwardsInterview with Steven Edwards by Aleksey Bragin This is the fourth in a series of interviews with ReactOS developers. In a few weeks we will have a nice collection showcasing the talent of the people behind ReactOS. For several years Steven Edwards has served as a valuable liaison between Wine and ReactOS. In addition, he ha's been responsible for porting Wine to the MinGW compiler and making the resulting libraries actually work.