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rename Arc to Fabro in README, marketing site, and events strategy doc
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Bryan Helmkamp
parent
e968ece42c
commit
4dd76b259e
4 changed files with 16 additions and 16 deletions
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@ -19,16 +19,16 @@ curl -fsSL https://fabro.sh/install.sh | bash
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## Use Cases
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- **Extend disengagement time** — Stop babysitting an agent REPL. Define a workflow with verification gates and walk away — Fabrokeeps the process on track without you.
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- **Extend disengagement time** — Stop babysitting an agent REPL. Define a workflow with verification gates and walk away — Fabro keeps the process on track without you.
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- **Leverage ensemble intelligence** — Seamlessly combine models from different vendors. Use one model to implement, another to cross-critique, and a third to summarize — all in a single workflow.
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- **Share best practices across your team** — Collaborate on version-controlled workflows that encode your software processes as code. Review, iterate, and reuse them like any other source file.
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- **Reduce token bills** — Route cheap tasks to fast, inexpensive models and reserve frontier models for the steps that need them. CSS-like stylesheets make this a one-line change.
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- **Improve agent security** — Run agents in cloud sandboxes with full network and filesystem isolation. Keep untrusted code off your laptop and out of your production environment.
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- **Run agents 24/7** — Arc's API server queues and executes runs continuously. Close your laptop — workflows keep running and results are waiting when you return.
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- **Run agents 24/7** — Fabro's API server queues and executes runs continuously. Close your laptop — workflows keep running and results are waiting when you return.
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- **Scale infinitely** — Move execution off your laptop and into cloud sandboxes. Run as many concurrent workflows as your infrastructure allows.
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- **Guarantee code quality** — Layer deterministic verifications — test suites, linters, type checkers, LLM-as-judge — into your workflow graph. Failures trigger fix loops automatically.
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- **Achieve compounding engineering** — Automatic retrospectives after every run feed a continuous improvement loop. Your workflows get better over time, not just your code.
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- **Specify in natural language** — Define requirements as natural-language specs and let Arc generate — and regenerate — implementations that conform to them.
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- **Specify in natural language** — Define requirements as natural-language specs and let Fabro generate — and regenerate — implementations that conform to them.
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---
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@ -13,7 +13,7 @@ const { title } = Astro.props;
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<meta name="description" content="Arc is an open-source AI software factory for expert engineering teams. Ship production code through deterministic workflows, built-in verification, and full observability." />
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<meta name="description" content="Fabro is an open-source AI software factory for expert engineering teams. Ship production code through deterministic workflows, built-in verification, and full observability." />
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<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
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<link rel="preconnect" href="https://fonts.googleapis.com" />
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
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@ -36,13 +36,13 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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}`;
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---
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<Layout title="Arc — AI Software Factory">
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<Layout title="Fabro — AI Software Factory">
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<!-- Nav -->
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<nav class="fixed top-0 z-50 w-full border-b border-navy-800/60 bg-navy-950/70 backdrop-blur-xl">
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<div class="mx-auto flex max-w-6xl items-center justify-between px-6 py-4">
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<a href="/" class="flex items-center gap-3">
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<img src="/symbol.svg" alt="Arc" class="h-8 w-8" />
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<span class="font-display text-xl font-bold tracking-tight text-ice-50">Arc</span>
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<img src="/symbol.svg" alt="Fabro" class="h-8 w-8" />
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<span class="font-display text-xl font-bold tracking-tight text-ice-50">Fabro</span>
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</a>
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<div class="flex items-center gap-6">
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<a href="https://docs.arc.computer" class="text-sm text-ice-300 hover:text-ice-50 transition-colors">Docs</a>
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@ -105,7 +105,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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Controlled, auditable pipelines<br class="hidden sm:inline" /> for real engineering
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</h2>
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<p class="reveal reveal-d1 mt-5 text-lg leading-relaxed text-ice-300">
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Instead of one-shot code generation, Arc runs workflows: plan, implement, verify, review, ship — using
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Instead of one-shot code generation, Fabro runs workflows: plan, implement, verify, review, ship — using
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the right model at each step, with guardrails that fail closed.
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</p>
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</div>
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@ -208,7 +208,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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Built for real engineering,<br class="hidden sm:inline" /> not promptware
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</h2>
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<p class="mt-5 text-lg leading-relaxed text-ice-300">
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Arc is built like infrastructure: solid architecture, strong defaults, and the reliability you expect from production tooling.
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Fabro is built like infrastructure: solid architecture, strong defaults, and the reliability you expect from production tooling.
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</p>
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<ul class="mt-8 space-y-4">
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<li class="flex items-start gap-3">
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@ -274,7 +274,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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Verification is a<br class="hidden sm:inline" /> first-class concept
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</h2>
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<p class="mt-5 text-lg leading-relaxed text-ice-300">
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Arc doesn't just produce output — it validates it. Builds and tests are gates, not suggestions.
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Fabro doesn't just produce output — it validates it. Builds and tests are gates, not suggestions.
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LLM review adds a layer. Human review loops close the gap.
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</p>
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<p class="mt-6 text-sm font-semibold text-teal-500">
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@ -295,7 +295,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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Multi-model, multi-provider
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</h2>
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<p class="mt-5 text-lg leading-relaxed text-ice-300">
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Different steps deserve different models. Arc orchestrates an ensemble so you get the best
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Different steps deserve different models. Fabro orchestrates an ensemble so you get the best
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quality per dollar — fast models for breadth, frontier models for correctness.
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</p>
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<ul class="mt-8 space-y-4">
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@ -385,7 +385,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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</div>
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</section>
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<!-- Why Arc -->
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<!-- Why Fabro -->
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<section class="relative py-28">
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<div class="section-divider mx-auto max-w-xs"></div>
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<div class="mx-auto max-w-4xl px-6 pt-28 text-center">
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@ -393,7 +393,7 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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Shippable outcomes,<br class="hidden sm:inline" /> not impressive output
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</h2>
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<p class="reveal reveal-d1 mt-5 text-lg text-ice-300">
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Most AI coding tools optimize for impressive output. Arc optimizes for what actually merges.
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Most AI coding tools optimize for impressive output. Fabro optimizes for what actually merges.
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</p>
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<div class="reveal reveal-d2 mt-14 grid gap-x-8 gap-y-8 text-left sm:grid-cols-2">
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<div class="flex items-start gap-4">
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@ -478,8 +478,8 @@ const cssExample = `<span class="text-ice-300">/* Fast model for planning */</sp
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<div class="mx-auto max-w-6xl px-6">
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<div class="flex flex-col items-center justify-between gap-4 sm:flex-row">
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<div class="flex items-center gap-3">
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<img src="/symbol.svg" alt="Arc" class="h-6 w-6" />
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<span class="text-sm text-ice-300">Arc — Open source, MIT-licensed</span>
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<img src="/symbol.svg" alt="Fabro" class="h-6 w-6" />
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<span class="text-sm text-ice-300">Fabro — Open source, MIT-licensed</span>
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</div>
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<div class="flex items-center gap-6">
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<a href="https://docs.arc.computer" class="text-sm text-ice-300 hover:text-ice-50 transition-colors">Docs</a>
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@ -286,7 +286,7 @@ Error information is stored as plain strings. The `error` field contains the hum
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| `failure_reason` | string? | StageFailed, StageCompleted | Outcome-level failure description |
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| `failure_class` | string? | StageFailed, StageCompleted | Machine classification: `transient_infra`, `deterministic`, `budget_exhausted`, `compilation_loop`, `canceled`, `structural` |
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`failure_class` is derived from `ArcError::failure_class()` for handler errors, or from handler hints in `context_updates["failure_class"]` for outcome-based failures. See `error.rs` for the classification logic.
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`failure_class` is derived from `FabroError::failure_class()` for handler errors, or from handler hints in `context_updates["failure_class"]` for outcome-based failures. See `error.rs` for the classification logic.
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## Consumers
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