Production Code.From a Prompt.
TTrryy  IItt  NNooww
IntroducingBACKBOARD STUDIO
Backboard Studio's Recursive-CLI and IDE builds better code with less tokens using the same frontier models.

MacOS

Install R-CLI
$curl -fsSL https://app.backboard.io/api/cli | bashCopy

WINDOWS (powershell)

Install R-CLI
$irm https://app.backboard.io/api/cli/windows | iexCopy
Same Models.Same Performance.Up to 30% Fewer Tokens.
Same Models.Same Performance.Up to 30% Fewer Tokens.
It's that good.
It's that good.
TTrryy  IItt  NNooww
Performance

Build more. Spend less.

Same underlying models, apples-to-apples. Backboard Studio improves efficiency and cost performance.

Baseline
20–30% more output
5–10x more output
Standard API
Backboard Studio
Backboard Studio (OSS)
Same models
Performance

Build more. Spend less.

Same underlying models, apples-to-apples. Backboard Studio improves efficiency and cost performance.

Baseline
20–30% more output
5–10x more output
Standard API
Backboard Studio
Backboard Studio (OSS)
Same models
R-CLI Demo

See it in action.

01Watch R-CLI generate production-ready code from a single prompt — thinking, writing files, running tests, and shipping.

📁 backboard
◆ Backboard R-CLI (v0.2.10)
session ready
mode agent
model gpt-5.5 medium
directory ~/Projects/my-app
context 301 / 1.1M
build me a website for my startup
◆ I'll scaffold a Next.js landing page:
⊙ Write app/page.tsx
✓ 0.2s
◆ Done — 4 files.
ready agent openai/gpt-5.5 think:medium 301/1.1M (0%)
Studio

One studio, from prompt to production.

02Generate, review, connect, and ship — Backboard Studio carries every change from a prompt to production-ready code without leaving the workspace.

billing.ts — reviewrunning
export async function createUsageLimit() {
- return generate()
+ const ctx = await backboard.context.load()
+ return generateFeature({ ctx })
}
simulationsrunning
Generating implementation…
Running tests · 42 passing
✓ Generated billing.ts
R-CLI

It starts in your terminal.

03R-CLI decomposes a goal into steps, runs them, verifies the result, and recurses until it's done — your entry point into the studio.

backboard — r-cli
Backboard R-CLI · session
$ backboard generate "auth flow"
Analyzing project context...
Generating implementation...
export async function POST(req) {
return generateFeature({ ctx })
}
✓ Ready for review in Studio
Context

Grounded in your project's context.

04Every generation is informed by your code, schema, and policies — so output stays consistent and correct across iterations.

project context
app/routes
api/contextsynced
schema.sql
auth-policy.md
Services

Wires into the stack you already run.

05Connect APIs, databases, and auth in a few lines — the full-stack API is one part of the studio underneath.

Services
R-CLI Demo

See it in action.

01Watch R-CLI generate production-ready code from a single prompt — thinking, writing files, running tests, and shipping.

📁 backboard
◆ Backboard R-CLI (v0.2.10)
session ready
mode agent
model gpt-5.5 medium
directory ~/Projects/my-app
context 301 / 1.1M
build me a website for my startup
◆ I'll scaffold a Next.js landing page:
⊙ Write app/page.tsx
✓ 0.2s
◆ Done — 4 files.
ready agent openai/gpt-5.5 think:medium 301/1.1M (0%)
Studio

One studio, from prompt to production.

02Generate, review, connect, and ship — Backboard Studio carries every change from a prompt to production-ready code without leaving the workspace.

billing.ts — reviewrunning
export async function createUsageLimit() {
- return generate()
+ const ctx = await backboard.context.load()
+ return generateFeature({ ctx })
}
simulationsrunning
Generating implementation…
Running tests · 42 passing
✓ Generated billing.ts
R-CLI

It starts in your terminal.

03R-CLI decomposes a goal into steps, runs them, verifies the result, and recurses until it's done — your entry point into the studio.

backboard — r-cli
Backboard R-CLI · session
$ backboard generate "auth flow"
Analyzing project context...
Generating implementation...
export async function POST(req) {
return generateFeature({ ctx })
}
✓ Ready for review in Studio
Context

Grounded in your project's context.

04Every generation is informed by your code, schema, and policies — so output stays consistent and correct across iterations.

project context
app/routes
api/contextsynced
schema.sql
auth-policy.md
Services

Wires into the stack you already run.

05Connect APIs, databases, and auth in a few lines — the full-stack API is one part of the studio underneath.

Services
R-CLI Demo

See it in action.

01Watch R-CLI generate production-ready code from a single prompt — thinking, writing files, running tests, and shipping.

📁 backboard
◆ Backboard R-CLI (v0.2.10)
session ready
mode agent
model gpt-5.5 medium
directory ~/Projects/my-app
context 301 / 1.1M
build me a website for my startup
◆ I'll scaffold a Next.js landing page:
⊙ Write app/page.tsx
✓ 0.2s
◆ Done — 4 files.
ready agent openai/gpt-5.5 think:medium 301/1.1M (0%)
Studio

One studio, from prompt to production.

02Generate, review, connect, and ship — Backboard Studio carries every change from a prompt to production-ready code without leaving the workspace.

billing.ts — reviewrunning
export async function createUsageLimit() {
- return generate()
+ const ctx = await backboard.context.load()
+ return generateFeature({ ctx })
}
simulationsrunning
Generating implementation…
Running tests · 42 passing
✓ Generated billing.ts
R-CLI

It starts in your terminal.

03R-CLI decomposes a goal into steps, runs them, verifies the result, and recurses until it's done — your entry point into the studio.

backboard — r-cli
Backboard R-CLI · session
$ backboard generate "auth flow"
Analyzing project context...
Generating implementation...
export async function POST(req) {
return generateFeature({ ctx })
}
✓ Ready for review in Studio
Context

Grounded in your project's context.

04Every generation is informed by your code, schema, and policies — so output stays consistent and correct across iterations.

project context
app/routes
api/contextsynced
schema.sql
auth-policy.md
Services

Wires into the stack you already run.

05Connect APIs, databases, and auth in a few lines — the full-stack API is one part of the studio underneath.

Services

Industries we power.

Code Generation Grounded in Your Industry

Healthcare.

Longitudinal patient memory for clinical workflows — from coaching apps to platforms managing 1M+ patient profiles.

FinTech.

Transaction-aware code generation for billing, compliance, and fraud detection pipelines grounded in policy.

E-commerce.

Generate checkout flows, inventory hooks, and recommendation endpoints from your catalog schema and business rules.

Legal.

Contract analysis, regulatory tracking, and policy-aware code generation grounded in your legal documentation.

EdTech.

Adaptive learning systems built from curriculum context — generate assessments, progress tracking, and content delivery.

DevTools.

Integrates with Git and Jira so engineers retrieve architectural decisions and code context in a single query.

Get started with Backboard

Wire Backboard into one service today and unlock 17,000+ models, BYOK, stateful behavior, adaptive context, and many free models across your stack.

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