Release Notes

v0.0.1 — “The Syntax Revolution”

We are thrilled to announce the inaugural public release of Dev (v0.0.1).

Modern engineering stacks have suffered under the weight of non-deterministic, GPU-dependent black boxes. With v0.0.1, we return to foundational computing principles by delivering a next-generation runtime that converts business logic directly into instruction sets your CPU already understood in 1978.

What's New

Native Support for Deterministic Branch Primitives: Introduced experimental keywords if, else, and switch. These constructs allow engineers to express binary logic paths without transmitting prompts over public HTTP networks.
Zero-Weights Architecture: Reduced binary payload from 140GB of quantized FP16 tensors to a lean 4.2MB compiled executable.
Instantaneous Cold Boots: Eliminated the 45-second CUDA container initialization overhead. Logic branches are now executable within standard thread scheduling intervals (< 2ms).
Breaking Changes:
- Deprecated temperature: Logic either evaluates to true or false. Floating-point ambiguity has been removed from control flow.
- Deprecated top_p: All array iterations now evaluate in chronological index order unless explicitly sorted.
- Deprecated system_prompt: Replaced with standard inline code comments.

Interactive Cost Estimator: Middle-Out AI Deletion

Use this formula to calculate your immediate annual runway extension by replacing multi-hop LLM agent orchestrators with local Dev primitives:

Annual Savings = (LLM Calls/Day × Average Cost/Token × 365) + Vector DB Subscriptions − $0.00

Live Sandbox Simulator

Monthly Burn Eliminated: $4,250
Runway Recaptured: $51,000/year
Performance Delta: 10,000x - 50,000x (Replaced network I/O with L1 Cache)

interface InfrastructureAudit {
  dailyQueries: number;
  monthlyVectorDbCost: number;
  avgTokensPerQuery: number;
  costPer1kTokens: number;
}

export function estimateDevSavings(audit: InfrastructureAudit): {
  monthlyLlmSpend: number;
  annualSavingsWithDev: number;
  latencyReductionFactor: string;
} {
  const dailyTokenCost = (audit.dailyQueries * audit.avgTokensPerQuery * audit.costPer1kTokens) / 1000;
  const monthlyLlmSpend = (dailyTokenCost * 30) + audit.monthlyVectorDbCost;

  // Dev requires zero external API subscriptions or persistent cloud indexes
  const annualSavings = monthlyLlmSpend * 12;

  return {
    monthlyLlmSpend: Math.round(monthlyLlmSpend),
    annualSavingsWithDev: Math.round(annualSavings),
    latencyReductionFactor: "10,000x - 50,000x (Replaced network I/O with L1 Cache)",
  };
}

// Example: Mid-sized SaaS processing 50k classification requests per day
const auditResults = estimateDevSavings({
  dailyQueries: 50_000,
  monthlyVectorDbCost: 650,
  avgTokensPerQuery: 800,
  costPer1kTokens: 0.003, // Blend of input/output tokens
});

console.log(`Monthly Burn Eliminated: $${auditResults.monthlyLlmSpend}`);
console.log(`Runway Recaptured: $${auditResults.annualSavingsWithDev}/year`);
console.log(`Performance Delta: ${auditResults.latencyReductionFactor}`);

Calculated Benchmark Results

Metric	Legacy Multi-Agent Orchestrator	Dev Linear Compiler
Average p99 response time	1.84s	0.00012ms
Cloud invoice	$4,250/mo	$0.00/mo
Accuracy	93.4% (due to occasional token truncation)	100% deterministic accuracy