I've analyzed the full 187-page Q2 Financial Report. Here are the key performance indicators:

Revenue & Growth

Profitability

Customer Metrics

Notable Risks flagged in the report:

Concentration risk: Top 10 customers represent 31% of ARR. Legal exposure from ongoing EU data compliance audit estimated at $2–8M.

React Server Components (RSC) are now stable in React 19 and production-ready via Next.js App Router. Here's how to use them effectively:

Core principle: Components are Server by default — only add 'use client' when you need interactivity.

// ✅ Server Component — no directive needed
// Runs on server, can fetch data directly
async function ProductList() {
  const products = await db.products.findMany();
  return (
    <ul>
      {products.map(p => <ProductCard key={p.id} product={p} />)}
    </ul>
  );
}

// ✅ Client Component — only for interactivity
'use client';
function AddToCartButton({ productId }: { productId: string }) {
  const [loading, setLoading] = useState(false);
  return <button onClick={() => handleAdd(productId)}>Add to Cart</button>;
}

When to use Server Components:

Production patterns:

Based on recent web searches, here are the major developments in AI reasoning models as of May 2026:

OpenAI o3 & o4-mini have become the dominant reasoning benchmarks, with o3 scoring 96.7% on AIME 2025 math competitions. OpenAI's "thinking budget" API parameter lets developers control compute vs. latency tradeoffs.

Google DeepMind's Gemini 2.0 Flash Thinking launched with 1M token context + native reasoning chains, showing particularly strong performance on multi-step coding tasks and scientific reasoning.

Anthropic Claude 3.7 Sonnet introduced "extended thinking" mode — visible chain-of-thought that users can inspect, addressing the interpretability gap in reasoning models.

Key trend: Hybrid architectures — fast instinct models (< 100ms) paired with slow reasoning models for complex subtasks — are emerging as the production pattern for cost-effective AI applications.

Comparing the two UI designs across key dimensions:

Visual Hierarchy

Typography

Both use sans-serif at appropriate sizes, but V2's weight differentiation (600 for headers vs 400 for body) creates clearer scanning patterns.

Recommendation: Go with V2's color scheme and layout grid, but adopt V1's card border treatment (subtle 1px border vs V2's flat cards) for better depth perception in dark mode.