C

Skill Entry

Custom AI semiconductor earnings claims due diligence

Structures verification of custom-AI chip vendor earnings headlines into a finance and supply-chain checklist. The workflow separates consolidated revenue and EPS beats from AI semiconductor sub-segment growth, full-year AI revenue guidance (raised vs reiterated), and infrastructure software shortfalls cited in the same report. It references CNBC reporting on June 3, 2026 that Broadcom's fiscal Q2 revenue was $22.19 billion versus $22.27 billion estimated (48% YoY), adjusted EPS $2.44 vs $2.40, AI semiconductor revenue $10.8 billion (more than doubled YoY), Q3 revenue guidance about $29.4 billion vs $28.53 billion expected, infrastructure software revenue $7.18 billion vs $7.32 billion expected, CEO Hock Tan reiterating AI semiconductor revenue in excess of $100 billion in fiscal 2027 without raising the 2026 forecast, naming six core custom-chip customers including Anthropic, Google, Meta, and OpenAI, and saying Broadcom would offer chips only rather than complete integrated AI systems—without treating media figures as procurement commitments.

Category Operations
Platform Custom silicon & AI infrastructure supply chain
Published 2026-06-04
semiconductorsearningsdue-diligence

Use cases

  • Procurement teams interpret a hyperscaler custom-chip partner's earnings miss as capacity risk
  • Finance compares reiterated $100B+ FY27 AI guidance against internal GPU/ASIC budgets
  • Strategy maps named customers (Google TPU, Meta, OpenAI) to your multi-vendor routing plan
  • Legal reviews 'chips only' vs integrated-system shifts in vendor statements
  • Investor relations needs sourced context on software drag vs AI hardware strength

Key features

  • Extract revenue, EPS, segment splits (semiconductor solutions vs infrastructure software), and guidance from the CNBC URL.
  • Record AI semiconductor revenue actuals, YoY growth, and next-quarter AI revenue outlook separately from consolidated totals.
  • Capture whether management raised, cut, or reiterated multi-year AI revenue targets.
  • List customer names and product-strategy shifts (chips-only) as qualitative context, not confirmed allocations.
  • Map implications to your contracts, lead times, and alternative suppliers.
  • Publish a memo: verified facts, guidance caveats, and retest triggers (10-Q, next earnings, customer capex filings).

When to Use This Skill

  • After CNBC earnings stories on custom AI chip vendors with mixed software/hardware results
  • Before revising ASIC/TPU capacity assumptions from a single after-hours move
  • When finance debates FY27 $100B-class guidance versus near-term quarterly AI ramps

Expected Output

Custom-AI semiconductor earnings due-diligence memo separating chip-segment facts from software misses and long-range guidance rhetoric.

Frequently Asked Questions

Does this predict Broadcom's stock direction?
No—it structures CNBC-reported earnings for internal planning; investment decisions stay outside this skill.
Can we treat $100B FY27 AI revenue as our forecast?
Record it as reiterated management guidance in media coverage; validate against issuer filings.
How does this differ from public-equity financing due diligence?
Financing skills track equity raises; this skill tracks quarterly earnings and AI semiconductor segment disclosure.

Related

Related

3 Indexed items

Third-party GPU compute lease claims due diligence

Operations

Structures verification of hyperscaler and neocloud GPU lease headlines into a capacity-planning checklist. The workflow separates announced monthly fees and GPU counts from delivery SLAs, termination clauses, and bridge-vs-strategic capacity framing in the same article. It references CNBC reporting on June 5, 2026 that SpaceX will receive $920 million per month from Google from October 2026 through June 2029 for about 110,000 Nvidia GPUs plus CPUs and memory in SpaceX data centers, with capacity ramping through September at a reduced fee; Google may end the deal if committed GPUs are not delivered by September 30, 2026; either party may terminate with 90 days' notice after December 31, 2026; a Google Cloud spokesperson cited bridge capacity for surging Gemini Enterprise demand; the deal follows SpaceX's February xAI merger valued at $1.25 trillion and Anthropic's May Colossus 1 arrangement; CNBC noted SpaceX Q1 capex $10.1 billion ($7.7 billion to AI) and AI segment operating loss $2.5 billion on $818 million revenue—without treating SEC filing figures as your signed contract terms.

Agentic AI orchestration efficiency claims due diligence

Operations

Turns CEO and vendor narratives about agentic AI efficiency into a procurement and strategy checklist. The workflow separates quoted efficiency metrics (for example token- or energy-per-user framing) from product launch facts, orchestration architecture claims, and third-party valuation context in the same article. It references CNBC reporting on June 3, 2026 that Perplexity CEO Aravind Srinivas told CNBC's Elaine Yu the long-term AI winner will maximize what he called the "most taken value per watt per user" by balancing accuracy, latency, cost, privacy, and intelligence; that Perplexity is emphasizing agentic orchestration with Perplexity Computer (announced February) and Personal Computer on Windows (announced the prior Tuesday, with Mac already available); that Srinivas said Personal Computer routes processing between device and cloud; that Perplexity was last reportedly valued at $20 billion versus Anthropic near $1 trillion and OpenAI just over $850 billion with Anthropic confidentially filing for a U.S. IPO that week; and that Srinivas cited tripled annualized revenue since the start of the year tied to integrated Anthropic model improvements—without treating media valuations or CEO efficiency slogans as internal benchmarks.

Corporate AI token spend claims due diligence

Operations

Turns headlines about corporate AI token budgets into a finance and procurement checklist. The workflow separates fundraising valuation narratives from operational metrics CFOs can verify: provider-level token bills, model-mix efficiency, team attribution, and whether frontier models are used for low-value tasks. It references CNBC reporting on June 4, 2026 that Ramp raised $750 million at a $44 billion valuation led by ICONIQ, GIC, and Ontario Teachers' Pension Plan (~38% step-up), crossed $1 billion in annualized revenue with positive free cash flow per CEO Eric Glyman, serves 70,000 businesses, and is growing partly because clients need to rein in AI spending; Glyman said tokens are a new third pillar of spend, most CFOs did not plan for steep growth, Ramp customers spending the most revenue share on AI grew revenue 12% versus flat for the lowest spenders, and Glyman called the era of tokenmaxxing nearing its end—without treating media quotes as internal budget approvals.