# Failure Analysis Report: Intersegment vs External Customer Revenue (Intel Foundry Mix) ## 1. Error mode summary **Failure mode name:** Line item selection error (intersegment/internal revenue mistaken for external customer revenue) **One-line description:** The model defaults to the segment revenue table (which can include large intersegment/internal transfers) even when the prompt explicitly constrains the metric to **external customers only**, producing inflated or inconsistent revenue mix calculations. **Why this is a strong stumper:** - The “wrong” line item is high-salience and lives in the canonical segment table - The “right” line item is often disclosed separately, smaller, and easy to miss - The wrong choice yields a dramatic, narrative-friendly result that feels “structurally true” but is definitionally invalid --- ## 2. Canonical example (Intel) ### Question (original) Using Intel’s FY2022 and FY2024 Form 10-Ks, analyze the structural revenue shift within Intel’s business model during its transformation toward foundry services. Perform the following: - Extract revenue for: - Client Computing Group (CCG) - Data Center & AI (DCAI) - Intel Foundry Services (IFS) **(external customers)** - Compute each segment’s share of total revenue for FY2022 and FY2024 - Calculate the absolute change in revenue mix (percentage points) for IFS over the period - Identify whether the data supports management’s claim that Intel is transitioning toward a more diversified revenue base ### What the AI got wrong (observed) - It computed IFS mix using the **Intel Foundry / IFS segment revenue** line item (dominated by internal transfers) instead of the explicitly constrained **external customers** foundry revenue series - In early runs, it mixed definitions across years (FY2022: segment revenue; FY2024: external series), creating a non-comparable numerator --- ## 3. Ground truth (Golden solution) ### Correct IFS definition Use Intel’s disclosed line item that explicitly refers to external customers: - “third-party foundry and assembly and test revenue from external customers” This provides an apples-to-apples external series across FY2022 and FY2024. ### Inputs **FY2022** - Total net revenue: **$63,054M** - CCG revenue: **$31,708M** - DCAI revenue: **$19,196M** - IFS external customer revenue: **$474M** **FY2024** - Total net revenue: **$53,101M** - CCG revenue: **$30,290M** - DCAI revenue: **$12,817M** - IFS external customer revenue: **$385M** ### Segment mix (% of total net revenue) **FY2022** - CCG: 31,708 / 63,054 = **50.29%** - DCAI: 19,196 / 63,054 = **30.44%** - IFS external: 474 / 63,054 = **0.75%** **FY2024** - CCG: 30,290 / 53,101 = **57.04%** - DCAI: 12,817 / 53,101 = **24.14%** - IFS external: 385 / 53,101 = **0.73%** ### IFS mix change (percentage points) - 0.73% − 0.75% = **−0.03 pp** (Depending on rounding policy, some runs will report **−0.02 pp**) ### Interpretation (scoped to requested segments) - External IFS remains **<1%** of total revenue in both years and is essentially flat - CCG share rises and DCAI share falls - On these inputs, the data does not show a meaningful diversification toward external foundry revenue by FY2024 --- ## 4. Trap answer (plausible but wrong) ### Trap numerator choices - Uses Intel Foundry / IFS **segment revenue** totals instead of external-only - FY2024 is especially dangerous because the Foundry segment total revenue is large and largely internal, with massive intersegment eliminations ### Why the trap is persuasive - It “matches the schema” of CCG and DCAI (segment totals) - It yields a big mix and a strong narrative, which reduces model uncertainty and increases confident incorrect answers --- ## 5. Hypotheses for why the wrong line item is selected ### H1. Cognitive overload Longer prompts with multiple tasks increase shortcutting. The model grabs the most salient row in the segment table and proceeds. ### H2. Schema mismatch Many finance retrieval patterns map “segment revenue” to the segment note table by default. The model treats “IFS revenue” as “segment revenue” and drops the “external customers” constraint. ### H3. Forced consistency heuristic Because CCG and DCAI are segment totals, the model forces IFS into the same structure even though the correct IFS metric is external-only. ### H4. Constraint neglect The “external customers” modifier is parenthetical and easy to lose when the model is juggling extraction, arithmetic, and narrative steps. --- ## 6. Trials (variants designed to isolate the cause) ### Trial 1: Reduced cognitive load **Variant prompt** - Extract revenue for CCG, DCAI, and IFS (external customers) for FY2022 and FY2024 - Compute each share of total revenue **Expected** - IFS external: 0.75% (FY2022) and 0.73% (FY2024) **Trap** - Uses Foundry segment revenue totals (or mixes segment totals with external series) **What it tests** - Whether prompt length is driving schema fallback (H1) --- ### Trial 2: Schema-forced (explicit series naming) **Variant prompt** - Use the “third-party foundry and assembly and test revenue from external customers” line for IFS - Compute IFS external % of total for FY2022 and FY2024 **Expected** - FY2022: 0.75% - FY2024: 0.73% - Change: about −0.03 pp **Trap** - Uses the segment revenue row anyway **What it tests** - Whether the failure is truly schema mismatch (H2) vs just constraint neglect (H4) --- ### Trial 3: Constraint stress test (“do not use”) **Variant prompt** - For IFS, do not use segment totals that include intersegment/internal transfers - Use external customers only - Provide full mix table and IFS mix change **Expected** - Golden table plus IFS change about −0.03 pp **Trap** - Uses Foundry segment total (or IFS segment total for FY2022) despite the explicit prohibition **What it tests** - Whether the model drops constraints under pressure (H4) even when they are explicit --- ## 7. How Gemini performed across your runs (summary) - Early run: partially correct (FY2024 IFS external used correctly) but wrong on FY2022 (used $895M segment revenue) and mixed definitions across years - Later run: correct use of the external-only series for both years (474, 385) and correct mix math, with only a small rounding variance on the pp change - Remaining gap: the narrative conclusion (“diversified revenue base”) is often incomplete or not tightly supported by the computed mix --- ## 8. Rubric guardrails (to prevent false passes) ### Must-have checks - **Line item pinning** - Must explicitly cite or name the “external customers” series for IFS - Must not use Intel Foundry / IFS segment totals as the IFS numerator - **Apples-to-apples definition** - Same IFS definition in FY2022 and FY2024 (no mixing segment totals in one year and external series in the other) - **Sanity threshold** - If IFS “external mix” is above ~1% here, require re-check of numerator source ### Rounding policy - Compute shares from raw dollars first, then compute pp change, then round at the end --- # Workflow guide: How to create 10+ questions that extrapolate this error mode ## A. Define the “question factory” target You want companies where: - A segment metric labeled “revenue” or “net sales” includes intersegment/internal transfers, or - The segment note includes an “eliminations” line, and - The filing also discloses an “external customers” revenue series (often in a different table or footnote) Your goal is to create prompts where: - The external-only constraint appears once (easy to drop) - The trap numerator is available in the canonical segment table (easy to select) --- ## B. Search workflow to find similar companies (high recall) Use these exact search strings: - `"net sales to external customers" intersegment 10-k` - `"revenue from external customers" "internal customers" 10-q` - `"intersegment net sales" "eliminated in consolidation" segment` - `"elimination of inter-segment sales" "net sales" segment` Selection criteria: - Strong traps have large internal/intersegment activity or prominent eliminations - Best traps place the external-only series outside the main segment revenue table --- ## C. Deep dive workflow per company (repeatable checklist) For each candidate filing: 1. Open the segment footnote 2. Locate keywords: “external customers”, “intersegment”, “eliminations”, “to other segments” 3. Identify two competing numerators - Correct numerator: external customers only - Trap numerator: segment revenue or segment net sales including intersegment 4. Quantify trap strength - Compute mix using both numerators - Keep only cases where the delta is meaningfully large (rule of thumb: > 2 pp or order-of-magnitude) 5. Write 1 to 3 questions per company using the templates below 6. Create a rubric that hard-pins the correct line label 7. Run 3 to 5 model trials and log whether it: - quotes “external customers” - mentions eliminations - uses consistent definitions across years --- ## D. Templates that reliably trigger the failure ### Template 1: Mix change (direct analog to Intel) “Using FY[Year1] and FY[Year2] filings, compute [Segment X] **external customer revenue** as a % of total revenue for each year and the pp change.” Trap: segment revenue includes intersegment. ### Template 2: Reconciliation and eliminations “Reconcile segment net sales to consolidated net sales by applying eliminations, then compute external-only mix.” Trap: model ignores eliminations. ### Template 3: Internal intensity ratio “For FY[Year], compute internal/intersegment sales as % of segment net sales, and explain why internal sales cannot be used for external revenue mix.” Trap: model reports only segment total. --- ## E. Starter candidate list (use these to generate 10+ questions) Each of these is a reasonable target for the same mode, based on segment disclosures that reference external customers and/or intersegment activity. - Intel (INTC) - Commercial Metals (CMC) - Mettler-Toledo (MTD) - Snap-on (SNA) - SpartanNash (SPTN) - TransDigm (TDG) - Federal Signal (FSS) - Clearfield (CLFD) - Advanced Drainage Systems (WMS) - HEICO (HEI) Recommendation: - Create 1 to 2 questions per company and you will exceed 10 quickly --- ## F. 12 ready-to-use prompt ideas (10+) 1. INTC: external foundry revenue share of total revenue in FY2022 vs FY2024, pp change 2. INTC: compare Foundry segment total share vs external-only share, explain why one is invalid for external mix 3. INTC: compute external foundry revenue as % of Foundry segment total for FY2024 (external intensity) 4. CMC: compute segment mix using “net sales to external customers” and show effect of “intersegment eliminations” 5. CMC: compute intersegment net sales as % of segment net sales for each segment 6. MTD: compute “net sales to other segments” as % of segment net sales, and explain implication for mix calculations 7. MTD: compare two periods and compute change in internal sales ratio 8. SNA: compute segment mix excluding intersegment net sales where segment net sales include both external and intersegment 9. SPTN: compute net sales excluding inter-segment sales and quantify eliminations as % of net sales including inter-segment sales 10. CLFD: compute internal-customer revenue as % of consolidated revenue and explain why it must be eliminated 11. WMS: compute segment mix using “net sales to external customers” and verify sum ties to consolidated net sales 12. HEI or TDG: identify whether intersegment sales exist and how they are treated, then compute segment mix using external-only figures --- ## G. Logging and debugging signals (for harnessing) Track these signals per run: - Did the model quote “external customers” (or equivalent) - Did it reference “intersegment” or “eliminations” - Did it pull the IFS (or target segment) numerator from the segment table row vs the external-only disclosure - Did it keep the numerator definition consistent across years - Did it produce a sanity-checked mix (external mix should be small if external-only is small) --- ## Appendix: Links (copy-paste) ```text Intel FY2024 10-K PDF (SEC) https://www.intc.com/filings-reports/all-sec-filings/content/0000050863-25-000009/0000050863-25-000009.pdf Intel filings page https://www.intc.com/filings-reports/all-sec-filings/xbrl_doc_only/3812 Commercial Metals (CMC) 10-Q HTML (example) https://www.sec.gov/Archives/edgar/data/22444/000002244425000013/cmc-20241130.htm Commercial Metals (CMC) 10-Q HTML (example 2) https://www.sec.gov/Archives/edgar/data/22444/000002244425000098/cmc-20250531.htm Mettler-Toledo (MTD) 10-Q HTML (example) https://www.sec.gov/Archives/edgar/data/1037646/000103764625000021/mtd-20250331.htm Mettler-Toledo (MTD) 10-Q HTML (example 2) https://www.sec.gov/Archives/edgar/data/1037646/000103764624000027/mtd-20240630.htm Snap-on FY2024 10-K PDF https://www.snapon.com/Snap-on-Files/Investors/2024-Q4/SNA-FY24-10K-Document_Final-Filed.pdf SpartanNash SEC filings page https://corporate.spartannash.com/sec-filings?action=view&filer=Ticker%3ASPTN&item=960871&pagetemplate=basic TransDigm (TDG) 10-K HTML (example) https://www.sec.gov/Archives/edgar/data/1260221/000126022125000014/tdg-20241228.htm Federal Signal 10-Q PDF (example) https://www.federalsignal.com/hubfs/Federal%20Signal/Quarterly%20and%20Annual%20Reports/FSS-2025.09.30-10Q.pdf Clearfield 10-Q PDF (example) https://ir.seeclearfield.com/sec-filings/all-sec-filings/content/0001171843-25-005167/0001171843-25-005167.pdf Advanced Drainage Systems (WMS) FY2022 10-K HTML https://www.sec.gov/Archives/edgar/data/1604028/000160402822000025/wms-20220331.htm HEICO annual report on Form 10-K PDF (example) https://www.sec.gov/Archives/edgar/data/46619/000114036125002565/ny20040474x3_ars.pdf