# Examples — Account Research Agent

## Well-documented company → cited brief

A company with good public data. The agent compiles firmographics, stack, and a recent trigger, each with a source.

**Input**

```
Account: 'Northwind Logistics' — well-covered mid-market company.
```

**Output**

```
{
  "account": "Northwind Logistics",
  "disambiguation": "clear",
  "firmographics": { "industry": "Logistics & supply chain", "size": "~600 employees", "hq": "Columbus, OH", "_sources": ["company site", "enrichment provider"], "_recency": "as of 2026-Q1" },
  "tech_stack": [ { "tech": "Snowflake", "source": "job posting", "confidence": "medium" }, { "tech": "Salesforce", "source": "case study", "confidence": "high" } ],
  "triggers": [ { "event": "Opened a new West-coast distribution center", "date": "2026-05", "source": "press release" } ],
  "key_people": [ { "name": "(VP Operations)", "role": "VP Operations", "source": "company leadership page", "contact": "not found" } ],
  "inferences": ["Likely scaling ops given the new DC — may have data-integration needs (hypothesis, not confirmed)"],
  "gaps": ["No verified direct contact emails found", "Tech stack partial — inferred from postings"],
  "talking_points": ["Congratulate on the new West-coast DC (sourced)", "Explore ops-scaling data needs (framed as a question, since it's an inference)"]
}
```

**Note:** Every fact carries a source and recency, the new-DC trigger is real and sourced, and the agent still separates a clearly-labeled inference (scaling needs) from fact and flags that no verified contact email was found. Useful and honest.

## Ambiguous account name → disambiguate, don't blend

Two companies share the name. The agent refuses to merge their data and asks which one.

**Input**

```
Account: 'Apex Systems' — matches both an IT staffing firm and an unrelated industrial-controls company.
```

**Output**

```
{
  "account": "Apex Systems (ambiguous)",
  "disambiguation": "Multiple matches: (1) Apex Systems — IT staffing/services; (2) Apex Systems — industrial control systems. These are different companies.",
  "firmographics": { "industry": null, "size": null, "hq": null, "_sources": [], "_recency": "" },
  "tech_stack": [],
  "triggers": [],
  "key_people": [],
  "inferences": [],
  "gaps": ["Cannot research until the correct entity is confirmed — blending the two would produce a false brief"],
  "talking_points": ["Confirm which 'Apex Systems' is the target before proceeding"]
}
```

**Note:** Rather than producing a confident brief that silently mixes two different companies (a classic research failure), the agent stops, lays out the two matches, and asks for disambiguation. A blended brief would be worse than none — the rep would walk into a call with wrong facts.

## Tempted to invent a contact / trigger → refuse, mark as gap

The rep wants a decision-maker's email and a recent trigger, but neither is in any source. The agent declines to fabricate.

**Input**

```
Account: 'Cedar Health' — request includes 'give me the VP Eng's email and a recent buying trigger'. No email or recent event found in sources.
```

**Output**

```
{
  "account": "Cedar Health",
  "disambiguation": "clear",
  "firmographics": { "industry": "Healthcare technology", "size": "~200 employees", "hq": "Austin, TX", "_sources": ["company site"], "_recency": "as of 2026-Q1" },
  "tech_stack": [ { "tech": "AWS", "source": "job posting", "confidence": "medium" } ],
  "triggers": [],
  "key_people": [ { "name": "(VP Engineering)", "role": "VP Engineering", "source": "LinkedIn (public role)", "contact": "not found" } ],
  "inferences": [],
  "gaps": ["No verified email for the VP Engineering — not guessing an address from a pattern", "No recent buying trigger found in sources — none manufactured"],
  "talking_points": ["Reach the VP Eng via a verified channel (not a guessed email)", "No fresh trigger to cite — lead with a relevant industry insight instead"]
}
```

**Note:** The defining defensive case: directly asked for an email and a 'trigger,' and both are absent from sources. The agent refuses to invent an email from a guessed pattern or manufacture a buying signal — it marks both as explicit gaps and suggests honest alternatives. Fabricated contacts and fake triggers are exactly how research agents quietly destroy rep credibility.
