What you’ll learn
Four copy-able artifacts a hiring loop runs on: the recruiter intake template, the master screening rubric, a stage-by-stage red-flag checklist, and LinkedIn Boolean strings for sourcing.
With Hiring Manager, 30 minutes.
Recruiter intake call: FDE search
With Hiring Manager · 30 minutes
1. Trigger What triggered this opening? Who's doing this work today? What happens if we don't fill it? 2. Day-in-life Walk me through what week 4 looks like. Hour by hour. 3. Customer Who is the customer? Are they technical? Where does the FDE physically sit? 4. Build vs. implement balance What % of their time is writing production code merged into mainline vs. configuration vs. customer meetings? If <30% writing merged code, it's not actually an FDE; it's a Solutions Architect or Implementation Lead. 5. Success metric How will we know in 6 months this hire was great? What number, artifact, or customer outcome? 6. Anti-profile Who would crush a FAANG SWE loop but fail in this seat? 7. Comp band + level Specific.
Used across the loop. Score 1–4 on each dimension.
| Dimension | Weight | Source round |
|---|---|---|
| Customer fluency / empathy | High | Recruiter, HM, Customer Sim |
| Grit / radical ownership | High | HM, Values, References |
| Problem decomposition | Critical | Onsite, Decomposition |
| Product sense | High | HM, Decomposition |
| Technical depth (production) | High | Technical screen, System design |
| AI tool proficiency | Critical | Technical screen + AI probe |
| Communication clarity | High | Every round |
| Scope discipline / saying no | Medium | Customer sim |
| Coachability | Medium | References |
Use during loop debriefs.
Red-flag checklist by stage
Use during loop debriefs
Resume:
• Only enterprise titles, no shipped artifacts.
• Buzzword-stuffed JD descriptions.
• 10+ years FAANG-only.
• Refuses GitHub or AI-augmented work samples.
Recruiter screen:
• Can't articulate why FDE specifically.
• Refers to all AI as "ChatGPT".
• Passive voice ("the team shipped …").
• No customer-facing experience or aspiration.
Technical screen:
• Can't explain code AI just produced.
• Pastes whole codebase into context.
• No plan before coding.
• Behavioral signals of stealth AI overlays.
• Defensive when asked to narrate.
Customer simulation:
• Solves before scoping.
• Blames customer's systems.
• Promises timelines without diagnosis.
• Cracks under polite escalation.
References:
• Manager declines to comment on customer-facing work.
• 'Would hire back' only for a lower role.
• Cross-functional partner unavailable.Run as saved searches; rerun weekly.
Direct-title catch + adjacent (broad)
LinkedIn Boolean: direct + adjacent
Use as a saved search
("Forward Deployed Engineer" OR "Forward Deployed Software Engineer" OR FDSE OR "Applied AI Engineer" OR "Deployment Strategist" OR "Customer Engineer" OR "Solutions Architect" OR "Solutions Engineer" OR "Solutions Architect II" OR (Python OR TypeScript OR Go) AND (LLM OR Claude OR GPT OR Anthropic OR OpenAI OR Cursor OR Palantir OR Anduril)) AND ("San Francisco" OR "New York" OR "London")Founding engineer pool (highest conviction)
LinkedIn Boolean: founding engineers
Filter to Series A / B + AI infra mentions
("Founding Engineer" OR "Founding Software Engineer" OR "Employee #" OR "First engineer" OR "Engineer #1" OR "Engineer #2" OR "Engineer #3") AND (YC OR "Y Combinator" OR "Series A" OR "Series B") AND ("data extraction" OR "data ingestion" OR "agent infrastructure" OR (Cursor OR Anthropic OR enterprise OR deployment OR onboarding))Key takeaways