# Yulia Interview — Levels of AI Usage & the Candidate Knowledge Base

#source

## Source Metadata

- **Raw path:** `raw/sources/Yulia interview.md`
- **Source type:** interview conclusions/insights doc (auto-generated summary; speakers unnamed in text)
- **Participants:** [[yulia]] (SPEAKER_00, HR/recruiting lead — name inferred from filename, Status: tentative) and [[eugene]] (SPEAKER_01, senior programmer ~20 years, works on [[inspectron]], $200 Claude max plan)
- **Ingestion date:** 2026-07-14

## Core Claims

- **AI usage has distinct levels, and most people are stuck at level one:** web chatbot → built-in memory → Claude Code/Cowork with local files → CLAUDE.md → skills → Obsidian knowledge base → RAG. The practical ceiling for non-programmers is **CLAUDE.md + skills** ([[levels-of-ai-usage]]).
- **Solve first, skill-ify after** — the recurring mistake is building the skill up front; instead reach the final solution once with Claude, then say "now create a skill from this" ([[solve-first-then-skillify]]). Turn any correction loop longer than ~3 messages into a skill.
- **Both recruiting problems are the same problem:** a candidate database plus search over it — record interviews, auto-transcribe with diarization, generate standardized profiles, then query by skill.
- **AI automates all information work; the human keeps the human parts** — "the human's role in this process is just to be human — introductions, communication." (Converges with [[connections-as-moat]].)
- **AI prices will rise, not crash** — "what I now buy for 200 will cost about 1,000"; the bubble pops *upward*, and leverage shifts to knowing which models to use. Status: tentative (prediction).
- **Renting GPU beats owning** for this workload: ~$0.10/candidate on RunPod vs a $1,500–2,000 machine — though a home GPU transcribes overnight for free.

## Key Evidence / Details

- Live demos: RunPod transcription; Claude driving a browser to pull LinkedIn HR contacts into a Markdown list. LinkedIn bans bots — only shallow passes (~20 contacts) are safe.
- Immediate no-tooling practice change: **start recording candidate interviews now**, one file per candidate, named by candidate (consent implied per [[2026-07-14-nina-interview]]).
- Stack recommendation: Claude (Cowork for non-programmers); RAG only matters at corporate scale; cheaper models (e.g. Qwen) do the same tasks "just worse."
- Prompting principle: your job is to "narrow the variability of interpretation" — vague asks invite "fantasy."
- Reusable framing: "Split yourself into two people — one slightly smarter (you, the manager), one slightly dumber (the AI, your subordinate)."
- Deal context: webinar plan to be drafted over a weekend, **no deadline**; a paid build of the HR system is on the table (rough "$5 to $100" per-project range needs scoping), possibly a shared monthly service on Eugene's subscription.
- Company-scale idea: a lightweight AI "assistant" chatting with employees to form an information core — automating much of the PM/status-reporting role.

## Connections

- Entities: [[yulia]], [[eugene]], [[nina]] (referenced), [[inspectron]], [[claude-code]], [[virtido]] (Yulia's team affiliation tentative)
- Concepts: [[levels-of-ai-usage]], [[solve-first-then-skillify]], [[skills-as-memory]], [[connections-as-moat]], [[personal-ai-operating-system]], [[context-as-scarce-resource]]
- Companion interview: [[2026-07-14-nina-interview]] (same team's pain points from the recruiter's seat)

## Open Questions

- Exact scope, deliverables, and price of the HR system build.
- Webinar date/title (later fixed as *"From a chat box to your own operating system"* per [[2026-07-14-nina-interview]] — this interview likely predates it).
- Rent GPU vs. buy a GPU machine — folded into Yulia's next hardware purchase decision?
- Larisa's Claude memory complaint — fixable via built-in memory/CLAUDE.md, but her actual BA/PM task was never detailed.
- Is SPEAKER_00 really named Yulia, and is she at [[virtido]]? Inferred from filename + references to Nina/Sergiy. Status: tentative.

## Change Impact on Wiki

- Created [[yulia]]; created concepts [[levels-of-ai-usage]] and [[solve-first-then-skillify]].
- Updated [[eugene]] (Inspectron, $200 plan, paid-build offer), [[connections-as-moat]] (Eugene independently lands on the human-connection residual), [[skills-as-memory]] (~3-message correction-loop heuristic), [[overview]].