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Learn summit 2023 talks

Skill hiteshbandhu/skills-i-use/skills/ai-engineer-talks/learn-summit-2023-talks

Drop-in skills and plugins for your AI development workflows

Install

npx -y skills add hiteshbandhu/skills-i-use --skill learn-summit-2023-talks

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Applies AI Engineer Summit 2023 main-stage playbooks for RAG, agents, interfaces, local LLMs, fine-tuning, product velocity, TypeChat/Pydantic, LangChain observability, and the discipline of AI engineering (Swyx, Willison). Use when grounding team practice in summit talks, shipping RAG/agents, or onboarding to AI engineering; or when the user says "summit 2023 talks", "1000x AI engineer", "production RAG Jerry Liu", "open questions Willison".

SKILL.md

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Learn Summit 2023 talks

Action playbook from twenty-two AI Engineer Summit 2023 talks. Do not summarize talks — pick a workflow and execute it.

Supporting files:

workflows.md — workflows A–N
source-index.md — src-NNN → learnings

Optional deliverables: {SKILL_OUTPUT_DIR}/learn-summit-2023-talks/

Step 0 — Pick workflow

What is the user trying to do?
├─ Define AI engineering career / 1000x leverage           → A  [src-018, src-002, src-022]
├─ Production RAG + vectors + wild deployments             → B  [src-006, src-015, src-017]
├─ Agents + context-aware reasoning                      → C  [src-019, src-005]
├─ Domain fine-tuning / adaptation                       → D  [src-009]
├─ Local / private LLM deployment                        → E  [src-010]
├─ Viral AI product / growth lessons                     → F  [src-001, src-011, src-003]
├─ LLM system building blocks (product)                  → G  [src-004]
├─ Interfaces & abstraction ladder                     → H  [src-008, src-021]
├─ Type-safe LLM I/O (Pydantic / TypeChat)               → I  [src-014, src-013]
├─ Data platform AI pivot                                → J  [src-020]
├─ Multimodal APIs (see/hear/speak/draw)                 → K  [src-016]
├─ Reactive / streaming AI apps                          → L  [src-007]
├─ Open questions & yearly retrospectives                → M  [src-012]
└─ Move fast without breaking prod                       → N  [src-011]

Open workflows.md for steps and deliverables.

Install

cp -r skills/learn-summit-2023-talks ~/.claude/skills/
cp -r skills/learn-summit-2023-talks ~/.cursor/skills/

Source: playlists/ai-engineer-summit-2023-talks/.

Cross-cutting rules

Rule	Source
AI engineering ≠ prompting; systems wrap non-AGI models	[src-018 @ 5:53]
Naive RAG fails in production — plan retrieval + eval	[src-006 @ 2:58]
Ask: impossible new builds vs faster builds (Willison)	[src-012 @ 1:01]
Structured outputs reduce integration risk	[src-014], [src-013]
Agents need product-grade interfaces, not chat-only	[src-019], [src-021]

Output to user

Name workflow (A–N) and artifact
Save under ./skill-outputs/learn-summit-2023-talks/ when requested

Invocation examples

@learn-summit-2023-talks production RAG checklist from Jerry Liu
framework for open questions in our AI roadmap
pydantic vs typechat for our API layer

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.