How do I install the Learn Summit 2023 Talks skill?

Run npx skillmds@latest add hiteshbandhu/learn-summit-2023-talks in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Learn Summit 2023 Talks safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Learn Summit 2023 Talks?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Learn Summit 2023 Talks free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Learn Summit 2023 Talks?

hiteshbandhu (@hiteshbandhu) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Learn Summit 2023 Talks by hiteshbandhu

Name: Learn Summit 2023 Talks
Author: hiteshbandhu

Learn Summit 2023 Talks

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".

hiteshbandhu Updated Sep 17, 2026

File contents

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

---name: learn-summit-2023-talksdescription: 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".---# Learn Summit 2023 talksAction playbook from twenty-two AI Engineer Summit 2023 talks. **Do not summarize talks** — pick a workflow and execute it.**Supporting files:**- [workflows.md](workflows.md) — workflows A–N- [source-index.md](source-index.md) — src-NNN → learningsOptional 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](workflows.md) for steps and deliverables.---## Install```bashcp -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 user1. Name workflow (A–N) and artifact2. Save under `./skill-outputs/learn-summit-2023-talks/` when requested---## Invocation examples```@learn-summit-2023-talks production RAG checklist from Jerry Liuframework for open questions in our AI roadmappydantic vs typechat for our API layer```

Frequently asked questions