How do I install the Learn Summit 2023 Remote skill?

Run npx skillmds@latest add hiteshbandhu/learn-summit-2023-remote 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.

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Which AI agents work with Learn Summit 2023 Remote?

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 Remote 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 Remote?

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

Learn Summit 2023 Remote by hiteshbandhu

Name: Learn Summit 2023 Remote
Author: hiteshbandhu

Learn Summit 2023 Remote

Applies AI Engineer Summit 2023 remote-talk playbooks for evals, hybrid RAG grounding, model selection, fine-tuning, prompt ops, multimodal apps, coding-agent maturity, and career transition from fullstack. Use when reproducing summit remote lessons, comparing LLM eval tools, or scoping hybrid retrieval; or when the user says "summit 2023 remote", "llmeval", "hybrid context query", "AI maturity model".

hiteshbandhu Updated Sep 17, 2026

File contents

Learn Summit 2023 remote talks

Action playbook from eleven remote sessions at AI Engineer Summit 2023. Do not summarize talks — pick a workflow and execute it.

Supporting files:

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

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

Step 0 — Pick workflow

What is the user trying to do?
├─ Ship LLM evals in production (LLMeval)                    → A  [src-001]
├─ Hybrid context query / RAG grounding                    → B  [src-002]
├─ Viral AI app / codegen product (10k apps)               → C  [src-003]
├─ Career path: fullstack → AI engineer                    → D  [src-004]
├─ Pick the right model for a use case                     → E  [src-005]
├─ No-code / low-friction fine-tuning                        → F  [src-006]
├─ Prompt engineering tactics + prompt management            → G  [src-007]
├─ Multimodal TS apps (ModelFusion)                          → H  [src-008]
├─ Code AI maturity model (SAE levels)                       → I  [src-009]
├─ AI software engineer stack (embeddings, retrieval)        → J  [src-010]
└─ Generative infinite game / creative AI loops              → K  [src-011]

Open the matching section in workflows.md.

Install

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

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

Cross-cutting rules

Rule	Source
Store prompts/configs; eval before fine-tune	[src-001 @ 0:00:53]
RAG needs deliberate pipeline, not naive retrieval	[src-002 @ 0:01:26]
Model choice is use-case specific, not one-size	[src-005 @ 0:00:45]
Prompt engineering ≠ prompt hoarding — use tooling	[src-007 @ 0:00:18]
Maturity model: partial → supervised agent autonomy	[src-009 @ 0:04:04]

Output to user

Name workflow (A–K) and deliverable
Artifacts under ./skill-outputs/learn-summit-2023-remote/ when requested

Invocation examples

@learn-summit-2023-remote set up evals like the LLMeval talk
hybrid grounding query design for our copilot
which workshop path for fullstack → AI engineer?

---name: learn-summit-2023-remotedescription: Applies AI Engineer Summit 2023 remote-talk playbooks for evals, hybrid RAG grounding, model selection, fine-tuning, prompt ops, multimodal apps, coding-agent maturity, and career transition from fullstack. Use when reproducing summit remote lessons, comparing LLM eval tools, or scoping hybrid retrieval; or when the user says "summit 2023 remote", "llmeval", "hybrid context query", "AI maturity model".---# Learn Summit 2023 remote talksAction playbook from eleven remote sessions at AI Engineer Summit 2023. **Do not summarize talks** — pick a workflow and execute it.**Supporting files:**- [workflows.md](workflows.md) — workflows A–K- [source-index.md](source-index.md) — src-NNN → learningsOptional deliverables: `{SKILL_OUTPUT_DIR}/learn-summit-2023-remote/`---## Step 0 — Pick workflow```What is the user trying to do?├─ Ship LLM evals in production (LLMeval) → A [src-001]├─ Hybrid context query / RAG grounding → B [src-002]├─ Viral AI app / codegen product (10k apps) → C [src-003]├─ Career path: fullstack → AI engineer → D [src-004]├─ Pick the right model for a use case → E [src-005]├─ No-code / low-friction fine-tuning → F [src-006]├─ Prompt engineering tactics + prompt management → G [src-007]├─ Multimodal TS apps (ModelFusion) → H [src-008]├─ Code AI maturity model (SAE levels) → I [src-009]├─ AI software engineer stack (embeddings, retrieval) → J [src-010]└─ Generative infinite game / creative AI loops → K [src-011]```Open the matching section in [workflows.md](workflows.md).---## Install```bashcp -r skills/learn-summit-2023-remote ~/.claude/skills/cp -r skills/learn-summit-2023-remote ~/.cursor/skills/```Source: `playlists/ai-engineer-summit-2023-remote-talks/`.---## Cross-cutting rules| Rule | Source ||------|--------|| Store prompts/configs; eval before fine-tune | [src-001 @ 0:00:53] || RAG needs deliberate pipeline, not naive retrieval | [src-002 @ 0:01:26] || Model choice is use-case specific, not one-size | [src-005 @ 0:00:45] || Prompt engineering ≠ prompt hoarding — use tooling | [src-007 @ 0:00:18] || Maturity model: partial → supervised agent autonomy | [src-009 @ 0:04:04] |---## Output to user1. Name workflow (A–K) and deliverable2. Artifacts under `./skill-outputs/learn-summit-2023-remote/` when requested---## Invocation examples```@learn-summit-2023-remote set up evals like the LLMeval talkhybrid grounding query design for our copilotwhich workshop path for fullstack → AI engineer?```

Frequently asked questions