OpenAI for Devs: Cheat Sheet
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🌟 OpenAI for Devs - CHEAT SHEET
(All factual • SWE-I friendly • sorted from least 🤖 to most 🤖🤖🤖 work)
📚 Table 1 — Docs Topics (least AI → most AI)
| ⭐ Rank | 📂 Topic Group | 🎯 SWE-Simple Meaning | 💫 Key Sub-Topics | 🤖 AI-Level |
|---|---|---|---|---|
| 1 | Getting Started | First API call, set key, pick model, check cost | Overview, Quickstart, Libraries, Pricing, Models | ⭐ |
| 2 | Core Features | Ask model to 📝 write, 🖼️ draw, 🗣️ talk, or return JSON | Text gen, Images & vision, Audio, Structured output | ⭐⭐ |
| 3 | Run & Scale | Make it real-time, stream tokens, store chat, handle webhooks | Streaming, Conv. state, Webhooks, Background mode | ⭐⭐ |
| 4 | Prompting & Reasoning | Craft better instructions / schemas | Prompting guides, Reasoning tips | ⭐⭐⭐ |
| 5 | Tools & Connectors | Give GPT extra powers (search web, run code, read files) | Code interpreter, Web search, File search, MCP | ⭐⭐⭐ |
| 6 | Realtime / Voice | Low-latency chat & voice agents | Realtime API, Voice agents | ⭐⭐⭐⭐ |
| 7 | Agents SDK | Multi-step assistants that choose tools | Agents SDK (Py/TS), Assistants API | ⭐⭐⭐⭐ |
| 8 | Specialised Models | Embeddings for search, Moderation for safety, TTS/STT, Image gen | Embeddings, Moderation, Image gen, Speech APIs | ⭐⭐⭐⭐ |
| 9 | Optimisation | Fine-tune, run evals & graders, cut cost/lag | Fine-tuning, Evals, Graders, Opt. cycle | ⭐⭐⭐⭐⭐ |
| 10 | Coding Agents / Deep | AI that writes & runs code, advanced research | Codex cloud/CLI/IDE, Local shell, Deep research | 🌟 ultra |
💼 Table 2 — Jobs / Roles (least 🤖 → most 🤖)
| # | 👔 Role | 🛠️ Daily Focus | 📑 Must-Read Topics (Tbl 1) | 🤖-Stars |
|---|---|---|---|---|
| 1 | Backend / API Integrator | Call API, retry, log cost | 1 + 3 | ⭐ |
| 2 | Front- / Full-Stack Dev | Add chat / image / speech widgets | 1 + 2 + 3 | ⭐⭐ |
| 3 | DevOps / Platform Eng. | Deploy & monitor GPT workloads | 3 + 9 | ⭐⭐ |
| 4 | Prompt / Workflow Eng. | Write prompts & JSON schemas | 4 | ⭐⭐⭐ |
| 5 | AI Integration Eng. | Chain tools (file/web/search) | 3 + 5 | ⭐⭐⭐ |
| 6 | Conversational / Voice Dev | Build chat or voice assistants | 3 + 6 + 7 | ⭐⭐⭐⭐ |
| 7 | RAG / Embedding Eng. | Retrieval-Augmented Generation pipelines | 5 + 8 | ⭐⭐⭐⭐ |
| 8 | ML / Fine-Tuning Eng. | Fine-tune, eval, cost/latency tune | 8 + 9 | ⭐⭐⭐⭐⭐ |
| 9 | Agent / Coding-Agent Eng. | Multi-tool autonomous agents, AI coding tools | 5 + 7 + 10 | ⭐⭐⭐⭐⭐ |
| 10 | AI Research Eng. | Novel model/agent research & safety | 8 + 9 + 10 | 🌟 ultra |
🛠️ Table 3 — How Normal Devs Get Started
| 👥 Role | 💻 Language(s) | 🔧 3-Step Quick Start | 📋 Pre-reqs | 🎯 First Mini-Project |
|---|---|---|---|---|
| Front-end Dev | JS/TS (UI) + small Node/Python proxy | 1️⃣ npm i openai on server 2️⃣ Create /api/chat endpoint 3️⃣ Stream to React/Vue | JS fetch, env vars | Live chat widget w/ streaming |
| Back-end Dev | Python or Node (pick one) | 1️⃣ pip install openai⬆️ or ⬇️ npm i openai 2️⃣ Choose model, log tokens 3️⃣ Build /generate route | REST basics, env vars | “Summarise PDF” API using File inputs |
| Full-stack Dev | Python or JS/TS (both not required) | 1️⃣ Finish Quickstart 2️⃣ Add Function Calling 3️⃣ Add Embeddings + File retrieval | Same as above + small DB | “Chat with Docs” (upload → embed → answer) |
Language FAQ ☑️ Either Python or JS/TS is fine. ☑️ Use what your stack already uses; SDKs exist for both. 🔒 Never expose API keys in browser code—hit a backend route instead.
📐 Table 4 — Prerequisites & Next Steps
| 📏 Area | ✅ Must-Know | 🍃 Nice-to-Have | ⏭️ Next / Latest | Why Care? |
|---|---|---|---|---|
| API Basics | HTTP, JSON, env-vars | Streaming (SSE) | Responses API patterns | Clean, future-proof calls |
| Backend Ops | Error handling, retries | Queues, webhooks | Conv. state, cost logging | Reliability & spend control |
| Data / RAG | Vector concept, a vector DB | Chunking, metadata | File search & connectors | Grounded, factual answers |
| Prompting | System vs. user prompts | Few-shot examples | Reasoning chains, JSON schemas | Accuracy & parseability |
| Quality / Safety | Moderation endpoint | Eval sets, graders | Fine-tuning, optimisation cycle | Safer, measurable outputs |
| Realtime / Voice | WebSocket/WebRTC basics | Audio codecs | Realtime API + Voice agents | Low-latency voice apps |
🚀 Climb the Ladder
- ⭐ Week 1 — Quickstart call in your main language.
- ⭐⭐ Week 2 — Add streaming + basic UI.
- ⭐⭐⭐ Week 3 — Use Function Calling + JSON; start prompt tuning.
- ⭐⭐⭐⭐ Week 4–5 — Add Tools (file/web) or Agents SDK.
- ⭐⭐⭐⭐⭐ Beyond — Fine-tune, run evals, or build coding agents.
No ML PhD needed until step 5. Pick one language, follow the docs above, and you’re off! 🌐✨