🤖 AI Engineer
AI Engineer conference talks, workshops, and panels. Frontier labs, agents, RAG, evals, the AI engineering toolchain.
Topics
🤖 Agents 175
LLM agents that plan, call tools, and act in loops. LangGraph, CrewAI, AutoGen, custom orchestration, multi-agent systems, agent reliability.
💻 Code Generation 130
AI coding tools and agents. Cursor, Devin, Copilot internals, SWE-bench, agentic refactoring, repo-scale understanding.
📐 Evals 105
How to actually measure LLM and agent quality — golden sets, LLM-as-judge, regression gates, production tracing, observability.
💼 AI Business 86
Going to market with AI. Pricing, GTM, build-vs-buy, moats, enterprise adoption, vertical agents, ROI stories.
🏗️ AI Infrastructure 83
GPU clusters, training stacks, autoscaling inference, data pipelines, feature stores, observability for AI workloads.
🔎 RAG 66
Retrieval-augmented generation — chunking, embeddings, hybrid search, rerankers, citation, evaluation. The dominant pattern for grounding LLMs in private data.
💬 LLM Apps 64
End-to-end LLM-powered applications. Prompt + context plumbing, structured outputs, retry & repair, user feedback loops.
✨ Product & UX 55
Designing AI features users actually want. Latency, trust, streaming, citations, undo, the "AI moment" in a product.
🛡️ Safety & Alignment 45
Prompt injection defenses, jailbreak resistance, hallucination mitigation, PII handling, red-teaming, responsible scaling.
🧠 Foundation Models 43
Frontier LLM training, architecture choices, scaling, post-training (SFT/RLHF/DPO), evaluation, releases from OpenAI, Anthropic, Google, Meta, Mistral, etc.
⚡ Inference & Serving 43
Throughput and latency engineering. Continuous batching, paged attention, quantization, speculative decoding, vLLM/TensorRT/SGLang.
🔌 MCP 42
Model Context Protocol — how clients (Claude, Cursor, IDEs) connect to servers that expose tools, resources, and prompts.
🎙️ Voice 35
Real-time voice AI. ASR (Whisper), TTS, turn detection, latency, voice agents for phones, support, accessibility.
🛠️ Tools & Frameworks 31
The AI engineering toolchain — LangChain, LlamaIndex, DSPy, LangGraph, LangSmith, Braintrust, Inspect, AGENTS.md.
🎨 Multimodal 31
Vision-language models, video understanding, image generation, multimodal agents. GPT-4V, Claude vision, Gemini, open-source VLMs.
🎯 Fine-Tuning 28
Adapting pre-trained models — full SFT, LoRA/QLoRA, DPO, preference tuning. When fine-tuning beats prompting + RAG.
✏️ Prompt Engineering 14
Prompting patterns — few-shot, chain-of-thought, ReAct, structured output, prompt management at scale.
🔬 Research 13
Frontier research talks — new architectures, training techniques, theoretical insights, paper deep-dives.
📦 Misc 8
Talks that span multiple themes, panels, opening keynotes, and general AI Engineer content.
🧮 Embeddings & Vector DBs 7
Embedding models, chunking, hybrid retrieval, vector store choice (Pinecone, Qdrant, Weaviate, pgvector), reranking.