Prompt Engineering Conference 2023
as the organisers put it
The conference will showcase a comprehensive range of topics, including theoretical foundations of prompt engineering, prompt generation methodologies, practical strategies for prompts optimizing, fine-tuning strategies, bias mitigation, innovative techniques, and many more.
| title | author | length |
|---|---|---|
| Opening | Maxim Salnikov, Erich Hellstrom, Dan Cleary, Goda Go, Wes Shields | 09m |
Organizers claim emerging discipline status for prompt engineering and position it as a potential separate profession, backed by a live, multi‑continent… | ||
| Democratising learning of AI - experiences from the University of Oxford | Ajit Jaokar | 25m |
Oxford runs a course that teaches non-developers to build ML and generative apps using chatGPT GitHub Copilot Power Platform Code Interpreter, and reports full… | ||
| Prompt Based Recommendation Systems: A New Era of Personalized Experiences | Rohan Singh Rajput | 25m |
LLM models like GPT-4 and seq2seq frameworks such as P5 treat recommendation as top-k prediction and explanation generation, producing next-item suggestions… | ||
| Generated Cities and Architecture | Ayse Glass | 09m |
A research project called DaFne defines 10 use cases and a six step pipeline from challenge identification to validating synthetic data for city design. A tool… | ||
| Q&A #1 | Ajit Jaokar, Rohan Singh Rajput, Ayse Glass | 25m |
Six-step design workflow becomes concrete: prompts break problems into substeps and can spawn autonomous AI agents that book holidays or assemble multi-step… | ||
| Better Prompting with Pseudocode | Eric Elliott | 24m |
Pseudocode prompting with SudoLang and GPT‑3/4 yields concrete gains: prompts convert to runnable specifications, generate unit tests and transpile to… | ||
| Semantic Kernel: Teaching AI to Not Just Repeat, But Complete! | Rory Preddy | 26m |
Shows a concrete pipeline that uses Semantic Kernel plus the RAG pattern and Azure OpenAI to daisy‑chain small skills into goal‑oriented programs. Demonstrates… | ||
| Rapid Prototyping with AI | Eric Allen | 10m |
A prototype D&D assistant gets built in TypeScript using local tooling: olama hosts a quantized orca mini 7B V3 (runs on a 2012 MacBook Pro), Chroma serves as… | ||
| Q&A #2 | Rory Preddy, Eric Allen | 27m |
Demos show a local stack: a local LLM plus Chroma vector DB running locally on MacBook Pro and orchestration via semantic kernel; an accessibility coaching app… | ||
| Building complex data visualisations using ChatGPT | Greg Nash | 35m |
Uses ChatGPT plus Vega-Lite inside Power BI via Deneb to generate JSON specs iteratively, turning raw daily temperature and rainfall tables into a layered… | ||
| The Power of Prompting: Rocket Fuel for People w/ a Growth Mindset; Here's the Proof! | Jan Krans | 10m |
An experiment proves prompting turns ideas into products: using ChatGPT to generate 52 card descriptions, Midjourney to create card art, a macro to… | ||
| How can you use prompt engineering to debug PowerShell? | Alexander Holmeset | 10m |
Uses Azure OpenAI Studio and the gpt-4-32k model to debug real PowerShell snippets: finds a typo that prevents a users loop, explains using userPrincipalName… | ||
| Q&A #3 | Greg Nash, Jan Krans, Alexander Holmeset | 31m |
A Q&A covers concrete takeaways: a working Azure OpenAI + Teams chatbot that queries internal SharePoint HR docs, advice to keep company data in Azure for… | ||
| Navigating the Evolution of Prompt Engineering | Stephen Perin | 22m |
Argues that prompt engineering behaves like a flow system and proposes using Constructal Theory to explain why prompting patterns evolve from zero‑shot to… | ||
| The Dawn Of Universal Creativity | Jesus Serrano | 33m |
Claims that AI bridges the skills and resources gap and acts as an exponential talent multiplier, with a concrete workflow: ideation via chat, fine‑tuning GPT… | ||
| Whose Intellectual Property is Prompt Engineering? | Anand Kulkarni | 10m |
Argues that individual prompts can be copyrightable prompts like code or scripts, while pure prompt engineering is usually not patentable but can be part of a… | ||
| Q&A #4 | Stephen Perin, Jesus Serrano, Anand Kulkarni | 27m |
Panel answers focus on concrete practice: prompt formats evolve to include comments and embedded code, workflows stitch many specialized tools together with… | ||
| Intro to Fine-tuning | Mark Henning | 19m |
Explains fine-tuning as supervised transfer learning and shows a no-code product, Entry Point AI, that turns CSVs into fielded templates, synthesizes training… | ||
| How prompt engineering projects change R&D cycle & team work in enterprise | Anastasia Podrabinek | 31m |
A practical playbook for embedding prompt work into product cycles: a Wix toolset for prompt engineering and test-driven approach that uses a test set of user… | ||
| Prompt Engineering a Product Manager | C Wen, Zhaohong Wang | 06m |
Claims a reproducible pipeline that reads thousands of tickets and outputs urgency, risk and missing fields; tools tested are OpenAI ChatGPT, Google PaLM API… | ||
| Q&A #5 | Mark Hennings, Anastasia Podrabinek | 29m |
Argues that prompt engineering starts prototypes while fine-tuning becomes best practice in production, with fine-tunes often needing 100–250 examples but… | ||
| Leveraging Prompt Engineering for Effective OpenAPI Descriptions of APIs | Daniel Kocot | 30m |
Uses ChatGPT and GitHub Copilot inside VS Code to generate developer personas, empathy maps and customer journeys, then auto-produces initial OpenAPI drafts… | ||
| Supercharge Your Productivity: Mastering Prompt Engineering | Jeroen Egelmeers | 29m |
A three‑phase method called Crafting AI Prompts Framework teaches exact prompt ingredients and workflows for ChatGPT and the OpenAI API, claiming measurable… | ||
| Prompting your next company strategy | Peter Kestenholz | 10m |
Live demo shows Azure OpenAI / ChatGPT (3.5 and GPT‑4 via Bing) and Microsoft Copilot integrated into a Power Apps + Dataverse + Power Automate flow that… | ||
| Q&A #6 | Daniel Kocot, Jeroen Egelmeers, Peter Kestenholz | 44m |
Demo shows a Power PPM app that calls GPT‑3.5 and GPT‑4 via Azure OpenAI to auto‑generate an OKR hierarchy (example: grow APAC online sales 20% with three key… | ||
| nothing matches | ||