Format: Technical talk with live demos, code and prompt examples

Description:

The role of the developer is fundamentally changing. We're moving from being executors who write every line of code to becoming orchestrators who conduct AI agents to build complex systems. This talk, based on my essay about transitioning from traditional coding to AI orchestration, shares practical insights from a year of experimenting with multi-agent development workflows. 🔗 Essay linked here: https://pivotech.substack.com/p/from-executor-to-orchestrator-my

Through real code examples and live demonstrations, I'll walk through my evolution from using ChatGPT for learning CS50 concepts to orchestrating Claude, Gemini CLI, and NotebookLM to build complete products. You'll discover the three distinct schools of AI development I've identified through hands-on experimentation: the One-Shot method, the Incremental approach, and my hybrid Layering technique.

I'll share the workflows I use to go from customer discovery sessions to deployed applications, including the mistakes, frustrations, and breakthroughs that shaped my approach. We'll explore the "Legacy Codebase Problem" that emerges from AI-generated code, the "Hyper-specificity Paradox" of detailed prompting, and the new skill set required to become an effective AI orchestrator.

Key Takeaways:

Three proven patterns for AI-assisted development and when to use each

Practical orchestration workflows for complex projects

The emerging skillset of the developer-orchestrator

How to maintain technical depth while leveraging AI efficiency

Real-world pitfalls and how to navigate them

Target Audience: Developers looking to evolve their practice in the age of intelligent agents. Minimal level of AI development experience required e.g. prompting Claude

What happens when you need to refactor 377 files in a SvelteKit codebase? Without AI, you retire. With Claude Code, you ship it in 11 hours.

This talk walks through real-world examples of using Claude Code for massive refactoring work that would be soul-crushing to do manually. I'll cover:

How I approach large-scale refactors with Claude (377 files → 364 files → and counting)

Building and activating Claude Code skills reliably (based on my viral post that's getting 4k+ views in 3 days)

The workflow patterns that actually work vs the ones that waste your time

Real examples from production codebases

This isn't about AI replacing developers - it's about using AI to handle the tedious parts so you can focus on the interesting problems.

Recently I have been building Menagerie a tool for dispatching many Claude Code agents to complete tasks in parallel while maintaining visibility of progress, status and outputs. agents can show you what they are doing to the web app via playwright and ask for help when the need it.

I think the future of engineering will be based on creating robust agentic systems and amid all the doom and gloom that can exist in the industry these days I want to paint a positive picture of the exciting engineering problems that actually lay ahead of us.

Along with this I'll describe what it has taken me to deploy a system like this, e.g. sandboxing, cursor compatibility, terminals over the network and also how i've made it fun to use (for example you can give your agent a cute avatar, and if you so choose also a top hat)

AI agents are everywhere, but how do you go from demo to dependable? In this talk, we’ll build agents using LangGraph, and take it beyond toy examples into enterprise-grade readiness.

We’ll start with context engineering concepts like: control flow, prompt engineering, prompt management and tool calling. From there, we’ll build an agent step-by-step, enabling contextual reasoning via Retrieval-Augmented Generation (RAG), and integrating tool use for dynamic task execution. We'll also cover agent observability with open source observability tools such as LangFuse to bring full observability into the decision our agents make.

Whether you're exploring AI agents or planning your first production deployment, you'll leave this session with the patterns, tools, and clarity to do it right.