Tim Kersey tkersey

Deep Analysis: OpenAI Agents Python SDK

Based on my comprehensive exploration of the codebase, here's how this SDK handles multi-agent systems:

1. Agent Composition Patterns

The SDK supports several powerful composition patterns:

a) Handoffs (Agent-to-Agent Delegation)

Agents can transfer control to other agents through the handoffs mechanism

The Ultimate Swift Testing Playbook (2024 WWDC Edition, expanded with Apple docs from June 2025)

Updated with info from https://developer.apple.com/documentation/testing fetched via Firecrawl on June 7, 2025.

See also my blog: See also my blog post: https://steipete.me/posts/2025/migrating-700-tests-to-swift-testing

A hands-on, comprehensive guide for migrating from XCTest to Swift Testing and mastering the new framework. This playbook integrates the latest patterns and best practices from WWDC 2024 and official Apple documentation to make your tests more powerful, expressive, and maintainable.

1. Migration & Tooling Baseline

MCP's client-server architecture: Technical design for AI integration

The Model Context Protocol (MCP) represents a fundamental shift in how AI applications connect to external systems. Introduced by Anthropic in November 2024, MCP chose a client-server architecture over alternatives like peer-to-peer or monolithic designs to solve the "M×N problem" - where M AI applications need to integrate with N data sources, traditionally requiring M×N custom integrations. The client-server model transforms this into an M+N solution through standardized, secure, and scalable connections.

This architectural decision reflects deep technical considerations: security isolation between components, modular extensibility for diverse integrations, and protocol standardization that enables any MCP client to work with any MCP server regardless of implementation language or platform. The design philosophy prioritizes developer simplicity while maintaining enterprise-grade security boundaries - what Anthropic calls "

Rules

Follow the Unison Programming Language Guide

Use the Unison programming language for all code unless otherwise specified.

Use the following procedure to assist me with writing code.

Step 1, before writing any code: confirm types and signatures

What is your setup?

Just chat.deepseek.com with prompts adapted from this gist.

Does it work in one-shot or I have to prompt it multiple times?

For the qX_0 variants, they are actually quite straight-forward so deepseek can come up with a correct result in 1 shot.
For the qX_K it's more complicated, I would say most of the time I need to re-prompt it 4 to 8 more times.
The most difficult was q6_K, the code never works until I ask it to only optimize one specific part, while leaving the rest intact (so it does not mess up everything)

	// ---------- Mockingbirds and Why Birds with Higher-Kinded Types ----------
	//
	// The nicknames "Mockingbird" and "WHy Bird" are derived from "To Mock a
	// Mockingbird" by Raymond Smullyan.
	//
	// requires https://github.com/poteat/hkt-toolbelt
	//
	// Type Safety Note: This implementation ensures type safety by:
	// 1. Constraining HigherOrderKind's return type R to extend Kind.Kind
	// 2. Making _$Maker track precise type relationships with conditional types

	// ---------- Mockingbirds and Why Birds with Higher-Kinded Types ----------
	//
	// The nicknames "Mockingbird" and "Why Bird" are derived from "To Mock a
	// Mockingbird" by Raymond Smullyan.
	//
	// requires https://github.com/poteat/hkt-toolbelt

	import { Kind, $, $$ } from "hkt-toolbelt";
	import { _$inputOf } from "hkt-toolbelt/kind";
	import { _$cast } from "hkt-toolbelt/type";

	import {
	Operation,
	Resource,
	Context,
	action,
	resource,
	spawn,
	sleep,
	main,
	suspend as effectionSuspend,

	// Deep Dive: Prompts as Delimited Continuations in TypeScript

	// =============================================================================
	// 1. PROMPTS AS INITIAL CONTINUATIONS
	// =============================================================================

	/**
	* Prompts as Initial Continuations treats the prompt itself as the starting
	* continuation that establishes the computational context. The prompt becomes
	* a first-class continuation that can be captured, modified, and resumed.

	import Foundation
	import SwiftUI

	extension View {
	/// Adds introspection to find the parent view controller in the view hierarchy and
	/// makes that view controller available to downstream views in the view hierarchy.
	public func addParentViewControllerIntrospection() -> some View {
	modifier(ParentViewControllerEnvironmentModifier())
	}
	}