📣 Welcome back! Here’s everything that happened this summer in agentic systems and AI-assisted coding, all in one post. 🔗 Share: X · LinkedIn · BlueSky · Email and let’s dive in.

🔥 Top Picks from Summer of 2025

📘 Agent Design Pattern Catalogue -Yue Liu 🔥
🧠 How to Fix Your Context – Drew Breunig
⚙️ AI Agent Workflow Design Patterns – Craig Li
🏗️ The Big LLM Architecture Comparison – Sebastian Raschka 🔥
💡 Why Applications & Pipelines Should Use DSPy – Drew Breunig
🛠️ AI Coding Tools Can Actually Reduce Productivity – Second Thoughts
🏢 Agentic AI Architecture Framework for Enterprises – InfoQ
⚡ Understanding the KV Cache in LLMs from Scratch – Sebastian Raschka
🎥 Mastering Claude Code in 30 minutes – Claude Code team
☠️ Replit goes rogue during a code freeze and deletes an entire prod database

…and if you dare, 100+ updates to explore 👇

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🎯 Featured Article

Agent Design Pattern Catalogue – Yue Liu and colleagues present 18 architectural patterns for building foundation model-based agents.

Agentic systems and architectural patterns ecosystems

The catalogue covers context, forces, and trade-offs in agent design, and introduces a decision model to help practitioners address challenges like hallucinations, explainability, and accountability. A comprehensive guide for anyone architecting agentic systems. 🔥

📰 Building Agentic Systems

How to Fix Your Context | Drew Breunig - Techniques for managing context in AI to avoid "garbage in, garbage out" problems.

Agentic Mesh for Regulatory Compliance: EU AI Act & DORA Integration

AI Agent Workflow Design Patterns - Craig Li introduces the implementation of an agent framework based on AI Agent Design Patterns while researching various workflow patterns that combine LLM reasoning capabilities, memory, and task execution.

Agentic Engineering in Action - Mitchell Hashimoto explains his AI-assisted development approach for Ghostty.

Context Engineering - What it is, and techniques to consider - A guide to providing AI agents with relevant context for effective task performance.

Pydantic Agents and Human-in-the-Loop - Lalit demonstrates how to build AI agents with PydanticAI that incorporate human feedback when faced with ambiguous situations, using a weather information system as a practical example.

Agents are not tools - Google Developer forums - This post examines the crucial distinction between agents and tools, highlighting how their different decision-making control flows require unique interaction approaches.

Understanding Tool Calling with Step-by-Step Examples in REST and Spring AI - Muthukumaran Navaneethakrishnan provides a comprehensive guide on implementing OpenAI-style tool calling in LLMs, with practical code examples in both REST and Spring AI, complete with diagrams and end-to-end implementation flows.

MCP vs. A2A: Friends or Foes? - Aurimas Griciūnas examines how Google's new A2A protocol competes with Anthropic's MCP in the race to establish standards for multi-agent AI system communication.

Agentic AI Architecture Framework for Enterprises - InfoQ - Enterprise framework for building autonomous AI systems that can plan and execute tasks independently.

Context Engineering: Bringing Engineering Discipline to Prompts - Osmani: Give AI complete context, not just clever prompts.

CodeAct - Apple researchers propose using executable Python code as a unified action space for LLM agents, enabling more flexible tool composition and dynamic action revision compared to traditional JSON or text-based formats.

The Open-Source Toolkit for Building AI Agents v2 - Updated toolkit overview for AI agent developers.

Context Is the New Compute: Designing the Future of Agentic - Gill: Context engineering replaces prompt engineering as AI agents grow more complex.

Context Engineering for AI Agents: Lessons from Building Manus - Manus team shares optimized principles for AI agent development based on their own experiences, offering valuable shortcuts for developers building similar systems.

Executable Code Actions Elicit Better LLM Agents - Xingyao Wang: Code-based actions enhance LLM agent effectiveness.

📰 Coding with AI

Leading your engineers towards an AI-assisted future - Pete Hodgson questions whether the team is leveraging AI coding tools enough.

Coding for the Future Agentic World - Addy Osmani examines how AI agents are transforming software development workflows.

Rethinking CLI interfaces for AI - CLI tools need AI-friendly redesigns to balance context windows and information needs.

Coding with LLMs in the summer of 2025 - Antirez: A forward-looking analysis of AI-assisted programming in 2025.

AI Coding Tools Can Actually Reduce Productivity - Study shows AI coding tools may hinder experienced developers' productivity.

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity - METR - Joel Becker's overview of the report.

Software engineering with LLMs in 2025: reality check - Gergely Orosz shares insights from discussions with engineers at leading AI companies about current AI tool usage patterns and emerging trends in software development.

LLMs bring new nature of abstraction - Martin Fowler: LLMs fundamentally change programming by introducing non-deterministic abstraction.

Vibe-Coding a PCB - surprisingly good - Chris Greening demonstrates how AI can successfully design functional hardware

Vibecoding a high performance system - AI-assisted development of a billion-page web crawler with minimal manual coding.

Leading your engineers towards an AI-assisted future | Pete Hodgson - A conversation about balancing AI hype with practical engineering value.

How to spot AI Generated Code - Brian White-Starrs on LinkedIn

From vibe coding to vibe planning - AI Native Dev's article examines a real-world incident where an AI coding assistant deleted a production database during "vibe coding," highlighting the dangers of unleashing AI on live codebases and Replit's subsequent response to improve safety.

Parallelizing AI Coding Agents | AI Native Dev - The author examines the evolution of AI coding from simple prompting to autonomous agents, highlighting how parallel agent architecture creates faster but more complex workflows similar to asynchronous programming models.

Coding agents have crossed a chasm

AI Agents, meet Test Driven Development - Applying TDD principles to AI agent development workflows.

Agentic Coding Recommendations - Armin Ronacher shares his practical workflow for agentic coding, detailing his preference for Claude Code with the Max subscription and how he optimizes for token efficiency while giving agents full permissions.

Learnings from two years of using AI tools for software engineering - Practical insights from a Thoughtworks engineer's two-year AI tools exploration.

📰 Long-Form Reads

You Got Commands in My Prompt! - Breunig: New Qwen 3 models let you control reasoning with simple prompt commands.

The Big LLM Architecture Comparison - Raschka analyzes LLM evolution: incremental tweaks or true innovation?

Why Applications & Pipelines Should Use DSPy - Breunig explains using DSPy to let models write their own prompts.

MCP market map - Finsweet examines how the Model Context Protocol (MCP) is evolving from a technical specification into a thriving ecosystem with commercial opportunities similar to the API economy, but accelerated by AI integration.

Building tiny AI tools for developer productivity - Title says it all

How has AI impacted engineering leadership in 2025? - Lizzie Matusov examines the 2025 Engineering Leadership Report which surveyed 617 engineering leaders

How Bolt hit 40M ARR in 5 months - Kyle Poyar: AI app builder goes from near-shutdown to $40M ARR overnight.

Your API might be someone else's model- CORS protects APIs from unauthorized use, similar to emerging AI model protection needs.

Autonomy Sliders - Andrew Miller examines the concept of autonomy sliders, likely discussing how to balance AI system independence with human oversight and control.

Seeing like an LLM - Krishnan compares LLM functionality to human learning and knowledge limitations.

MCP Authorization in 5 easy OAuth specs - WorkOS - OAuth standards for secure MCP authorization with LLMs.

Recovering from AI Addiction – Internet and Technology Addicts Anonymous - Stanford: A support community for overcoming technology addiction.

The Tiny Teams Playbook - by Shawn swyx Wang - Framework for building small, hyper-efficient AI-powered teams that prioritize efficiency over scale.

Do developers need to think less with AI? - Thoughtworks' author challenges the common assumption that AI tools require more developer thinking, not less.

Why Google's Agent2Agent Protocol Needs Apache Kafka - Kafka offers critical messaging capabilities for Google's multi-agent AI communication protocol.

Do Machine Learning Models Memorize or Generalize? - Explores how models transition from memorization to genuine understanding during extended training.

Phoenix.new is Fly's entry into the prompt-driven app development space - Fly.io launches tool that creates Phoenix apps from text prompts.

Researchers hide AI prompts in papers - Researchers caught hiding instructions for AI to give favorable paper reviews.

Experimenting with LLMs for semantic testing - Semantic testing validates content meaning beyond functional correctness.

Understanding and Coding the KV Cache in LLMs from Scratch - Sebastian Raschka breaks down KV caches: how they speed up LLM inference by storing key-value computations.

A Survey: 2025 AI Newsletters - Michael Spencer's extensive list of AI newsletters with upcoming LinkedIn influencer guide.

Death by a thousand slops - Daniel Stenberg: Curl project drowning in AI-generated vulnerability report spam.

Why I'm Betting Against AI Agents in 2025 (Despite Building Them) - Experienced agent builder explains why autonomous AI agents won't deliver on 2025 promises.

How to use AI to Optimize your Personal Life and Free Time - Daria Cupareanu: AI strategies for reclaiming time and enhancing personal life quality.

Leadership co-processing with LLMs - James Stanier discusses how LLMs are changing management roles and practices.

🎙️ YouTube & Podcasts

Andrej Karpathy: Software Is Changing (Again) - YouTube - Karpathy explores AI's revolutionary impact on software development paradigms. 🔥🔥🔥

Mastering Claude Code in 30 minutes - YouTube - Quick guide to Claude Code's advanced features and shortcuts. 🔥

Software engineering with LLMs in 2025: reality check - YouTube - The Pragmatic Engineer’s Gergely Orosz presents a comprehensive overview of how developers at AI startups and Big Tech companies are currently using AI tools, featuring projections about the future landscape of software engineering.

🗞️ News and Updates

Gergely Orosz's take on X - Being able to specify what software you want to build, how it should be structured, and how exactly it should work is... programming. And getting into the weeds, when needed.

Batch Mode in the Gemini API: Process more for less - New Gemini API feature offers discounted batch processing for non-urgent AI tasks.

Whats Your Best Advice For Using Claude Code [Reddit] - Reddit thread collecting Claude code usage tips.

10 Principles of Building AI Agents - Paweł Huryn on X

MCP Authorization specs - Christian Posta on X

OpenAI experiments with new "Study together" tool on ChatGPT - New ChatGPT feature creates interactive learning with step-by-step guidance.

AWS introduced Kiro on X -Introducing Kiro, an all-new agentic IDE that has a chance to transform how developers build software.

Replit goes rogue during a code freeze and shutdown and deletes our entire database

🛠️ Tech & Tools

Backlog.md - Git-based Markdown task manager with Kanban visualization.

install.md - Tools that help coding agents integrate various software components into codebases through MCP server technology.

Browserbase - A specialized web browser designed specifically for AI agents and applications to interact with web content.

spec-driven-agentic-development - A specification-based workflow for AI-assisted software development.

BrowserStack - AI-powered test case generation from requirements documents.

any-agent - mozilla-ai - A unified interface that allows developers to use and evaluate different AI agent frameworks through a single implementation.

📚 Learning Picks

Claude Code in Action - Skilljar hosts Anthropic course materials for organized, interactive learning.

ai-agents-for-beginners - Microsoft's beginner-friendly AI agent development curriculum with multilingual support.

🎭 AI Humor

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👋 See You Next Time

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