🤖 Generative Programmer | Issue #6
Your weekly dose of developer-focused AI news
📣 After a bit of a break, welcome back to Generative Programmer! This week we dive deep into AI agents, from design patterns to enterprise applications, while examining how these developments are reshaping software careers and development practices.
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This week in Generative Programmer
AI Agents: From Design Patterns to Enterprise Reality 🤖
Google’s whitepaper Explains Agent Tools, Extensions, and Datastores 📘
Gartner's Research: Emerging Patterns for LLM-Based Agents 🔍
Acceptance Testing: The Future of AI Programming 🧪
GitIngest: Making Codebases LLM-Friendly ❤️
more updates here 👇
🎯 Featured Article
AI Agents and Agentic Reasoning - Andrew Ng argues that while everyone focuses on foundation models, the real opportunity lies in agentic AI workflows. He covers four key design patterns reshaping development:
Reflection - Enabling AI to critique and improve its own output
Tool Use - Allowing models to make API calls and access external tools
Planning - Breaking complex tasks into sequential steps
Multi-Agent Collaboration - Having specialized agents work together on tasks
The results are compelling - using agentic patterns with GPT-3.5 outperformed GPT-4 in coding tasks (95% vs 67% success rate).
As part of his keynote, Andrew Ng also covers 4 key trends that will be shaping AI. Watch his full keynote here to learn more about where AI is heading.
📰 Long-Form Reads
Understanding AI Agents: Google's Practical Guide - Google's whitepaper breaks down the foundational concepts of AI agents, focusing on how tools, extensions, and datastores work together to enable human-like problem solving. Must-read for anyone implementing agent architectures.
Future-proofing Your Software Engineering Career - Pragmatic analysis of how AI is reshaping software development careers with concrete strategies for staying relevant.
Reimagining automation with Business Process Agentification - Fresh perspective on how AI agents are revolutionizing business processes, moving beyond traditional workflows to autonomous, adaptive systems.
AI Agents in the Enterprise: Bridging the Gap - NVP's analysis cuts through the hype to examine what's actually possible with agentic AI today and where these systems deliver real business value.
The 4 Advanced RAG Algorithms You Must Know - Technical deep-dive into cutting-edge RAG implementations, covering hybrid search, multi-query expansion, and recursive retrieval approaches.
Multi-Agent Workflows: What Are They? - Temporal's practical guide to implementing multi-agent architectures with concrete examples of orchestrating complex agent interactions.
Task Framing: No Need to Beg! - Insightful piece on structuring LLM prompts effectively, moving beyond simplistic approaches to robust, constraint-based definitions.
2024: State of Generative AI in Enterprise - Survey of 600 enterprise IT decision-makers reveals which AI implementations are delivering value versus those stuck in pilot phase.
Agile in the Age of AI - Henrik Kniberg examines how AI is forcing us to rethink fundamental Agile practices around team structure and development velocity.
Agentic AI Explained - Technical breakdown of how AI agents differ from traditional automation, with practical insights on combining LLMs with RAG.
🎙️ YouTube & Podcasts
Acceptance Testing Is the FUTURE of Programming - Dave Farley explores how acceptance tests can guide AI code generation more reliably than natural language prompts, with practical experiments in AI-assisted development.
Supercharging Developer Productivity with ChatGPT and Claude - Simon Willison shares practical workflows and techniques for leveraging LLMs in daily development, including prompting strategies and rapid prototyping.
Lovable.dev + Supabase Full Stack App in 5 Messages - Hands-on building a full-stack app with authentication and database using Lovable.dev
Building Large Language Models - Stanford CS229 lecture by Yann Dubois covering practical aspects of building ChatGPT-like models, from pretraining to RLHF.
I Paid $500 For Devin And Found Critical Security Issues - A skeptical analysis of Devin AI's capabilities and limitations.
🗞️ News and Updates
Emerging Patterns for Building LLM-Based AI Agents - Gartner VP Gary Olliffe's fresh analysis reveals that while AI agents are still mostly in POC phase, they're becoming a significant focus for technical leaders. His research outlines emerging patterns across frameworks like CrewAI, LangChain, and Microsoft's AutoGen, highlighting both opportunities and implementation challenges.
Lovable's Mindblowing Growth Story - The AI app generator reaches $4M ARR in just 4 weeks, demonstrating unprecedented growth for a European startup.
🛠️ Tech & Tools
Building Effective Agents Cookbook - Anthropic's reference implementations for common agent patterns, including prompt chaining, routing, and multi-LLM parallelization with practical examples.
GitIngest - Clever tool that converts any Git repository into LLM-friendly format, with built-in token counting and smart formatting. My life-saver this week!
Swark - VS Code extension leveraging GitHub Copilot to automatically generate architecture diagrams from your codebase.
OpenHands - Open source alternative to Devin, it can modify code, run commands, and interact with external services.
📚 Learning Picks
AI Agentic Design Patterns with AutoGen - A course by Chi Wang and Qingyun Wu teaching practical patterns for building multi-agent systems using Microsoft's AutoGen framework.
Multi AI Agent Systems with crewAI - Comprehensive course by João Moura on designing and orchestrating AI agent teams, with hands-on examples with CrewAI
🎭 AI Humor
Even GPT-9 Can't Figure Out Jira -
👋 See You Next Week
Thanks for reading Prompt Patterns 🙏
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Have a great rest of the week 😉