Building Local AI Agents from Scratch: A Developer's Guide Using Ollama

PLUS - AI Engineering Deep Dive: Chip Huyen on Fine-tuning, Evaluations, and Practical Implementation

DevThink.AI

Essential AI Content for Software Devs, Minus the Hype

As local AI capabilities expand, this edition spotlights a significant shift in development patterns. From Ollama's growing ecosystem to SmolVLM2's iPhone-ready models, running sophisticated AI locally is becoming not just possible, but practical. We explore multiple approaches—whether you're building AI agents without cloud dependencies, running chat applications across platforms, or leveraging mobile-first development tools.

Beyond local innovations, we've curated insights from industry leaders like Chip Huyen, alongside announcements such as Meta's first LlamaCon. This mix of practical tutorials, tool announcements, and strategic analysis aims to keep you ahead of AI's rapid evolution in software development.

Let's dive in 📰 

In this edition

📖 TUTORIALS & CASE STUDIES

A Senior Developer's Proven Workflow for LLM-Assisted Code Generation

Estimated read time: 15 min

Harper Reed shares their practical workflow for leveraging LLMs in both greenfield and legacy projects. The process covers spec development, structured planning, and execution using tools like Aider and Claude, with specific techniques for maintaining control and avoiding common pitfalls.

Run LLMs Locally: A Developer's Guide to Building AI Apps with Ollama on Mac

Estimated read time: 14 minutes

Simple local app to rename PDF files based on their contents

A hands-on guide to building AI applications with Ollama on Mac. The article demonstrates text generation, chat completions, and RAG system implementations. For teams prioritizing data privacy and cost reduction, Ollama provides a robust local-first solution.

SmolVLM2: Efficient Video Understanding Models That Can Run on Your iPhone

Estimated read time: 12 min

Hugging Face releases SmolVLM2, ranging from 256M to 2.2B parameters, designed to run locally on mobile devices. The release includes Python and Swift APIs, plus integration options for VLC media player and transformers library, bringing advanced video AI capabilities to mobile applications.

Building Local AI Agents from Scratch: A Developer's Guide Using Ollama

Estimated read time: 12 minutes

Continuing on the run local theme, this step-by-step guide demonstrates how to create AI agents using Ollama, without GPU requirements or API keys. It covers web search implementation and code execution functions, providing a foundation for both basic and advanced agent development while maintaining local control.

🧰 TOOLS

Mastra: A New TypeScript Framework for Building Production-Ready AI Agents

Estimated read time: 8 min

The Gatsby team introduces Mastra, a TypeScript framework for AI agent development and deployment. It features unified vector store integration, workflow orchestration, and RAG capabilities, along with agent memory management and performance metrics.

Warp CEO Reveals How AI Is Transforming the Command Line Interface

Listen time: 47 min

A candid conversation with Warp CEO Zach Lloyd discussing the future of AI-enhanced terminals. The conversation examines command-line automation, security considerations, and practical approaches to building AI-powered developer tools.

OllamaTalk: A Cross-Platform App for Running Local LLM Chats Without Cloud Dependencies

Estimated read time: 8 min

OllamaTalk enables offline AI chat capabilities across desktop and mobile platforms. Built for developers prioritizing security, it uses Ollama to run LLMs locally without cloud service requirements.

Replit Launches Mobile-First AI Agent for App Development: Build and Deploy Apps from Your Phone

Estimated read time: 4 min

Replit releases an AI agent for iOS and Android that enables mobile app development through natural language prompts. Developers can create, host, and share remixable applications directly from their phones, streamlining development through AI assistance.

 

📰 NEWS & EDITORIALS

LLM Reasoning in Software Development: Valuable Tool or Overhyped Feature?

Estimated read time: 10 min

In this thoughtful analysis, Thoughtworks' Birgitta Böckeler examines the role of LLM reasoning capabilities in software development tasks. She explores the limitations of reasoning models like OpenAI's o1 and DeepSeek's R1, particularly in debugging and implementation planning, while questioning whether specialized coding models might be more effective for most development tasks.

AI Engineering Deep Dive: Chip Huyen on Fine-tuning, Evaluations, and Practical Implementation

Listen time: 1 hr 15 min

Stanford instructor Chip Huyen shares key insights on implementing AI solutions. She challenges common assumptions about fine-tuning, discusses LLM evaluation methods, and emphasizes user-centric development over technical complexity.

DeepSeek AI Announces Open-Source Infrastructure Release Week: 5 Production-Tested Tools Coming Soon

Estimated read time: 4 min

DeepSeek AI's 202502 Open-Source Week will release five battle-tested infrastructure repositories. This initiative shares key components from their AI services, supporting transparent and community-driven development.

Europe Launches Major Open-Source LLM Initiative to Compete with Global AI Leaders

Estimated read time: 4 min

Twenty European organizations launch OpenEuroLLM to develop multilingual models for commercial and public services. The project aims to democratize AI access while ensuring European regulatory compliance, enabling region-specific AI application development.

Meta Announces First-Ever LlamaCon Developer Conference and Connect 2025 Dates

Estimated read time: 3 min

Meta sets dates for their inaugural LlamaCon developer conference on April 29, 2025, focusing on open-source AI developments. Meta Connect follows September 17-18, featuring updates on Meta Horizon, XR development tools, and emerging technologies.

Anthropic's New Hybrid AI Model to Offer Developers Control Over Speed vs Reasoning Tradeoffs

Estimated read time: 4 min

Anthropic prepares to release a hybrid AI model featuring adjustable performance settings. The model includes a variable scale for controlling computational costs, with early tests showing strong performance against OpenAI's o3-mini-high in programming tasks.

 

Thanks for reading, and we will see you next time

Follow me on LinkedIn or Threads