Series
AI Tools Mastery
An 18-part engineering deep dive into the most impactful AI tools of 2026. Each post follows the Problem → Investigation → Solution → Results → Trade-offs narrative, with hands-on code, architecture diagrams, cheat sheets, and course-style technical explanations.
ChatGPT: Building Production Apps with GPT-4o
How we built a document processing pipeline handling 10K+ pages daily using ChatGPT's API — with structured outputs, function calling, and streaming patterns.
Claude: Engineering with Long-Context LLMs
How we migrated from GPT-4 to Claude for code analysis — leveraging 200K token context windows, prompt caching, and multi-shot prompting to cut costs by 60%.
Gemini: Multi-Modal AI for Code and Beyond
Benchmarking Gemini 2.5 Pro against GPT-4o for code generation, image understanding, and audio processing — a 3-month study with production workloads.
Perplexity: Building Real-Time Search and RAG Systems
Real-time web retrieval, citation-grounded generation, and the architecture behind sub-second answers — building a Perplexity-style search engine.
DeepSeek: Self-Hosting Open-Source LLMs
Running DeepSeek V3 and R1 locally on Kubernetes — how we cut API costs by 90%, the hardware requirements, and the quantization trade-offs we made.
Copilot: AI-Assisted Development at Scale
How GitHub Copilot changed our code review process — a quantitative analysis of 500+ PRs measuring acceptance rates, code quality, and developer velocity.
Grok: Real-Time Knowledge Graphs and Conversational AI
Building a Grok-inspired real-time knowledge graph system that ingests live data streams and answers questions with up-to-the-minute accuracy.
Lovable: From Idea to MVP with AI-Generated Code
Our experience building a production MVP in 2 hours using Lovable — the architecture it generated, the code we kept, and the 3 things we had to rewrite.
Manus: Multi-Agent Automation Pipelines
Evaluating Manus as an AI agent framework for our automation pipeline — how it handles complex multi-step tasks and where it still needs human oversight.
NanoBanana: Building Agentic Workflows
Building a multi-agent system with NanoBanana — architecture patterns, tool-calling orchestration, and lessons from deploying agentic workflows in production.
Leonardo AI: Generative Art in Engineering Workflows
Automated asset generation, style consistency, and API patterns that saved our design team 20 hours per week — integrating Leonardo AI into our pipeline.
Meta AI: Fine-Tuning Llama for Production
From data curation and LoRA training to deployment and monitoring — our 6-month journey fine-tuning Llama 3 for production with 40% accuracy improvement.
Assembly AI: Speech-to-Text at Scale
Real-time transcription architecture, speaker diarization, and cost optimization strategies for processing 1M+ minutes of audio — cutting our bill by 45%.
Canva AI: Automating Visual Content Pipelines
How we built an automated social media graphics pipeline using Canva's API and AI features — generating 100+ branded assets per week.
Veo 3: Text-to-Video for Technical Demos
Prompt engineering patterns, temporal consistency techniques, and how we integrated Google Veo 3 into our documentation pipeline for product demo videos.
Sora 2: Video Generation for Engineering Documentation
Benchmarking quality, cost per minute, and the 5 patterns that produced watchable results — experiments with OpenAI Sora 2 for technical explainer videos.
Kimi: Long-Context LLMs for Document Intelligence
Handling 200K+ token documents with Kimi — the architecture for processing entire codebases, legal contracts, and research papers in a single context window.
Kling: Video Generation Benchmarks and Integration
Benchmarking Kling against Sora 2, Veo 3, and other video generation models — a head-to-head comparison on quality, cost, latency, and API ergonomics.