On-Device AI Comes of Age, but Hardware Still Sets the Limits
Compact models run offline on phones, laptops, and edge devices. The bottleneck is no longer model capability. It is RAM, memory bandwidth, and thermal headroom under sustained load.
Architecture
19 articles exploring architecture
MD vs MDX: The Decision Most AI-Agent Repos Get Wrong
Markdown is a storage format. MDX is an execution format. Every AI coding tool chose .md for agent instructions. The distinction explains why, and when MDX earns its place.
Airflow in 2026: The Orchestrator That Became the Operating System for Data
Comprehensive Apache Airflow analysis: open source and every managed vendor (Astronomer, Cloud Composer, MWAA), pricing at three scales, Airflow 3.0 migration, operational pain points, AI workflows, and a decision matrix for choosing the right deployment.
Dagster in 2026: The Orchestrator That Treats Data as the Product
Comprehensive Dagster analysis: pricing, asset-centric orchestration, AI/ML pipelines, learning curve, integrations, and why treating data as the product gives teams lineage and governance that task-centric orchestrators cannot match.
Prefect in 2026: The Orchestrator Built for AI Workflows
Comprehensive Prefect analysis: pricing, scaling, deployment architecture, integrations, learning curve, and why its dynamic Python-native control flow fits AI agent workflows better than static DAG orchestrators.
Vector Databases in 2026: Why Most Teams Adopt One Too Early
Most teams adopt a dedicated vector database before the production signals that justify it arrive. A decision framework for when pgvector stops being enough.
Document Parsers for Agentic Workflows: LiteParse, LlamaParse, and the Tools That Actually Matter
Benchmark-driven comparison of the 2026 document parsing landscape - LiteParse, LlamaParse, Unstructured, Docling, PyMuPDF, Google Document AI - with Python code, failure modes, and an async routing architecture.
Which Frontend Framework Wins in the AI Era
Framework choice is no longer about developer ergonomics. In an AI-driven era, the winners will be frameworks that resist entropy, enforce constraints, and scale safely under continuous AI modification.
The AI Coding Shift: Why Strongly-Typed and Compiled Languages May Win
For 30 years, language choice was driven by developer productivity. AI changes the equation. When machines generate code, verification matters more than velocity.
You Probably Don't Need Elasticsearch for Global Search
PostgreSQL's built-in full-text search can handle global search for most SaaS applications. Learn when Postgres is enough and when Elasticsearch makes sense.
Why PostgreSQL Is Your Best Bet for AI Projects (And You Probably Already Have It)
Stop over-engineering AI infrastructure. PostgreSQL already has everything you need: pgvector for embeddings, pgai for automation, TimeScaleDB for metrics. Build faster by using what you have.
The 2% Problem: Why AI Harness Beats Model Capability
Production AI systems are 98% harness, 2% model. New research reveals why architecture, permissions, and safety matter more than model capability - and how to build systems that actually work.
Airflow vs Prefect vs Dagster: The Production Migration Guide (2026)
After running all three in production: 20-criteria breakdown of real migration costs, team overhead, backfill behaviour, and which orchestrator survives 500+ pipelines.
SaaS Metrics Stack: ARR, MRR & Churn You Can Actually Trust
How to build a SaaS metrics stack that produces ARR, MRR, churn, LTV, and CAC you can actually defend - with SQL, Python, and the right source-of-truth hierarchy.
The Only AI Coding Tool Comparison That Matters in 2026
Most AI coding tool comparisons still reward the wrong things. A workflow-first breakdown of Claude Code, Cursor, Copilot, Windsurf, and Antigravity through the lens that actually matters: how teams ship under real constraints.
The Hidden Cost of AI-Generated Code (and How to Fix It)
AI-generated code feels fast, but the maintenance cost appears later. Why AI creates locally correct but globally fragile systems, and the engineering standards that fix it.
Claude Code Project Structure That Actually Scales: Patterns, Templates & Real Examples
A battle-tested blueprint for Claude Code projects that stay predictable at 50+ files - folder layout, .claudeignore, skills architecture, and 3 ready-to-copy templates.
I Built My Own Portfolio From Scratch (Here's What Bit Me)
A CTO's honest account of building a personal portfolio site from scratch - the decisions that made sense at the time, the bugs that didn't, and what I'd do differently.
Building API Dev Utils: A 400+ Tool Developer Platform
From a simple JSON formatter to a 400+ tool developer platform serving 100K+ users - the complete engineering journey covering architecture, zero-backend design, performance, and deployment.