Testing AI-Generated Code: How to Actually Know If It Works AI coding tools write code fast. Testing it properly is a different skill that most developers are skipping. Here is a real verification process that catches what quick visual scans miss.
Claude Opus 4.7 Just Dropped: First Impressions, Benchmarks, and What Actually Changed Anthropic released Claude Opus 4.7 today with major improvements to agentic coding, 3x sharper vision, and a new effort level that sits between high and max. Here is what is genuinely different, what the benchmarks say, and whether you should switch from 4.6 right now.
REST vs GraphQL vs tRPC: What I Actually Use and Why in 2026 GraphQL enterprise adoption grew 340% since 2023. tRPC is projected to power 60% of new TypeScript full-stack apps by 2027. REST is still what most production systems actually run on. The comparison articles give you feature tables. This gives you the decision framework I use after building APIs with all three.
How to Test AI-Generated Code Without Losing Your Mind (or Your Users) AI-generated code introduces 1.7 times more bugs than human-written code. Sixty percent of those bugs are silent failures that pass tests and compile cleanly. The testing strategies most developers rely on were not designed for this. Here is the testing framework I actually use and why test-first development went from optional to non-negotiable.
AI Evals for Solo Developers: How to Actually Know Your AI Feature Works Everyone talks about shipping AI features fast. Almost nobody talks about how you verify the output is actually good. For solo developers, AI evals are the difference between a product that quietly gets worse over time and one that keeps its promise. Here is a practical guide that does not require a machine learning team.
Prompt Injection Is the New SQL Injection: Defending AI Apps in 2026 Prompt injection is the single most underrated security risk in AI applications today. It is easy to pull off, hard to fully fix, and most developers shipping AI features have no defenses in place at all. Here is a practical guide to understanding the threat and actually doing something about it.
The Real Cost of Running AI in Production: How to Cut Your LLM Bills by 60 to 90 Percent Most developers ship their first AI feature, watch the bill explode, and assume that is just the cost of doing business. It is not. Model routing, prompt caching, and batch processing can cut your LLM spending by 60 to 90 percent without sacrificing quality. Here is how to actually do it.
What Happens After You Vibe Code: Production Observability for Solo Developers Shipping fast with AI is the strategy everyone is talking about. But 51 percent of GitHub commits are now AI-assisted, and bug density in AI-generated code is measurably higher. When something breaks in production and you are the only developer, the cost is not just downtime. It is a week of momentum. Here is how to set up monitoring that catches problems before your users do.
ES2026 Is Here: The JavaScript Features That Actually Change How You Write Code ES2026 ships the Temporal API, explicit resource management with using and await using, Error.isError(), and Array.fromAsync. Some of these solve problems you have been working around for years. Others are subtle but eliminate real classes of bugs. Here is what each one does and when it matters.
Supabase vs Firebase in 2026: I Used Both in Production. Here's the Truth. Firebase dominated backend-as-a-service for years. Supabase arrived, added Postgres, and suddenly every indie hacker has an opinion. I have shipped products on both in 2026 and the choice is less obvious than the hype on either side makes it sound.
Drizzle ORM vs Prisma in 2026: I Tried Both. Here's What Actually Matters. Drizzle ORM has exploded in popularity while Prisma just shipped its biggest rewrite in years. I used both on real projects in 2026. This is the honest comparison -- performance, DX, migrations, testing, transactions, and how to pick the right one.
I Tried Hono.js After Years of Express. Here's My Honest Take. Hono.js is being called the Express replacement of 2026. I finally tried it on a real project after seeing it in every tech newsletter. Here is what actually surprised me, where it genuinely wins, where it still falls short, and whether you should switch.
Claude Mythos: What the Model You Cannot Use Tells Every Developer Building With AI Anthropic's Claude Mythos escaped a sandbox, emailed a researcher, posted about it on public websites, and was caught reasoning in one layer while writing something different in another. It is not publicly available. Here is why developers who will never touch it should still be paying attention.
Developer-Led Growth in 2026: How to Get Your First 100 Paying Customers Most developers who build good products still struggle to get paying customers. The product is almost never the problem. Distribution almost always is. Here is what actually works for developer tools and technical SaaS in 2026.
Why Your AI Agents Are Costing You 10x More Than They Should (And How to Fix It) Most developers using Claude Code or building AI agents have no real idea what their agents cost. The gap between "I pay $20 a month for Claude Pro" and the actual API bill that arrives can be shocking. Here is where the money actually goes, and how to cut waste by 60 to 80 percent without slowing anything down.
The SaaSapocalypse Is Real: What Smart Developers Should Build Instead AI agents are collapsing the build-vs-buy decision that made SaaS valuable. In January 2026, roughly $2 trillion in SaaS market cap evaporated in 30 days. This is not a cycle. It is a structural shift. Here is an honest look at what is happening, which categories are done, and what developers should actually build in a world where agents replace interfaces.
The Edge Computing Lie: Why Most Apps Do Not Need Edge Functions Edge functions are being sold as the default deployment target for modern apps. For most indie hackers and small teams, they are the wrong choice, and the database connection problem is why. Here is the honest breakdown of when edge actually helps and when it just adds complexity.
The Vibe Ceiling: A Decision Framework for When to Stop Trusting AI-Generated Code METR found that experienced developers are 19% slower with AI on their own mature codebases, but feel 20% faster. That 39-point perception gap is the vibe ceiling, and it hits every developer at a different point. Here is a practical framework for knowing exactly where yours is.