AI Coding
35 guides tagged “AI Coding”.
- Does AI Still Hallucinate (and Why)? Yes, AI models still hallucinate. The 2026 AI Index measured hallucination rates from 22% to 94% across 26 models. Why it happens and what you can do about it.
- Can AI-Generated Code Be Detected? No reliable way to detect AI-generated code exists. Detectors claim high accuracy but mislabel human code and are easy to evade. What actually works instead.
- Which Code Hosting Platforms Ban AI-Generated Code? Codeberg and SourceHut restrict AI-generated code, Stack Overflow bans ChatGPT answers. What each policy says, when it takes effect, and how enforcement works.
- How to Prevent AI Code Detectors From Flagging Your Code AI code detectors flag style, not origin. Learn what makes code look machine-generated, how to write code that doesn't get flagged, and when hiding it is the wrong move.
- What Is an AI Agent? An AI agent is a program that uses a language model to decide and act — calling tools, reading files, and iterating until a task is done. Learn how they differ from chatbots.
- What Watermarks Do LLMs Leave in Generated Code? Text watermarks like SynthID-Text and Claude's watermark exist — but code has no deployed watermark yet. Here's how watermarking works and why code resists it.
- How to Choose the Right AI Coding Tool for Your Workflow Compare the 8 best AI coding tools of 2026: Claude Code, Cursor, GitHub Copilot, OpenAI Codex, Windsurf, Gemini CLI, Lovable, and Bolt. Decision guide for vibecoders of every skill level, budget, and project type.
- How to Coordinate Multiple AI Coding Agents on One Codebase Running multiple AI agents in parallel sounds fast, but without coordination they overwrite each other's work. Learn six patterns that keep parallel agents safe: spec-driven decomposition, git worktrees, role splits, model routing, verification gates, and sequential merges.
- How to Optimize Token Usage When Coding with AI Every AI coding session burns tokens. Learn the five levers that cut token spend 50-80%: prompt compression, caching, model routing, output control, and context pruning. Practical techniques for vibecoders and teams.
- Self-Hosted AI Coding Models in 2026: The Practical Review The gap between open-weight and proprietary coding models is closing fast. Compare Kimi K3, GLM-5.2, Qwen3-Coder, Gemma 4, DeepSeek V4, and more. Benchmarks, hardware requirements, and honest recommendations for every budget.
- Path Traversal in AI-Generated Code: How Your File Download Endpoint Gets Hacked AI assistants build file-serving endpoints with string concatenation that attackers exploit with ../. Here are the vulnerable patterns your AI generates, the encoding tricks that bypass naive fixes, and the one correct solution.
- How to Write Comments That AI Assistants Actually Read and Use AI assistants read your comments to understand intent and constraints. But they ignore noise and copy bad patterns. Here's what to write — intent over mechanics, constraints over descriptions, and contracts over implementation.
- How to Structure Files So AI Agents Don't Break Your Architecture AI agents generate code in the wrong files, break module boundaries, and turn your project into a monolith. Here's how to structure directories and files so AI agents generate code that fits your architecture.
- How to Name Things So AI Assistants Generate Better Code AI assistants pattern-match on your existing names. Inconsistent naming produces inconsistent AI-generated code. Here's the naming system — descriptive, searchable, consistent — that makes AI assistants generate code that fits your project.
- How to Stop AI Assistants from Duplicating Code Across Your Project AI assistants can't see your entire codebase, so they duplicate validation, formatting, and helper functions everywhere. Here's how to find duplication, extract shared code, and prevent the AI from copying itself again.
- How to Work With an AI Coding Assistant Without Creating a Mountain of Tech Debt AI assistants generate code fast — and generate tech debt faster. Duplicated logic, dead code, over-engineered abstractions. Here's the system for catching these before they accumulate: review, deduplicate, simplify, delete.
- How to Debug an AI-Generated API That Returns Wrong Data Your AI built an API endpoint. It returns 200 OK with wrong data. Here's how to trace request → handler → response when you didn't write the handler — isolate the broken function, instrument it, and get a targeted fix.
- How to Debug AI-Generated Code: A Complete System for When You Don't Understand What the AI Wrote Your AI wrote 300 lines and you don't know what any of it does — and now it's broken. Here's a repeatable debugging system: isolate, bisect, instrument, explain. No prior understanding required.
- How to Debug AI-Generated Database Queries That Return Wrong Results Your AI wrote a database query. It runs, but returns the wrong data — missing rows, wrong counts, stale results. Here's how to extract the raw SQL, test it directly, and fix it without the AI rewriting your whole data layer.
- How to Find Which AI-Generated Change Broke Your App Using Git Bisect Your AI made 15 commits yesterday and now something's broken. git bisect pinpoints the exact commit in minutes without reading any code — just a yes/no test. Step-by-step for AI builders.
- Why Does the AI's Code Keep Failing Linting (and How to Fix It)? Your AI assistant generates code that fails every lint rule. Here's why, which rules to enforce in CI, and how to auto-fix the AI's output before it merges.
- How to Make Your Codebase AI-Friendly: A Complete Guide Your AI assistant is only as good as the codebase it reads. Structure files for context windows, name things consistently, and write comments the AI actually uses. Complete practical guide for making any codebase AI-friendly.
- How to Simplify Overly Complex AI-Generated Functions (Without Breaking Them) AI assistants over-engineer everything — factory patterns for one implementation, abstract classes for nothing, 5 nested conditionals for a yes/no. Here's how to simplify AI-generated code to match the actual complexity of the problem.
- How to Refactor AI-Generated Code Without Breaking Your App Your AI assistant wrote a 400-line function and you need to clean it up. Here's the step-by-step refactoring loop that keeps tests green — one small change at a time, with the diff you can actually review.
- How to Find and Remove Dead Code Your AI Assistant Left Behind AI assistants leave dead functions, unused imports, and abandoned abstractions everywhere. Here's how to find dead code with grep and IDE tools, delete it safely, and stop the AI from generating more.
- What Is Multi-Agent Coding (and Why Do Agents Conflict With Each Other)? Multi-agent coding runs several AI agents on one codebase in parallel — and they step on each other's changes. Learn the failure modes and how to manage them.
- Why Did My AI-Generated Terraform Config Almost Delete Production? AI-generated Terraform can look correct while lacking prevent_destroy, state safety, and plan review. Learn the specific mistakes and how to guard them.
- How to Write a Spec an AI Coding Agent Can Actually Follow Write specs that produce reliable AI-generated code: explicit goals, edge cases, non-goals, and acceptance criteria. A practical, template-driven guide.
- What Is SQL Injection (and Why Does AI-Generated Code Keep Writing It)? SQL injection lets attackers run arbitrary database commands through your app. Learn how it works and why AI-generated code repeatedly introduces it.
- What Is Context Engineering? Context engineering is the skill of curating what an AI model sees so it produces the right output. Learn why it's replacing prompt engineering.
- What Is Spec-Driven Development? Spec-driven development writes a specification before code, so AI agents build from explicit intent. Learn how it fights intent drift and context decay.
- What Makes a Codebase "AI-Friendly"? An AI-friendly codebase gives agents clear conventions, modular files, and tests so they make fewer mistakes. Learn the traits that make AI coding work.
- What Is Vibe Coding (and Where Does It Break Down)? Vibe coding is building software by prompting AI and accepting what works, without reading every line. Learn what it is and exactly where it fails.
- How to Debug AI-Generated Code When You Don't Understand It Debugging code you didn't write is a skill. Learn the method: read the error, reproduce minimally, bisect the change, and interrogate the code.
- How to Review AI-Generated Code Like a Senior Engineer A practical checklist for reviewing AI-generated code: correctness, security, edge cases, and intent. Review what the assistant skips, not just what it wrote.