Gemini 3 Prompting Best Practices
Gemini 3 works best with direct, well-structured prompts. Core principles, Flash-specific tips, and a ready-to-use template to get the best results.
Adding Spec-Driven Workflow to an Existing Project Without Burning Months
You inherited a codebase with no specs, so the agent guesses. Fix: spec going forward, not backward. One change at a time, thirty-minute setup.
Why Your AI Agent Ignores Your Team's Conventions
You typed the rule in chat three times and the agent still broke it. Chat is for the current task. Project rules live in AGENTS.md. Yours is empty.
Edit, Restore, or Handoff: The Three Reset Moves Every Agent User Needs
Three things break an agent session: a wrong turn, a drifted conversation, a thread too big. Three moves fix each: Edit, Restore, Handoff. Picking the wrong one wastes time.
Why Phase-Locked Workflow Breaks When the Agent Learns Mid-task
Phase-locked workflow blocks you from going back when you learn mid-task. The fix: actions you run anytime, in any order, without restarting the change.
Prompt Iteration: Fixing Prompts That Don't Work
Your first prompt rarely gives perfect results. Learn three simple fixes: rephrase the ask, switch the task type, and change the order of content.
Prompting Basics: How to Write Clear Instructions for AI
Bad AI answers usually mean a bad prompt. Learn the basics: question or task, constraints, and output format, so the model gives you what you actually want.
Why Your AI Agent Gets Dumber After 30 Minutes
The model did not get worse. Your context filled up. Old noise now fights your new instructions, and the noise is winning.
Which Artifact to Update When the Agent Gets Confused
A change folder has four files: proposal, specs, design, tasks. Teams guess which to update, and artifacts drift. The fix: know what each is for.
Why Your AI Coding Agent Forgets Every Decision You Made
You asked for the same feature twice and got two different implementations. The problem is not the model. Your decisions only live in chat history.
Zero-Shot vs Few-Shot: Teaching AI with Examples
Asking with no examples is zero-shot. Adding a few examples is few-shot, and it usually gives much better results. Here is how and when to use each.
