Optimization Articles
Browse 251 articles about Optimization.
What Is the System Evolution Mindset for AI Agents? How to Turn Every Mistake Into a Rule
Instead of blaming the model when agents fail, use system evolution: turn every mistake into a harness improvement that prevents future errors.
How to Use Claude Code Effort Levels: Low, Medium, High, Max, and Ultra Code
Claude Opus 4.8 adds five effort levels. Learn when to use each, how effort affects token spend, and why matching effort to task complexity changes everything.
Claude Opus 4.8 Effort Levels Explained: Low, Medium, High, Max, and Ultra Code
Claude Opus 4.8 introduces five effort levels that change how deeply the model reasons. Learn which level to use for each type of task.
Google AI Search Mode Explained: What Changed and How to Optimize for It
Google's AI Search Mode is the biggest upgrade to search in 25 years. Learn what changed, how conversational search works, and what it means for your content.
How to Prompt Claude Opus 4.8 Differently: Tell It What to Do, Not What to Avoid
Claude Opus 4.8 responds better to positive instructions with context than to negative constraints. Learn the prompting shift that improves output quality.
What Is the AI Token Cost Crisis? Why Enterprise AI Bills Are Exploding
Agents and reasoning eat tokens at a different scale than chat. Learn why enterprise AI costs are rising and how to manage token spend across your stack.
How Google AI Search Mode Changes Content Strategy for Businesses
Google's AI-first search mode is reshaping how content gets discovered. Learn what it means for SEO, AEO, and how to adapt your content strategy.
How to Forecast AI Token Usage for Your Business: Beyond Seats and Licenses
Forecasting AI by users or seats will leave you underprepared. Learn to forecast by tokens per workflow, agent loops, and concurrency to avoid capacity shocks.
What Is Prompt Caching in Claude Code? How to Save Millions of Tokens
Prompt caching cuts Claude token costs by 90% for repeated context. Learn how cache TTL works, what breaks the cache, and three habits that maximize savings.
How to Use Language Server Protocol (LSP) with Claude Code for Large Codebase Navigation
Give Claude Code the same symbol-level search developers have in their IDE. Here's how to expose an LSP via MCP server for large codebase navigation.
Prompt Caching in Claude Code: How to Save Millions of Tokens and Extend Session Limits
Learn how Claude Code's prompt caching works, what breaks the cache, and three habits that save millions of tokens and extend your session limits.
How to Build an AI Agent Harness: Why the Wrapper Matters More Than the Model
The harness—rules, skills, hooks, MCP, and memory—drives more agent performance than the underlying model. Here's how to build one that actually works.
What Is Context Engineering? Why It Matters More Than Prompt Engineering for Agents
Context engineering—building the right environment for AI agents—drives better results than prompt crafting alone. Here's how to apply it to your workflows.
How to Position Your Brand for AI Search: The Truth Layer Strategy
AI agents do the shopping now. Learn how to build a structured, provable truth layer so your product appears in AI-mediated searches and recommendations.
What Is the Agent Harness? Why Scaffolding Matters More Than the Model
Cursor's research shows the same model scores 46% or 80% depending on the harness. Learn why your agent wrapper drives more performance than model choice.
Why You Should Never Switch Models Mid-Conversation in AI Coding Agents
Switching models mid-task causes cache misses, context mismatches, and slower turns. Cursor's research explains why one model per session is the right call.
Multi-Agent Reliability Math: Why Chaining 5 Agents Drops Success Rate to 77%
Chain five agents at 95% reliability each and your end-to-end success rate collapses to 77%. Here's the compounding problem and how to architect around it.
Why You Shouldn't Switch Models Mid-Conversation in AI Coding Agents
Cursor's blog explains why switching models mid-session causes cache misses, out-of-distribution context, and slower turns—and what to do instead.
What Is Progressive Disclosure in AI Agent Design? How Skills Load Context Efficiently
Progressive disclosure means loading only the context a skill needs at each step. Learn why this pattern prevents quality drops in complex Claude workflows.
What Is the Agent Context Bundle? How to Stop Your AI Agent from Rediscovering Everything
Agents waste tokens rediscovering context on every run. Learn how to define and pre-assemble the exact data bundle your agent needs to do its job reliably.