LLM Cost & Production
Running LLM applications and AI agents in production: token cost, model routing, latency, caching, rate limits and reliability.
An agent that costs cents in a demo can cost dollars per conversation in production, because retries, tool calls, long system prompts and ever-growing context multiply the tokens behind every answer. Cost, latency and reliability are one problem seen from different sides, and the fixes, from routing easy turns to cheaper models to trimming context, tend to help all of them at once.
These articles break down where agent spend actually goes and how to control it without making the agent worse.
Start here: Total cost of ownership calculator · Token budget (glossary)
How to Reduce LLM Token Costs in Long Conversations: What Caching Saves, and Where It Stops
A long conversation costs far more than its number of turns suggests, because every request carries the system prompt and the entire history again, so total input grows with the square of the number of turns.
Claude API Pricing in 2026: Every Model per Million Tokens, and What Pro and Max Cost
The Claude API costs between $1 and $10 per million input tokens and between $5 and $50 per million output tokens on Anthropic's current models.
The Real Cost of DIY Agent Memory
Building agent memory from scratch costs $40K-$120K and 6+ months of engineering time. See the real numbers behind DIY memory systems and when to build vs buy.
Your AI Agent Is A Cash Guzzler. Here's a Framework for Thinking About It.
Most founders misjudge agent costs, focusing only on token price. In reality, stacked expenses from context accumulation and infrastructure can explode bills 10x at scale. Learn to identify the actual growth curve in your billing stack and why smart context management is the only viable path to sustainable unit economics.