Prompt engineering, minus the hand-waving.
Concrete techniques, real math, honest benchmarks. Written for developers who already use LLMs in production and want to spend less of their own money doing it.
Building an LLM SaaS that doesn't go broke: things we wish we'd known on day one
Honest founder retrospective from EcoToken's first year. The pricing decisions, the cost surprises, the customer feedback that mattered, and what we'd build differently if we started over today.
Read →The 1M-token context window: when you should actually use it
Gemini, Claude, and GPT all offer huge context windows now. That doesn't mean you should fill them. Here's the cost, latency, and accuracy math on long context — and when retrieval still beats it.
Read →Claude Code vs Cursor vs Windsurf: the real cost-per-task breakdown
All three AI coding tools advertise flat monthly pricing — and all three have completely different overage models hiding underneath. Here's a concrete breakdown of what a typical week actually costs on each.
Read →Extended thinking is hiding your real Claude bill
Anthropic's extended thinking and OpenAI's reasoning models charge thinking tokens at the output rate. Most accounting dashboards never show them. Here's how to actually see your bill — and what to do about it.
Read →Five MCP servers actually worth wiring into your dev workflow
The Model Context Protocol ecosystem hit 500+ servers in early 2026. Most are noise. These five are the ones that earn their keep — with the specific commands and quick-start setups for each.
Read →How to reduce Claude API costs in 2026
Five specific techniques to cut your Claude API bill by 30-70% without switching providers — with concrete examples and the math behind each.
Read →Why "input-only" savings dashboards are lying to you
Most prompt-optimizer tools claim huge savings by counting input tokens only. That understates the real number by 3-5× and ignores the actual value prop. Here's what honest math looks like.
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