The existing library on AI cost, model economics, agents and spend controls.
"Enhance compliance with audit schema for AI transactions. Explore use cases, implementation, and challenges in AI-driven transaction audits with Harpd's open-source solutions."
Safely switch AI models in production with shadow testing and canary rollouts. Mitigate risks and ensure seamless transitions with this step-by-step guide.
"Debunking the myth of cheap-per-token AI models & their hidden costs. Learn how optimizing for Cost per Successful Task saves up to 90% (McKinsey)."
Compare cost-effective LLMs for JSON extraction, classification, and code review. Analyze top options, capabilities, and integrate with observability tools like @harpd/observe.
Learn how to audit AI agent transactions with a shared audit schema, track spend, and ensure compliance in finance, healthcare, and support use cases.
Explore why per‑workload model replacement outperforms per‑request AI routing for cost, latency, and reliability.
Optimize your content for AI answer engines with GEO and AEO strategies that boost visibility in ChatGPT, Perplexity, and Google AI Overviews.
Cost per successful task LLM: why cheap models can end up more expensive. Learn metrics, observability, and spend control strategies.
Safely switch AI models in production using shadow testing and canary rollouts to avoid regressions, cost spikes, and latency issues.
Audit schema implementation guide for transaction-level agent auditing with @harpd/agent-transaction-audit-schema. Learn how to standardize AI agent audit trails, enforce spend control, and ensure compliance.
AI agent cost observability guide for finance teams – spend analytics, budget tracking, and MCP tool metering
Learn best practices for auditing AI agents in SaaS to ensure compliance and trust.
Learn how to build a governance framework for LLM agent spending to manage costs effectively and ensure compliance.
Learn how to implement AI agent payment guardrails with budget policies, spend caps, and audit trails using open-source tools like x402 and Harpd.
Learn how to implement budget policies for LLM agents to control costs effectively.
Learn how to build a GEO and AEO content strategy for 2026. Optimize for AI answer engines like ChatGPT and Perplexity to win AI search visibility.
Learn about top AI observability tools for monitoring and auditing AI systems effectively.
The checklist we hand to teams going live with paid agents. Twelve items, in order, with the failure mode each one prevents. Skip one and that's the one that bites you.
A concrete, per-tier budget policy template for agent commerce — what to cap per call, per agent, per endpoint, per day, and how to escalate denials to a human without breaking the agent loop.
Three anonymized case studies of agent payment failure patterns — the runaway loop, the wrong-decimals overcharge, and the silent facilitator divergence — and the exact controls that would have stopped each one.
How to turn any MCP tool into a paid tool with x402 — gate tool invocations behind HTTP 402, expose the same MCP schema, and bill per call in USDC. Plus the open-source starter repo that does this end-to-end.
Build an autonomous data agent that pays for its own data using open-source tools like @harpd/mcp-paid-tool-starter and Spend Control. Step-by-step tutorial and case study.
An append-only schema for agent payment events that satisfies three auditors at once — finance, security, and compliance — without coupling to any specific payment protocol.