Delegate to an agent

How we review AI agents

Agents are different from tools: a tool waits for your input, an agent takes a goal and runs with it. That means every writeup has to answer the safety question explicitly. What is the agent allowed to touch, what does it log, and what happens if it goes off the rails? We always disclose the autonomy level and the safety surface, even when the agent is well known.

Our AI agent comparison framework is built around intent alignment: does the agent actually do what you asked, or does it do what it thinks you meant? We test each agent against structured briefs with deliberate ambiguities to surface overreach, under-delivery, and the uncanny valley between. A capable agent that quietly reroutes your prompt into a plausible-but-wrong outcome is more dangerous than one that simply fails, so we score conservatively on safety-first execution.

Pricing figures matter, but they're rarely apples-to-apples: some agents bill per task, others per token or elapsed wall-clock time, and a few charge by inference step. Our writeups normalize these into a cost-per-task estimate based on a standard medium-complexity brief so you can compare agents without spreadsheet hell. We also flag hidden costs: mandatory API keys, workspace provisioning fees, and rate limits that effectively cap throughput below the advertised tier.

When people search for the best AI agents in 2026, what they're really asking is which agent won't burn their budget, leak their data, or spin its wheels on a three-minute task until the timeout kills it. We update the leaderboard every time an agent ships a breaking release or meaningfully changes its safety posture. The agents page isn't a directory; it's a live evaluation log kept honest by the same public briefs we use in every review.