From Sand to Superintelligence · Drill cards · Chapter 34
Drills
Agents
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In Anki: File → Import, choose this TSV, set field separator to Tab, deck = Sand to Silicon · Ch 34, note type = Basic.
| Front | Back |
|---|---|
| What are the four minimum components of an agent, per the chapter? | Model, tools, memory, and goal. |
| What does a goal component usually need to be augmented with in serious agent systems? | A verifier — a check that runs after each action to catch divergence early. |
| Name the five steps of the agent loop in order. | Perceive, Plan, Act, Observe, Repeat. |
| What does the chapter say about how much engineering effort goes into guardrails vs. model integration? | Systems like Claude with computer use, OpenAI Operator, and OpenHands spend more code on guardrails, logging, confirmation prompts, and rollback than on the model integration itself. |
| What benchmark does the chapter cite for software-engineering agents, and what solve rate did top agents achieve in late 2025? | SWE-bench Verified; 60–70% of tasks solved. |
| What agent completion rate does AgentBench show for best agents? | ~30%. |
| What four production use-cases does the chapter say agents handle well in 2026? | Coding agents inside established codebases, customer-support triage and resolution, research-and-analysis loops, and routine browser tasks. |
| What does the chapter say definitively does NOT yet work for agents? | Long-horizon autonomous projects without supervision, complex strategic decisions, novel situations without training analogues, and tasks where wrong-action cost is very high relative to right-action value. |
| How does the chapter define the budget that terminates the agent loop? | Tokens, seconds, or dollars — whichever is exhausted first. |