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Course contents

  • Getting Started with AI for VLSI Engineers5
  • Just Enough AI: Models and Context15
  • Prompting13
  • Trust and Verification14
  • Using AI for Engineering Work17
  • Engineering Walkthroughs7
  • Practical Foundations for AI Workflows4
  • Engineering Data5
  • Retrieval-Augmented Generation6
  • Agents and Tool Use18
  • Agent Design8
  • MCP and Skills6
  • Multi-Agent Design6
  • Practical Capstone6
  • Tokens, Cost and Latency12
  • Agentic Workflows for Chip Teams18
  • Interview and Judgment10
  • AI Skills: Full Course Index
  • Working with AI Glossary
  • Working with AI Cheatsheet
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‹AI Skills for VLSI Engineers
  1. Topics
  2. AI Skills for VLSI Engineers
  3. Working with AI Cheatsheet

Working with AI · Beginner to Intermediate

Working with AI Cheatsheet

Cost, latency, chain success and pass-rate formulas with examples, plus prompt, verification and guardrail checklists.

On this page

    One page for the four formulas and three checklists. Every number below uses labelled example parameters.

    Cost arithmetic

    Cost is tokens times price, counted separately for input and output. State both counts and both prices before multiplying.

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    Example parameters: 20,000 input tokens at $2 per million, 5,000 output tokens at $8 per million.
    Input cost = 20,000 x 2 / 1,000,000 = $0.04
    Output cost = 5,000 x 8 / 1,000,000 = $0.04
    Job cost = 0.04 + 0.04 = $0.08

    Latency model

    Latency is time to first token plus output tokens over decode speed. Streaming shows tokens early but does not change this total.

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    Example parameters: time to first token 0.4 s, 200 output tokens at 50 tokens/s.
    Decode time = 200 / 50 = 4.0 s
    Latency = 0.4 + 4.0 = 4.4 s

    Chained-step success

    A chain needs every step to pass, so if steps succeed independently with probability p each, overall success is p to the power n. Small per-step losses compound fast.

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    Example parameters: per-step success p = 0.90, steps n = 5.
    Chain success = 0.90^5 = 0.90 x 0.90 x 0.90 x 0.90 x 0.90 = 0.59049, about 0.59

    Pass rate and cost per accepted result

    Pass rate is passed over total on a fixed set. Cost per accepted result divides total spend by accepted results only.

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    Example parameters: 40 passed of 50 trials, each trial $0.10.
    Pass rate = 40 / 50 = 0.80
    Total cost = 50 x 0.10 = $5.00
    Cost per accepted = 5.00 / 40 = $0.125

    Verification checklist

    Check

    Action

    Scope

    Restate the task and what the draft must not change.

    Diff

    Review the diff line by line, not just the final result.

    Differential

    Run the draft against a reference on the same inputs.

    Properties

    Check widths, resets, and protocol invariants the reference may miss.

    Experiment

    The engineer runs the test and keeps the log as evidence.

    Refuse

    Reject the draft when evidence is missing or the check fails.

    Guardrail tiers

    Tier

    Rule

    Example

    Read-only

    The agent reads and proposes without changing state.

    Summarise a regression log and rank suspects with file lines.

    Approval-gated

    Each state change needs explicit approval and a preview.

    Propose a lint patch in a scratch copy, then wait for review.

    Restricted

    Destructive or secret-adjacent acts need a human, a sandbox, and logs.

    Push a fix, rotate a key, or open a network path.

    Prompt checklist

    Item

    Ask

    Goal

    Does the first line name the task and done criteria.

    Context

    Are the files, logs, and constraints attached, trimmed to fit.

    Format

    Is the output shape and schema stated for validation.

    Self-check

    Is a recheck or worked check requested before the answer.

    Budget

    Are tokens, steps, and cost capped for this call.

    Script, workflow, or agent

    Use this

    When

    Why

    Script

    Fixed repeatable steps with no judgment calls.

    Deterministic, cheap, and easy to regress.

    Workflow

    Multi-step path with approvals and fixed branches.

    Control stays explicit while tools do the routine parts.

    Agent

    Open-ended search over tools with uncertain order.

    Flexibility costs budgets, guardrails, and evaluation.

    Related topics

    • Course Hub

    • Glossary

    • What an Agent Is

    • Verifying AI Output

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    See also

    • Getting Started with AI for VLSI Engineers
    • Just Enough AI: Models and Context
    • Prompting