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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
    • Regression Triage Agent
      • The Nightly Triage Loop
      • Clustering Failures by Signature
      • Ranking Suspects with Evidence
      • Read-Only by Default
      • Evaluating Against Labelled History
    • Lint-and-Fix Loops
    • Guardrails and Human in the Loop
    • Evaluating and Operating Agents
  • Interview and Judgment10
  • AI Skills: Full Course Index
  • Working with AI Glossary
  • Working with AI Cheatsheet
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‹Regression Triage Agent
  1. Topics
  2. AI Skills for VLSI Engineers
  3. Agentic Workflows for Chip Teams
  4. Regression Triage Agent
  5. The Nightly Triage Loop

Reference: Agentic Workflows for Chip Teams · Beginner to Intermediate

The Nightly Triage Loop

Inputs, tools, and outputs of one triage pass over nightly regression failures.

On this page

    Inputs

    The agent starts from three inputs. Failure logs carry the error lines, seeds reproduce the run, and recent commits bound the suspect set.

    Input

    What it holds

    Why the agent needs it

    Failure logs

    Error lines plus surrounding context

    Signatures for clustering.

    Seeds

    Random seeds per failing run

    Exact reruns of a failure.

    Recent commits

    Changed files since the last green run

    The first suspect list.

    Tools

    The agent reads through three narrow tools. Each tool has one job and returns plain data the agent can quote.

    Tool

    Does

    Returns

    Log search

    Finds lines matching a pattern

    Matching lines with file offsets.

    Rerun a seed

    Replays one failing run

    Pass or fail plus the new log tail.

    Bisect

    Runs seeds across a commit range

    First bad commit in the range.

    Outputs

    The output is one card per failure group. Each card lists the cluster size, the ranked suspects, and one evidence line per suspect.

    Field

    Example content

    Group

    3 runs sharing one signature.

    Suspects

    Commits ordered c1, c3, c2.

    Evidence

    Touched file, rerun result, bisect vote.

    A schematic pass

    The listing below is schematic. It shows the shape of one pass and is not output from any real system.

    plaintext
    1
    2
    3
    4
    5
    schematic illustration of one triage pass, not output from any system
    1. normalize: strip timestamps, seeds, and addresses from each log line
    2. cluster: runs sharing one signature form one group
    3. rank: score each suspect commit against the group evidence
    4. report: write one card per group with suspects and evidence lines

    Common mistakes

    Common pitfall

    Ranking before clustering multiplies work. Ten repeats of one bug produce ten suspect lists that all name the same commit, and engineers stop reading after the third.

    Interview

    Likely probes: name the three inputs and the three tools, and say what one card holds.

    • Logs, seeds, and recent commits go in; log search, seed rerun, and bisect sit in the middle.

    • One card per group holds the cluster size, ranked suspects, and evidence lines.

    • Report wording varies by model: measure readability with engineers, not by assumption.

    Check yourself The suspect list grows to every commit this quarter. Which input was misused?

    The recent-commits input. Only commits since the last green run belong in the suspect set.

    Check yourself Two runs fail with the same message but different seeds. One card or two?

    One card. The signature matches, so they form one group; the two seeds become rerun evidence.

    Related topics

    • Clustering failures by signature

    • What an agent is

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    See also

    • Ranking Suspects with Evidence
    • Read-Only by Default
    • Evaluating Against Labelled History