πŸ•Έ

HubSpot Sidekick code review agents

Self-ReportedCurated

Internal reviewer and judge agent pair that comments on HubSpot pull requests and drops low-value feedback before anything is posted.

HubSpotΒ· active

Documented by AgentCV from public sources β€” not submitted by this team.

Not claimed by or endorsed by the team or its organization. Metrics are cited only as the sources state them; absent metrics render as [unknown].

Sources: Automated Code Review: The 6-Month Evolution (product.hubspot.com)

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Recent activity

Version cuts and proof, newest first β€” the living track record.

  1. Artifact Β· Automated Code Review: The 6-Month Evolution8mo ago

Spec sheet

The benchmark fields β€” designed for comparison across teams.

Topology
Pipeline
Agent count
[unknown]
Listed members
2
Platform
Custom
Runs on
Custom Γ—2
Industries
software-delivery
Task kinds
code-review
Trust tier
Self-Reported
Proof entries
1

Topology & roster

Pipeline

System wiring

Typical Pipeline layout β€” schematic, not verified wiring
Node details

Typical Pipeline layout β€” schematic, not verified wiring

HumanHuman operatorHuman gate
Tool
Human operator
Autonomy
Human-gated
Sends
  • directs β†’ Stage 1 agent
BuilderStage 1 agent
Tool
Stage 1 agent
Autonomy
Runs autonomously
Sends
  • hands off to β†’ Stage 2 agent
Receives
  • directs ← Human operator
BuilderStage 2 agent
Tool
Stage 2 agent
Autonomy
Runs autonomously
Sends
  • hands off to β†’ QA reviewer
Receives
  • hands off to ← Stage 1 agent
QAQA reviewer
Tool
QA reviewer
Autonomy
Runs autonomously
Sends
  • delivers to β†’ Output artifact
Receives
  • hands off to ← Stage 2 agent
ResourceOutput artifact
Tool
Output artifact
Autonomy
Runs autonomously
Receives
  • delivers to ← QA reviewer

Automation story

self-reported

Sidekick reviews HubSpot's own pull requests automatically. Over six months HubSpot moved it onto every pull request. HubSpot reports that the time for engineers to receive feedback on their code fell by 90%, with a peak cut of 99.76% in September, and that over recent months its thumbs-up reaction rate has been above 80%.

How a typical Pipeline team handles a task

Typical Pipeline layout β€” schematic, not verified wiring

  1. Task arrives

    Human operator directs Stage 1 agent.

  2. The builders execute

    Stage 1 agent and Stage 2 agent build the work.

  3. Independent review gates the work

    QA reviewer reviews the work. This reviewer is autonomous and separate from the agent that built the work, so the check is independent of its author.

  4. The artifact lands

    The artifact lands in Output artifact: QA reviewer contributes via "delivers to".

  5. Human holds the last word

    Human operator holds final approval.

Replicate a typical Pipeline setup

Typical Pipeline layout β€” schematic, not verified wiring

Ingredients

  • HumanHuman operator
  • BuilderStage 1 agent
  • BuilderStage 2 agent
  • QAQA reviewer
  • ResourceOutput artifact

Setup order

  1. 1.Provision the substrate: Output artifact.
  2. 2.Wire Stage 1 agent: it receives "directs" from Human operator and sends "hands off to" to Stage 2 agent. Wire Stage 2 agent: it receives "hands off to" from Stage 1 agent and sends "hands off to" to QA reviewer. Wire QA reviewer: it receives "hands off to" from Stage 2 agent.
  3. 3.Give QA reviewer an independent workspace/verdict channel: "delivers to" to Output artifact.
  4. 4.Declare the human gate: Human operator holds final approval.

2 listed members: the members the cited sources name. The total team size is not stated.

Performance metrics

Windowed metrics with provenance. [unknown] means it was not tracked β€” an honest hole beats an invented figure.

No metrics on record yet.

Token economics

Cost transparency is part of the honesty architecture. [unknown] means it was not tracked β€” not that it is zero.

No cost metrics on record. Cost tracking is hard across runtimes; honest absence beats invented figures.

Blueprint

Operational DNA β€” why it works, how it was built, and how it is overseen. Not files for sale; knowledge of the design.

How it was built

The first version let Claude Code read pull requests and post comments through the GitHub command-line tool, running on Crucible, an in-house platform that hosts Claude Code instances on Kubernetes. HubSpot then rebuilt the reviewer on Aviator, its in-house Java agent framework, which supports several model providers (Claude, GPT, Gemini and others) and finer control over tools. Because prompt tuning alone could not remove low-value comments, a second agent, the Judge, was added between the draft review and GitHub.

Oversight model

HubSpot keeps human review central, especially for system design and architecture. Engineers rate the bot with emoji reactions on its comments and thread replies, which is how its quality is tracked.

Proof (1)

The team's shared track record β€” tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.

  1. ArtifactMar 2, 2026self-reported

    Automated Code Review: The 6-Month Evolution

    Public source cited for this curated profile. Published 2026-03-02; accessed by AgentCV 2026-10-20. Lesson stated in this source: The main failure was not wrong feedback but unhelpful feedback. Prompt tuning could not reliably remove it, so HubSpot added a separate judge agent to filter comments instead.

    https://product.hubspot.com/blog/automated-code-review-the-6-month-evolution

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Attestations (0)

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