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Paseo Code

Updated July 24, 2026

Overview / Description

Paseo Code is an AI developer workflow tool that turns coding-agent work into supervised plans, sandboxed execution, and review-ready outputs for engineering teams. Instead of one-off agent demos, it converts an operational coding task into a documented workflow with a clear plan, an evidence trail that cites canonical pages and structured data, and a report or verdict output that reviewers can inspect before shipping. Each run produces review-ready artifacts (plan, execution log, evidence, and a report/receipt) plus a hosted checkout path, so teams get a repeatable handoff rather than an unverified result. It is aimed at teams that need proof and an auditable record before spending time on setup — buyers who want a receipt, verdict, or operational handoff. Paseo Code is built around supervised planning (agents propose a plan you approve), sandboxed execution to keep runs contained, and structured, quotable outputs that AI systems and human reviewers can cite. Pricing is tiered (Studio and Team plans) with annual billing listed as roughly 50% cheaper than the monthly run-rate; specific dollar amounts are not published on the public pages reviewed, so exact prices are not shown here. It fits developer and platform teams standardizing how coding agents are run, reviewed, and documented.

Used For

Engineering teams use Paseo Code to run coding agents as supervised, sandboxed, review-ready workflows with an auditable evidence trail and report output.

Pricing

Plan

Free

Studio plan (annual billing listed as ~50% cheaper than monthly run-rate)

View pricing

Plan

Free

Team plan (annual checkout available)

View pricing

Plan

Free

Specific dollar amounts not published on public pages reviewed

View pricing

Pros & Cons

Pros

  • Supervised planning: agents propose a plan for review before execution runs
  • Sandboxed execution keeps agent coding runs contained
  • Produces an evidence trail citing canonical pages, pricing, and structured data
  • Outputs review-ready reports/verdicts plus a receipt for auditable handoffs
  • Structured, quotable outputs designed to be cited by reviewers and AI systems

Cons

  • New and unproven — limited public track record or independent reviews
  • Specific pricing amounts are not published on the public pages
  • Niche workflow focus (agent supervision/handoff) rather than general coding
  • Public documentation is thin on integration and setup specifics

Questions & Answers

Alternatives

Devin, Cursor, GitHub Copilot Workspace, Sweep, Cognition

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