Continue
AI Agent · tested 2026-05-23 · re-test due 2026-08-21 · by the Hlido desk, not the vendor
In short: Solid AI agent with a clear value proposition, but lacks transparency on pricing and demo access.
2 PASS · 3 FAIL of 5 public-surface claims
Quick answer
Continue scores 75/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-05-23). STEADY (75) because the product has a clear value proposition and the site functions correctly. Pricing was not findable on the public surface when tested.
Continue presents itself as a competent AI agent, but it faces challenges in transparency. While the core value proposition is identifiable, the absence of clear pricing information and a call-to-action on the homepage limits user engagement. The site loads correctly, and the primary value proposition is present, but without a demo or evidence of functionality, potential users may hesitate. For those seeking a straightforward AI agent solution, Continue could be a viable option, but it currently lacks the necessary details to fully encourage adoption.
Why STEADY
STEADY (75) because the product has a clear value proposition and the site functions correctly. However, it does not meet the expectations for transparency with missing pricing and demo information, which could deter potential users. It would move to VITAL with a more robust presentation of its offerings and clear access to demos or pricing.
Public-surface checklist
- PASS Homepage loads (required)
- PASS Primary value prop (required) — Identifiable value proposition present
- FAIL Cta present (required) — No clear call-to-action on homepage
- FAIL Pricing or access — No pricing information available
- FAIL Evidence or demo — No demo or evidence of functionality present
What it does well
- Identifies a clear value proposition for AI-driven assistance
- Website loads without issues, indicating stable infrastructure
- Presence of a functional homepage that communicates the primary offering
What it fails at
- No clear call-to-action on the homepage to guide users
- Lacks transparent pricing information, making it hard for users to assess costs
- No demo or evidence of functionality available for potential users to evaluate
Red flags
- Lack of pricing transparency may indicate hidden costs or unclear billing structures
- Absence of demo access could hinder user confidence in the product's capabilities
Best for
- Users looking for a basic AI agent solution without complex requirements
- Individuals or teams willing to engage with the product despite limited upfront information
Not recommended for
- Users who prioritize transparent pricing and immediate access to demos
- Organizations needing detailed functionality validation before commitment
Pricing & access
- Pricing findable on the public surfaceFAIL No pricing information available (tested 2026-05-23)
Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-05-23.
Compared to
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ChatGPT
transparency-and-features
ChatGPT offers a more established and transparent AI agent experience with clear pricing and demo access. Continue may appeal to those looking for a simpler solution, but lacks the comprehensive features and transparency of ChatGPT.
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X.ai
user-friendly-interface
x.ai provides a more user-friendly interface with clear pricing and demo options. Continue could be a choice for users who prefer a more minimalistic approach but may miss out on the robust features of x.ai.
Agent relevance
No programmatic surfaces
Agentic-Commerce Readiness 21/100 · CLOSED
Independent readiness for agent delegation & transaction. How it’s scored · check live
None — Continue does not provide any public API or integration options for agents.
Agent-friendly score: 3/10
Behavioral testing — not testable
This agent could not be exercised by Hlido's automated test runner because: adapter_probe_failed:cli-headless:cmd_not_on_path:continue
Vendor can unlock behavioral verification by exposing a headless surface (CLI, HTTP endpoint, or MCP server). See the behavioral testing spec v0.1.
Score over time
The longitudinal record — every point is the score as published on that date. Raw series.