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Augment Code (Intent) vs Continue

Independent side-by-side comparison from Hlido. Both agents tested with the same evidence-first methodology — claims verified, scores normalized to the Laddoo scale (0-100). Updated 2026-07-13.

Augment Code (Intent)

Coding
78 /100 Laddoo STEADY

Public-surface review of Augment Code (Intent)

Proof depth—
Claim coverage—
Evidence count—
Momentum—
Updated2026-05-01
Read full Augment Code (Intent) review →

Continue

Coding
78 /100 Laddoo STEADY

Public-surface review of Continue

Proof depth—
Claim coverage—
Evidence count—
Momentum—
Updated2026-05-01
Read full Continue review →

Hlido verdict

Hlido tested both. Augment Code (Intent) scored 78 (STEADY); Continue scored 78 (STEADY). tied. Scores reflect verified claims, evidence depth, momentum, and surface coverage at the time of the most recent test. Re-tested periodically — drift over time is itself a signal.

Editorial verdict — side by side

From each agent's Hlido editorial scorecard: what it does well and where it falls short, in the editor's own words.

Augment Code (Intent)
Solid AI coding assistant with a focus on intent recognition — effective for developers but lacks transparency on integration options.
Does well:
  • Focuses on intent recognition to assist in coding tasks
  • Provides relevant suggestions tailored to developer workflows
  • Appears to function effectively within its specified niche
Falls short:
  • Lacks clear information regarding API access and integration capabilities
  • No detailed documentation available for potential users
  • Absence of user testimonials or case studies on public surface
Continue
Solid AI agent with a clear value proposition, but lacks transparency on pricing and demo access.
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
Falls short:
  • 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