The comparison
| Decision factor | Devin | Archiet |
|---|---|---|
| Existing-codebase tasks (close an issue, add a feature) | Strong. The agent reads the codebase, plans, executes, opens a PR. | Not the use case. We generate; we don't operate inside an existing repo. |
| Greenfield codebase generation | Possible but variable — agents drift, the structure differs per session, decisions aren't documented. | Designed for it. Same input produces the same output. Decisions are documented in ADRs. |
| Determinism | LLM-driven planning + execution. Two runs of the same task can produce meaningfully different code. | Deterministic-first. Templates are versioned Jinja2; structural decisions are rule-based. LLMs only fill stubs and write prose. |
| Architecture documentation | Up to the agent's prompt — usually not produced. | Every material decision gets an ADR in MADR v4 format under docs/decisions/. |
| Compliance documents | Out of scope unless explicitly prompted, in which case the agent generates from generic templates. | Generated from your entity model, classified per regulation (GDPR direct/indirect/Article 9, HIPAA PHI, PCI cardholder data). |
| Predictable cost per outcome | Agent runs are usage-based; complex tasks can be expensive. | Per-generation pricing on a tier. You know the cost before you run. |
| Best fit | "Add OAuth to my existing Express app." "Refactor this service to use the new payment provider." "Fix this issue." | "Generate the production codebase for this PRD with the docs to back it up." |
| Worst fit | Greenfield with strict architecture / handoff requirements. | Inside-an-existing-codebase task where you want the agent to take initiative. |
| Risk shape | Agent might do something you didn't intend. Reviewers catch it. | Generator might emit something that doesn't match your expectation. Quality score + Synthetic Boot Test catch it before delivery. |
The way these tools coexist: Archiet generates the initial production codebase + handoff pack. Devin (or a similar agent) operates inside that codebase later, taking on individual tasks. The agent benefits from working inside a codebase with clear conventions and documented decisions — exactly what Archiet produces.
The mistake we see: using an agent to greenfield a production codebase. The result is technically working code that nobody can maintain because the architecture is an emergent property of however the agent felt that day. Six months in, the team rewrites.
The deeper philosophical difference: Devin bets on agents getting better. Archiet bets on the boring infrastructure work being deterministic. Both bets can be right; they're not mutually exclusive.
What you get
The generated ZIP from Archiet always includes:
- The production codebase in your chosen stack (12 options)
docs/decisions/— ADRs explaining every material choicedocs/traceability/matrix.md+.csv— every user story to FR to file pathdocs/compliance/— DPIA / HIPAA / PCI / SOX populated from the genome (when overlays flagged)docs/security/posture.md— attack surface, auth controls- Quality score (4 dimensions × 25 points)
- Synthetic Boot Test result — codebase verified to start before delivery
The output is yours. There's no agent runtime to keep paying for; you download the ZIP and own it.
CTA
Try Archiet — free plan, no credit card. archiet.com.
If you have an existing codebase and well-defined tasks, agents are the right tool. For greenfield production work with handoff requirements, Archiet is what we built.