How YATFA compares
Devin, Factory, and YATFA all start from the same conclusion: one AI doing everything fails. They disagree about where to put the fix.
Every competitor claim below links to its primary source.
How to think about this category
“AI coding tool” covers three jobs that barely overlap. Most teams end up with one from each tier, and that is the right outcome — these are not substitutes.
An interactive pair-programmer inside your editor. You are at the keyboard; it helps you write, edit, and navigate faster. Synchronous, session-based, driven by you.
Complementary. Keep using them. They speed up the code you write yourself; YATFA works the backlog in the background.
Single-purpose automation triggered by an event, usually a pull request: review a diff, or generate tests for it. One job, scoped to the change in front of it. Tier-3 platforms usually include a review bot of their own.
Overlapping, narrower. YATFA's Reviewer does the review job as one stage of a lifecycle that also plans the work, writes it, and proposes what to do next.
Take a goal or a ticket and execute it independently: plan, build, review, open a pull request. Asynchronous, long-running, working from repository state rather than your cursor position.
This is the tier YATFA competes in. Within it, YATFA's distinction is a four-role team by default, deterministic coordination, and a researcher that proposes work you did not ask for.
YATFA does not replace your IDE assistant or your CI. It picks up work in the background, on GitHub, and hands you pull requests.
Three bets on the same problem
Devin (Cognition)
Bet on a single brilliant agent. Long-horizon planning, a full cloud sandbox with a browser, and parallel child sessions for large work. Its stated philosophy is explicitly anti-multi-agent.
Cognition’s own post →Factory
Bet on enterprise fit. A single Droid by default, multi-agent “Missions” for large jobs, and the strongest compliance and sovereign-deployment posture in the category.
Factory’s Missions architecture →YATFA
Bet on the team as the default. Four specialized roles — planner, worker, reviewer, researcher — coordinated by a deterministic engine, with memory shared across roles and a researcher that improves your codebase unprompted.
What YATFA is →Dimension by dimension
Each row is a dimension, not a scorecard. Several of them go to Devin or Factory — if a comparison table published by one of the three vendors showed a clean sweep, you should not believe it.
| Dimension | Devin | Factory | YATFA |
|---|---|---|---|
| Default execution model | One linear agent per session. Multi-agent patterns are added around it — a separate review bot, a manager that spawns child sessions. source for Devin: Default execution model → | One Droid. Specialized roles (orchestrator, workers, validators) appear inside opt-in Missions. source for Factory: Default execution model → | Four specialized roles on every ticket — planner, worker, reviewer, researcher. There is no single-agent mode to fall back to. |
| Stated philosophy | Argues against multi-agent systems: the simplest sound design is a single-threaded linear agent, because conflicting implicit decisions make parallel agents fragile. source for Devin: Stated philosophy → | One agent by default, promoted to multi-agent Missions when a job is large enough to need decomposition. source for Factory: Stated philosophy → | The team is the baseline. Separation of concerns is structural rather than something you enable. |
| How work is coordinated | Through the model itself — context engineering, on the assumption models keep getting more capable, which keeps the system flexible and lets it inherit every model improvement. source for Devin: How work is coordinated → | A programmatic runner spawns a worker per feature and triggers validation with fresh agents — deterministic, and scoped to a Mission's goal. source for Factory: How work is coordinated → | A deterministic engine that runs continuously across all work, not per goal — the path a ticket takes is fixed and predictable rather than improvised. |
| When work gets stuck | Live session view with one-click take-over, so a human can steer mid-task. source for Devin: When work gets stuck → | Mission-level validation and retry, within the Mission's scope. source for Factory: When work gets stuck → | Stalled work is detected and re-queued automatically, and after a bounded number of failed review cycles it stops and escalates to you rather than retrying indefinitely. |
| Adversarial review | Devin Review — a separate reviewer agent with its own clean context, posting on pull requests as a GitHub bot. source for Devin: Adversarial review → | Validators inside Missions, which judge correctness without implementing fixes, plus a code-review GitHub Action. source for Factory: Adversarial review → | A dedicated Reviewer role on every change, with a different context from the worker that wrote it. No configuration needed. |
| Who decides what gets worked on | A human configures the automation first — Auto-Triage watches a channel someone set up; Scheduled Devins run a task someone described. source for Devin: Who decides what gets worked on → | Triggered by you, or by Jira, GitHub, Slack, or a schedule. source for Factory: Who decides what gets worked on → | The Researcher scans your codebase on its own initiative and proposes work nobody asked for — tech debt, missing tests, stale docs — which you approve or decline. |
| Memory | Knowledge — cross-session tips and instructions recalled automatically, scoped to an organization — plus DeepWiki, which indexes repositories into architecture docs. source for Devin: Memory → | No built-in memory between sessions in the CLI; you build one from markdown files and hooks. The cloud platform adds hierarchical user and organization memory with its own retrieval stack. source for Factory: Memory → | Cross-agent by construction and self-updating: a quirk the worker learns is enforced by the reviewer later, without anyone curating it. |
| Runtime and sandbox | Its own cloud VM with a shell, an editor, and a real browser it can operate — useful for work that needs to click through a UI. source for Devin: Runtime and sandbox → | A local terminal agent, and a cloud platform. source for Factory: Runtime and sandbox → | Sandboxed Docker containers, one per role. |
| Where execution runs | In Cognition's cloud, on your plan. source for Devin: Where execution runs → | SaaS, hybrid, on-premises, or fully air-gapped — the widest range of the three. source for Factory: Where execution runs → | On hardware you provide — a laptop, a server, or a cloud VM. Put the runner on an always-on machine and the team keeps working around the clock on compute you already pay for. |
| Enterprise compliance | SOC 2 Type II and ISO 27001, with a dedicated government offering. source for Devin: Enterprise compliance → | SOC 2 Type II, ISO 27001, ISO 42001, GDPR, zero data retention, and customer-managed keys. source for Factory: Enterprise compliance → | Sandboxed containers, feature-branch-only changes, role-scoped permissions, and a human merge gate — but no compliance certification. |
| Integration breadth | GitHub, GitLab, Bitbucket, and Azure DevOps; Slack and Teams; Jira and Linear; plus an MCP marketplace. source for Devin: Integration breadth → | GitHub, GitLab, Jira, Linear, Slack, Notion, PagerDuty, and Confluence, plus three IDEs. source for Factory: Integration breadth → | GitHub, MCP, and Telegram. |
| Open source | No — the core is proprietary. | No — the core is proprietary; some SDKs are open. | No — the core is proprietary. Only a small MCP wrapper is published. |
| Getting started | A free tier to try, then paid plans. source for Devin: Getting started → | Paid per-seat plans, with enterprise through sales. source for Factory: Getting started → | A drop-in command, `npx yatfa`. No free tier. |
The three differences that matter
Single agent, or a team?
Devin’s default session is one linear agent, and Cognition argues that is the sound design — that multi-agent systems are fragile because “actions carry implicit decisions, and conflicting decisions carry bad results.”
“The simplest way to follow the principles is to just use a single-threaded linear agent.”
That is a coherent, defensible position, and Devin has since added narrow multi-agent patterns — a separate review bot, a manager that spawns child sessions. Factory’s default is one Droid, with orchestrator, worker, and validator roles inside opt-in Missions. In YATFA, four roles are the baseline: every ticket is planned, built, and reviewed by different agents with different contexts. The worker never reviews its own work, and there is no single-agent mode to fall back to. Both bets cannot be right in every case; the question is which failure mode costs more on a production codebase.
Improvising, or coordinated?
Devin coordinates through the model itself — Cognition’s framing is context engineering, on the assumption models keep getting more capable. Factory runs a programmatic runner, scoped to a Mission’s goal. YATFA’s coordination is a deterministic engine that runs continuously across all work: it detects stalled work and re-queues it, and after a bounded number of failed review cycles it stops and escalates to you rather than retrying indefinitely. For a codebase you intend to leave agents running on, that difference is the whole argument.
Who decides what gets worked on?
Both competitors ship proactive behavior, and in both cases a human defines the work first. Devin’s Auto-Triage watches a channel someone configured; scheduled sessions run a task someone described. Factory’s Signals is genuinely impressive and points inward — Droid analyzes its own sessions and files tickets to improve Droid. YATFA’s Researcher points outward: it scans your codebase on its own initiative and proposes work nobody asked for — tech debt, missing tests, stale docs, refactors — which you approve or decline. The difference is who defines the work.
Where each is genuinely stronger
Written so that a competitor’s own team would recognise their column as fair.
Devin is stronger at
Scale and traction, with a large certified vendor’s procurement profile. Long-horizon planning on unstructured problems. A cloud sandbox with a real browser, for work that needs to click through a UI. Spinning up many parallel agents on one large build. Breadth of integrations, and a free tier to start on.
Factory is stronger at
Enterprise compliance — SOC 2 Type II, ISO 27001, ISO 42001, GDPR — and sovereign deployment: SaaS, hybrid, on-premises, or fully air-gapped. Integration breadth across Jira, Linear, Slack, and three IDEs. Decomposing a large, well-specified build inside a Mission, with validators that surface problems rather than quietly fixing them.
YATFA is stronger at
Running a team by default, so the worker never reviews its own work. Deterministic coordination that recovers stalled work and escalates to you on a bounded schedule instead of looping. Improving your codebase unprompted. Memory that carries across roles. And running on your own hardware: put the runner on an always-on machine and the team works around the clock on compute you already pay for, with token usage included in your plan rather than metered per agent-hour or per seat.
Which one to choose
Choose Devin if
you have an open-ended problem that needs long-horizon planning, a browser sandbox, or many parallel agents on one large build — and you want the procurement safety of a large, certified vendor with a delivery guarantee and Fortune 500 references. If the work you are handing over is exploratory rather than ticket-shaped, that is what Devin is built for.
Choose Factory if
you are a regulated enterprise that needs SOC 2, ISO 27001, or ISO 42001, air-gapped or on-premises deployment, and deep Jira, Slack, and CI integration — and you want one strong agent you promote to multi-agent Missions for large builds.
Choose YATFA if
you want a structured team where the worker never reviews its own work, a deterministic engine that recovers stalled work and escalates to you rather than looping, and a researcher that improves your codebase without being asked — so you can leave agents running on a production codebase.
Common questions
Does YATFA replace Cursor or GitHub Copilot?
No, and we would not recommend dropping them. They are in-IDE assistants for the code you write at the keyboard. YATFA works asynchronously on GitHub — it picks up tickets, opens pull requests, and proposes improvements while you are doing something else. Most teams running YATFA still have an IDE assistant open.
How is this different from CodeRabbit or a pull-request review bot?
A review bot inspects a diff after someone else writes it. YATFA's Reviewer does that too, but as one stage of a lifecycle: a planner turns the request into a ticket, a worker implements it, the reviewer checks it, and a researcher proposes work nobody asked for. If pull-request review is all you want, a dedicated review bot is a simpler purchase.
Can I run YATFA alongside tools I already have?
Yes. It works through GitHub — feature branches and pull requests — so anything already attached to your repository keeps working, including your CI and any review bots.
Does it work on an existing codebase, or only greenfield?
Existing codebases, primarily. Agents read what is there and follow the patterns you have already established, so new work fits in naturally.
What does it need to run?
A Docker-capable machine for the runner — a laptop, a server, or a cloud VM — and the GitHub repositories you want it to work on. Put the runner on an always-on machine and the team keeps working around the clock on your own hardware. Token usage is included in your plan, with per-project budgets you set, so what scales with continuous running is tokens rather than seats or agent-hours.
How does it compare to Devin or Factory?
That is the rest of this page — the deep dives cover each one dimension by dimension, including where they are genuinely stronger.
How we compare
Competitor facts link to primary sources — each company’s own site, docs, and engineering blog, plus dated press and independent reviews — and each one carries its own date, so you can see how current it is. This category ships monthly; if you find something out of date, tell us and we will correct it. We do not publish competitor claims we cannot source, and where a competitor is stronger, we say so.