Put your coding agents on a governed delivery line.
ThriveOnDev turns a Linear issue into a reviewed pull request — routed to the right agent, isolated, retried, audited, and measured. Run the control plane in our cloud or entirely in your cluster.
- Any agent, routed per task
- Cost and outcome per run
- Your Kubernetes or ours
- One shared practice — same skills for every agent
Add rate limiting to the public API
Implement
#opus
Review
#gpt
- 3
Fix review
#sonnet
- 4
PR ready
CI passed · no human rework commits
Accepted PR
Inference cost · $0.42 on API key / $0.00 marginal on your subscription
Runs on the subscriptions you already pay for.
Each agent runs under the engineer's own Claude Code, Codex, or Copilot subscription auth — just like the CLI does locally — or on your API keys with BYOK.
No token markup, ACUs, credits, or new per-seat AI bill from us. Per-user credential mapping avoids shared accounts, and the scheduler respects provider plan limits.
The commercial model
We charge for the pipeline, not the tokens.
Subscription-billed runs have no marginal inference charge from ThriveOnDev. API-billed runs stay on your key and remain visible in the run receipt.
Billing unit · factual comparison as of July 2026
- Devin Enterprise
- ACUs
- Factory / Tembo / Warp
- Credits
- GitHub Copilot
- AI Credits
- ThriveOnDev
- Platform fee only
Usage-metered platforms
Bill against measured agent work or token credits.
ThriveOnDev
Bills the platform fee; inference runs on your own subscriptions and API keys.
Bring the agents you already use
Subscription auth and BYOK are both first-class paths.
- Claude Code
- Codex
- Copilot
- OpenCode
- Gemini
The control plane ships its own control plane.
ThriveOnDev's own Linear issues are implemented, reviewed, and fixed by the agents it orchestrates. The same graphs, isolation, and run receipts we sell are how the product gets built.
Every pilot conversation includes a walkthrough of the live workspace — not a polished recording or a fabricated dashboard.
See it on a pilot callThriveOnDev / live workspace
Dogfood delivery graph
Issue selected in Linear
durable · traceable · repeatable
Agent implements in an isolated job
durable · traceable · repeatable
Second agent reviews and fixes
durable · traceable · repeatable
Outcome and cost recorded
durable · traceable · repeatable
The strongest proof point is operational: we can open the actual issue, agent session, PR review, and run receipt in one demo.
Know what your subscriptions ship — and where runs need help.
One operating view starts with delivery outcomes and utilization across providers. API cost stays visible as pilot evidence, not as a ThriveOnDev billing meter.
A pilot agrees success criteria up front, then populates these views with your real delivery data — not generic benchmarks.
- Merged PRs / week
- Outcome throughput
- No-rework rate
- Quality signal
- Subscription utilization
- Existing capacity
- Provider comparison
- Agent + model
THR-482 · rate limit public API
- Agent / model
- Claude · Opus
- Runtime
- 06m 12s
- Billing source
- API-billed example
- CI result
- Passed
- Elicitations
- 1
Outcome trace
- Implement#opus
completed
- Review#gpt
approved with findings
- Fix review#sonnet
completed
- Pull requestPR #128
ready for human merge
Accepted PR
None
$0.42 API / $0.00 marginal on subscription
One alias. Any harness.
Change the underlying agent or model without retraining the team, rewriting automations, or betting delivery on one lab.
Deep reasoning
General delivery
Fast tasks
Cost-efficient
Aliases also cover #sonnet, #haiku, #deepseek, and #copilot variants, so routing policy can stay stable as the underlying provider changes.
Durable recovery
Retries, timeouts, cleanup, and dead-letter handling are part of the graph — not an operator’s late-night checklist.
Isolated execution
Each run gets a tenant-scoped Kubernetes job with a defined repository and tool boundary.
Audit by default
The issue, graph version, agent events, review, outcome, and cost stay connected in one trace.
One way of working with AI — for the whole team.
Today every developer uses agents their own way: personal prompts, personal habits, and invisible quality variance. The result can depend on who ran the agent.
ThriveOnDev makes the team's AI practice a shared, versioned asset. The same skills, pipeline, and review standard apply to every agent and every provider. A new engineer inherits that practice on day one instead of inventing their own.
One versioned practice
implement
Applies to: all agents
review
Applies to: all agents
fix-review
Applies to: all agents
audit
Applies to: all agents
Managed in your repo. Visible in the dashboard. The practice stays stable even when the agent or provider changes.
Your code can stay in your perimeter.
Install the control plane and every agent job in your Kubernetes cluster. Self-hosting is the product, not a remote runner attached to someone else's SaaS.
- Whole control plane and execution via Helm
- Tenant-scoped Kubernetes jobs and credentials
- Offline license validation; no phone-home dependency
- HMAC-signed callbacks and full run audit trail
- SSO / OIDC and air-gapped deployment path
Customer cluster boundary
issue · comment · status
Isolated agent job
Repository + tools
code and credentials remain inside the boundary
A delivery line around every agent run.
The mechanism comes after the outcome: routing, isolation, review, recovery, and a receipt make each run repeatable.
- 01Linear is the command surface
Assign or label an issue.
Keep work where the team already plans it. Assign the agent, add the Automatable label, or call /implement with a model alias.
/implement #opus - 02The delivery graph takes over
Run the whole pipeline.
A versioned graph launches an isolated job and runs implement → review → fix-review with durable retries and failure handling.
implement → review → fix - 03Humans keep authority
Review the reviewed PR.
A second agent checks the work against the issue and CI. The PR arrives with its audit trail, model, runtime, billing source, and outcome.
accepted_pr · subscription-billed
Prove what your existing agent spend can ship.
A focused pilot for AI-forward teams on Linear — designed to measure merged PRs, rework, subscription utilization, and provider performance on your own backlog.
Coming from Devin or another metered agent platform? The pilot is designed to reproduce the workflow you already liked — on your existing subscriptions — and measure the difference on your own backlog.
- Four-week, founder-led engagement
- One Linear workspace and a scoped repository set
- Live cloud or self-hosted deployment path
- Success criteria measured by run telemetry
- Pilot fee credited to the first-year contract
Consultative pricing; no public self-serve checkout. The pilot starts only after scope, decision owner, and measurable success criteria are agreed.
The questions that should be asked.
Early-stage does not mean vague. The pilot exists to make the technical and commercial decision with real evidence.
Linear and our coding agents already create PRs. Why add this?
Keep them. ThriveOnDev orchestrates those same harnesses and adds the operating layer around the run: provider routing, a review-and-fix stage, durable retries, isolation, auditability, cost and outcome telemetry, and a fully self-hosted path. It is for teams that need a pipeline, not another trigger.
How is this different from Devin?
Devin is a proprietary agent product. Enterprise usage is metered in Agent Compute Units (ACUs), while current self-serve plans combine included quota with on-demand credits. ThriveOnDev keeps the same Linear-native motion — assign an issue, get a reviewed PR — but is agent-neutral: Claude Code, Codex, Copilot, OpenCode, and Gemini can be routed per task. Runs use the subscriptions your team already pays for or your API keys, so the platform fee is separate from inference and there is no ThriveOnDev usage-metered inference bill. If you liked Devin’s workflow but not a variable usage invoice, it is the same habit with more predictable economics.
Which teams are a fit for the design-partner pilot?
AI-forward engineering teams of roughly 15–150 people that already use Linear and at least one coding agent. The strongest fit is a team feeling review bottlenecks, cost opacity, agent sprawl, or a requirement to keep code and execution inside its own Kubernetes environment.
Which agents and models are supported?
Claude Code, Codex, Copilot, OpenCode, and Gemini are supported. Teams can route a task using aliases such as #opus, #sonnet, #haiku, #gpt, #kimi, #deepseek, or #copilot while the versioned graph and delivery policy stay the same.
Our developers each use AI differently. Does this help?
Yes. Skills, pipelines, and review standards are defined once at the organization level and versioned. Every agent and provider follows them, so a new engineer automatically inherits the team’s AI practice on day one.
Can agents run on our existing Claude or ChatGPT subscriptions?
Yes. Per-user credential mapping means each engineer's own subscription powers their tasks, the same as running the CLI locally. ThriveOnDev does not use shared accounts, and the scheduler respects provider plan rate limits. BYOK API billing is a first-class option; with self-hosting, all authentication stays inside your perimeter.
Can the whole platform run in our infrastructure?
Yes. The self-hosted package installs the control plane and agent execution into your Kubernetes cluster via Helm. It supports offline license validation, tenant-scoped jobs and credentials, SSO/OIDC, and an air-gapped deployment path, so source code does not need to leave your perimeter.
How does the pilot prove ROI?
Before the pilot starts, we agree measurable success criteria: merged PRs per week, human rework rate, subscription utilization, provider performance, runtime, and failure reasons. Cost per accepted PR remains supporting evidence for API-billed runs. The platform records the inputs for those decisions on each run.
You are an early company. How do we reduce that risk?
The engagement is limited to four weeks with a fixed scope, a named decision owner, and success criteria the product measures. We show the live workspace where ThriveOnDev ships its own code, and the self-hosted option means you do not have to depend on our cloud for continued operation.
Watch the control plane ship its own code.
In 25 minutes: a live issue-to-reviewed-PR run, the receipt behind it, and a straight answer on whether your team is a good pilot fit.