What does ExecuteSpec actually do?

ExecuteSpec runs your feature request through a pipeline — planner → plan-approval gate → executor → reviewer (general + wiring passes) → final build + test gate — and opens a pull request on your repo with a deterministic verdict (Ready / Needs review / Failed) attached. Unlike inline AI coding tools that produce diffs you have to validate yourself, ExecuteSpec runs the validation and shows you the result.

What makes ExecuteSpec different from other AI coding tools?

Unlike standard text-to-code generators, ExecuteSpec runs every AI-generated task through a deterministic validation chain — Syntax, Type, Lint, and Unit Tests — before the pull request is opened. The PR you receive carries a Ready / Needs review / Failed verdict from that chain, not the LLM's self-rating.

How does ExecuteSpec compare as an alternative to Lovable, Bolt.new, emergent.sh, Cursor, or Windsurf?

Lovable, Bolt.new, v0, and emergent.sh are excellent for rapid zero-to-one prototyping in their own sandboxes. Cursor, Windsurf, and Claude Code are great inline copilots in your IDE. ExecuteSpec is neither — it's the merge-validated alternative: takes a feature request, runs autonomous code generation, runs the CI/CD validation chain (Syntax, Type, Lint, Test, reviewer), and opens a real PR on your repo with a verdict attached. Built for the merge step, not the typing step.

Does ExecuteSpec support Bring Your Own Keys (BYOK)?

Yes. The Team tier ($50/seat/month, from 2 seats) and Enterprise are both BYOK — plug in your own Anthropic, OpenAI, or Google API keys, get unlimited managed-AI usage with zero per-run markup from us, and pay providers directly. Enterprise can also route through OpenRouter as a gateway. The Pro tier ($20/mo) uses managed keys — we pay the LLM costs and you get 2,000 AI credits per month. The Free tier (200 AI credits per month, no credit card) uses our managed-AI grant.

What enterprise use cases does ExecuteSpec support?

ExecuteSpec excels at clearing engineering tech debt through merge-validated AI runs. Key use cases include automated unit test coverage generation, clearing JIRA backlogs autonomously, and modernizing legacy frameworks (e.g., migrating Spring Boot 2.x to 3.x). Each run opens a PR with a Ready / Needs review / Failed verdict so reviewers know where to start.

How does ExecuteSpec compare to Cursor?

Cursor is an AI-powered IDE — you edit code inline with the model as a pair programmer. ExecuteSpec is a hosted delivery pipeline — you write a spec, the platform generates a plan, executes tasks, runs validation gates, and produces a PR with a Ready / Needs review / Failed verdict. Cursor shines for line-level editing; ExecuteSpec shines when you want a structured spec to produce merged, tested code without sitting at the keyboard. Many teams use both.

How does ExecuteSpec compare to Windsurf?

Windsurf is Codeium's agentic IDE fork with deeper multi-file agent flows. Like Cursor, it's an editor you drive manually. ExecuteSpec is not an editor; it's an async pipeline that takes a spec, decomposes it into a task plan, validates the work against build + test gates, and opens a PR with a deterministic verdict. Use Windsurf if you want to stay in your IDE. Use ExecuteSpec if you want to hand off feature-sized work and get back a merged PR with a deterministic verdict.

How does ExecuteSpec compare to Claude Code?

Claude Code is Anthropic's terminal-first coding agent — run locally, reads/writes files in your current workspace, pay Anthropic directly by token. ExecuteSpec is a hosted multi-agent platform with a browser UI, multi-repo project workspaces, architecture doc generation, tech-debt tracking, and team features (RBAC, org audit trail). Both support BYOK for Anthropic. Claude Code is the minimalist CLI; ExecuteSpec is the workbench around it.

How does ExecuteSpec compare to GitHub Copilot?

GitHub Copilot is primarily an autocomplete and chat assistant inside your IDE. ExecuteSpec operates at a higher altitude: you give it a spec, it plans the decomposition, executes multi-step tasks across one or more repos, runs CI validation, and ships a PR. Copilot is great for 'finish this function'; ExecuteSpec is for 'ship this feature'. Copilot has deeper IDE integration; ExecuteSpec has deeper verification, project context, and multi-repo orchestration.

How does ExecuteSpec compare to Lovable, Bolt.new, or v0?

Lovable, Bolt.new, and v0 are zero-to-one web prototyping tools — type a prompt, get a running web app in minutes. Optimised for greenfield demos. Their output often struggles with complex business logic, multi-repo codebases, test coverage, and day-two maintenance. ExecuteSpec enters where those leave off: operates on existing codebases, enforces validation gates on every task, tracks tech debt over time, supports multi-repo projects, generates architecture documentation. Use Bolt for a 10-minute prototype; use ExecuteSpec for verified production code.

How does ExecuteSpec compare to Devin?

Devin (from Cognition Labs) is an autonomous coding agent that goes from ticket to merged PR with minimal human input. ExecuteSpec shares the ambition but differs on transparency and pricing. ExecuteSpec always pauses at a plan-approval gate before burning compute, surfaces every tool call via live SSE, produces a deterministic Ready / Needs review / Failed verdict from real signals (build status, test pass rate, reviewer outcome — not LLM self-rating), and starts free, then $20/mo. Devin starts at $500+/mo and is optimised for full autonomy. Choose Devin for pure autonomy; ExecuteSpec for autonomy with a reviewable plan gate and transparent scoring.

ExecuteSpec — AI that ships pull requests your team actually merges

Token transparency

Know what the agents spend before, during, and after the run.

ExecuteSpec does not hide LLM usage behind a vague credit counter. Every production run exposes the estimate you approved, the live token stream while agents work, and the final provider-cost ledger your team can audit.

Before approval

Plan-time estimate

See expected input, output, cache-read tokens, provider route, and dollar cap before execution starts. Reject or revise without burning worker tokens.

During execution

Live spend meter

Watch input, output, cache-read, reasoning tokens, and cost move task by task beside the live tool log.

After completion

Final token ledger

The run report and PR summary keep the provider-level ledger: planner, worker, reviewer, cache savings, total cost, and approved cap.

How it works · 4 steps

From a spec to a merge-able PR.

One pipeline, four checkpoints. Every run carries a verdict, a cost breakdown, and a diff your team can read.

01 · PLAN

📝

You write one line

A natural-English spec. We classify it as SMALL/MEDIUM/LARGE and build a task plan with a cost estimate. You approve before any LLM tokens are spent on execution.

02 · EXECUTE

⚡

An agent per task

One agent works each task in turn. Tool-calling: readFile, writeFile, editFile, shell, buildProject. Live log streams every action with timestamp + cost.

03 · VERIFY

🔍

Tests + reviewer + build

Smoke test after every task. Final reviewer pass (general + wiring) on the whole change, plus a fix-the-build pass if needed. Additive verified score (0–100).

04 · SHIP

🚀

PR with a verdict

A real PR on your repo, opened from your connected GitHub account, with the verified score attached. CI runs your gates too. You merge.

Your workspace

A real IDE, in the browser.

● RUNNING NOW · R-4429

Add OAuth2 to checkout, support Google & GitHub.

3/4TASKS

14mELAPSED

$0.42SPENT

Move logs to pino92%

Migrate jobs to BullMQ96%

Admin search w/ fuzzy73%

A workspace, not a dashboard.

A VS Code-style IDE: activity bar, Explorer, editor, and a real code & diff viewer — so you read the change the way you'd read a teammate's PR. Runs take 5–20 minutes; watch one live or walk away.

✓
Explorer + code & diff viewerBrowse the file tree, open any file, read every diff inline — no leaving the page.
✓
⌘K command paletteJump to a run, a project, or an action without touching the mouse.
✓
Project chat with memoryAsk "why did March's refactor hit 94% and this one is at 87%?" — the agent knows.
✓
Light & dark, follows your systemPlus push notifications — plan ready, run shipped, cost-cap warnings — when you step away.

Library + Migrations

Skip the boilerplate. Ship the readymade.

28 solutions and 11 migrations, each pre-tuned to ship to your stack. Pick one, tweak the spec, approve the plan. Average 5 minutes from click to PR.

⚡

Stripe checkout

Subscription + one-time + webhook signature verify

~6m

🔐

OAuth login

Google + GitHub + email-password fallback

~4m

🧠

RAG with pgvector

Tika extraction → embeddings → retrieval

~9m

🛠

GitHub Actions CI

Build · test · lint · containerize · push

~3m

📦

Docker compose dev

Postgres + Redis + app · hot reload

~2m

💳

Razorpay checkout

India payments · UPI · cards · auth webhooks

~5m

Browse 28 solutions 11 modernization recipes

Pricing

Simple. Start free. Scale up.

Managed AI is metered in AI credits as your run works — failed calls aren't charged. BYOK removes the managed-AI cap entirely. Cancel any time.

FREE

$0₹0

No card required

200 AI credits / month
Small specs only
Managed-AI cap
1 project · 1 repo
Email support

Start free

PRO

$20/mo₹1,699/mo

Indie devs · monthly

2,000 AI credits / month
Managed keys — Anthropic · OpenAI · Gemini
PR review + code review (4 scans/mo)
2 projects · 2 repos each
Managed-AI cap · Pro+ upsell when needed
Library + migrations

Get started

RECOMMENDED

BYOK

$50/mo₹4,299/mo

Solo org · own API keys

No managed-AI cap
Mandatory provider keys
Model matrix available
Single-person organization
No provider markup
Upgrade to Team for members

Use your keys

TEAM

$50/seat/mo₹4,299/seat/mo

Minimum 2 seats · monthly

Unlimited on your own keys (BYOK)
No managed-AI cap · zero markup
BYOK — Anthropic · OpenAI · Gemini
Org spend caps + approval thresholds
Cross-repo + sharing
Autofix: PR review · tech debt · code scans

Get started

ENTERPRISE

Custom

Custom contract · DPA

Unlimited · no managed-AI cap
BYOK + OpenRouter gateway
Model matrix override + per-run pin
Standards · Contracts · ADRs
Org governance + audit trail
Dedicated support

Talk to sales

Honest comparison

How we differ from inline AI coding tools.

Cursor, Copilot, Continue — they suggest code at the cursor. You validate it. ExecuteSpec runs the validation itself and only opens a PR when it passes.

ExecuteSpec

OutputReal PR + verdict

Approval gatePlan-level

ValidationBuilt-in

Multi-repoNative

BYOK3 providers

DPA + GDPR exportYes

Cursor / Copilot

OutputDiff suggestion

Approval gatePer-edit

ValidationYour CI

Multi-repoOne repo

BYOKYes

DPA + GDPR exportYes

Devin / Lovable

OutputLong-form

Approval gateOptional

ValidationPartial

Multi-repoLimited

BYOKNo

DPA + GDPR exportSome

v0 / Bolt

OutputUI snippet

Approval gateNone

ValidationPreview only

Multi-repoNo

BYOKNo

DPA + GDPR exportNo

FAQ

What people ask before they sign up.

Do you train models on my source code?

No. Your source code lives in a workspace that's wiped at run end. We never train any model on it, never share it beyond the LLM provider you picked, and never read it without a run-scoped JWT that proves you authorized the access. See Trust & Security for the full sub-processor list.

What does "Bring Your Own Keys (BYOK)" mean?

On TEAM and ENTERPRISE, you can connect your own Anthropic, OpenAI, and/or Google AI keys — and ENTERPRISE can also route through OpenRouter as a gateway. Calls against your keys bypass the managed-AI cap entirely (we still track cache-hit rates for optimization). Your keys are stored server-side under the deployment crypto policy, never logged, and can be replaced any time from org settings.

How is this different from Cursor / Copilot / Continue?

Inline AI coding tools (Cursor, GitHub Copilot, Continue) suggest code at the cursor and leave validation to you. ExecuteSpec runs the validation itself — syntax, type, lint, build, tests, reviewer pass — and only opens a PR when those gates pass (or labels it Needs review / Failed when they don't). The output is a real merge-able PR, not a diff suggestion.

What's the verified score?

A deterministic 0–100 score attached to every PR, computed from real signals — not the model grading itself. It's an additive weighted score across five slots: code delivered (30) + build (25) + tests (20) + reviewer (20) + criticals (5), averaged over whichever slots actually fired. Tests come from running your own test suite in the workspace; build and reviewer from the real passes. The verdict pill (Ready / Needs review / Failed / Blocked) is derived from the score.

Can I cancel any time?

Yes. Cancel from Account → Billing. Your data stays available for 30 days after cancellation. GDPR export gives you everything as a ZIP.

What languages and stacks do you support?

Anything an LLM can read. We have battle-tested support for Java/Spring, TypeScript/Node, Python/FastAPI, Go, React, Vue, and React Native. The agent's behavior is the same regardless of stack; the test framework is what differs (JUnit/pytest/Vitest/Go test).

Does it work for monorepos?

Yes — that's where we shine. The TEAM and ENTERPRISE tiers support multi-repo runs natively: per-repo codemaps, per-repo architecture docs, cross-repo contracts with drift detection, per-repo PRs that cross-link in the run report.

Stop reviewing diffs. Start merging PRs.

200 free AI credits a month. No card. Five minutes to your first verified PR.