CodePus is an AI-native IDE: 10 built-in working modes — Ask, Plan, Agent, YOLO, Design and more — paired with multi-agent orchestration and self-healing debugging. From Q&A, planning and coding to design and debugging, all in one place. Switch modes per task, and AI works within the right permission boundaries.
Available for Windows · macOS · Linux. Free tier forever.
The industry's first AI automation pipeline covering the entire software engineering lifecycle. The super agent advances stage by stage under contract, with fixed inputs/outputs/acceptance criteria — no skipping, no gaps.
Task recognition · Type detection · Template matching
Multi-source intake · Structured follow-ups · Multi-model debate
Stack selection · API design · Module breakdown
URL→HTML · Image→Prototype · Voice→Design
Auto-detection · Dependency install · Environment check
Task breakdown · Auto-coding · Change report
Tiered testing · Auto-diagnosis · Self-healing
Docs generation · Security scan · Quality gate
Artifact packaging · Canary deploy · Delivery sign-off
Monitoring & alerting · Runbooks · Feedback iteration
Three quick-start templates covering every scenario
S1→S9 fully automated, including architecture, environment, testing, gating, release and ops
S1→S5 with test loop, URL scraping + reverse requirements + automated implementation
S1→S5 recognises existing code and iterates incrementally
Real-time visibility into every agent's status, stage progress and quality-gate results. When the super agent is running, you don't see a black box — you see a full stage timeline, progress bars and deliverable list.
S0→S9 visual timeline, current stage highlighted, progress at a glance
Success rate, average duration, failure point tracking — every delivery quantified
Pass/Warn/Fail three-tier gating — nothing ships until it qualifies
Requirements, design prototypes, test reports, delivery lists — all in one view
Not a simple Copilot — it's an AI architect, project manager and chief engineer with full lifecycle authority. One instruction, from requirements to launch, orchestrating 12 specialist sub-agents autonomously.
Commands 12 sub-agents to deliver complete software projects end-to-end
Automated S0→S9 ten-stage orchestration with smart skip/parallel/rollback
7 providers, cross-model verification, consensus-based decisions
Test → diagnose → fix → retest, 3 auto-fix rounds by default
Each stage gated Pass/Warn/Fail — nothing passes that doesn't meet the bar
Requirements–architecture–design–code–test artifacts flow through the whole chain, zero information loss
Human confirmation at key checkpoints, autonomous decisions otherwise — efficiency and safety in parallel
Every sub-agent is an expert in its niche — independent window, session, command and acceptance criteria. Launch individually or orchestrated by the super agent.
S1→S3 · From requirements to prototype
Multi-source intake (text/voice/URL/video/docs), structured follow-ups, multi-model debate, outputs PRD + acceptance criteria + feature-UI mapping
Tech stack selection, module decomposition, API list, data model design — auto-generates architecture draft
URL→HTML reverse engineering, image→prototype, sketch→code, voice-driven design edits, feature-UI mapping validation
S4→S5 · From environment to code
Automated environment detection (doctor), dependency install (setup), runtime verification (verify) — ready in one click
Reads requirements and design artifacts, decomposes the task tree, implements the code, emits change reports and risk notes
S6→S7 · Testing, docs, security & CI/CD
Unit→integration→E2E→RPA tiered testing, auto-diagnosis + auto-fix + retest loop (configurable rounds)
Auto-generates architecture docs, API docs, user manuals and ops guides — synced live with the code
Dependency scanning, risk grading (High/Medium/Low), fix suggestions, release-blocking decisions
Pipeline execution, gate aggregation, artifact verification — automated CI/CD
S8→S9+ · From launch to iteration
Artifact packaging, release gates, canary deployment strategy, human confirmation for production, delivery manifest
Monitoring & alert rules, Runbook generation, incident response flow, database/server deployment config
Collects issues/user feedback, prioritises them, one-click loops back to S1 to start the next iteration
Debug mode runs a full self-healing pipeline: run tests → auto-diagnose → apply fixes → re-test, looping until they pass — freeing you from repetitive manual debugging.
Unit · Integration · E2E · RPA tiered execution
Aggregate logs, traces, screenshots to locate root cause
Automatically apply fix patches based on diagnosis
Auto-retest after fix to confirm resolution
CodePus supports multi-modal input across chat and every working mode. Express your requirements the most natural way.
Describe requirements and intent in natural language
Record → Transcribe → Edit → Confirm, ASR supports multiple languages
Auto-scrape web pages, configurable depth (0=full site)
Screenshot→HTML, Sketch→Prototype, Image→Code
Multimodal video parsing to extract requirements and design
PDF/DOC/MD auto-parsed into structured requirements
Got a complex requirement? Multiple AI models debate the contested points and output a converged plan. Not one model's guess — multiple models colliding into the best answer.
At least 2 different models in the debate
User can stop anytime and take the latest document
Disagreements → merged conclusions → open questions all logged
Covering all major AI providers, automatically routing to the best model for each task. One-click switching, always synced with the latest capabilities. No vendor lock-in. Your keys, your control.
Complex logic · Math proofs · Multi-step planning
Smart coding · Refactoring · Auto testing
Image+text · UI screenshot analysis · Visual reasoning
Million-token windows · Full repo awareness
Millisecond inference · Real-time completion · Streaming
Local deployment · Data stays on-premise · Compliance
OpenAI-compatible · Private deploy · Self-hosted models
From millisecond completions to deep code understanding, every detail engineered for peak efficiency.
Proprietary completion model with millisecond response, multi-line prediction, function-level generation. Context-aware precision.
Select code, describe changes in natural language, AI rewrites instantly. Diff preview + AI review — see before you change.
Semantic indexing of your entire codebase. Search code in natural language, understand architecture intent beyond text matching.
Model Context Protocol connects external tools, .codepus/rules enforces coding standards — infinitely extensible AI capabilities.
Your code is your most valuable asset. CodePus provides comprehensive security so enterprises can confidently adopt AI coding.
One-click privacy mode — zero code sent to cloud. Use local models for sensitive projects, fully offline.
SAML/OIDC enterprise auth, SCIM auto-sync seats, unified identity management.
Complete operation audit trail, meeting SOC 2, ISO 27001 and other compliance requirements.
Full on-premise deployment, data never leaves your network. Built for finance, government, and high-security environments.
Share prompts, rules, and tool configs. Unified team AI coding experience — new members onboard instantly. Per-member AI usage and code generation analytics.
I used to write code; now I describe requirements and the super agent delivers from S1 to S8 autonomously. One person is a whole team.
12 agents each on their post, end-to-end from requirements to ops. Three auto-fix rounds before they even report — that's a real Agent.
One-click URL scraping → reverse analysis → prototype → code. Simulating a competitor's site collapsed from 2 weeks to 2 hours.
Not just faster code completion — a whole new way to work across Q&A, planning, coding, design and debugging. 10 modes + multi-agent teamwork. Free tier forever.