Live engineering session · 12 agents online

The Most Advanced
AI Solution
for Every Coding Problem.

Ask coding questions, debug errors, generate apps, create websites, design dashboards, learn programming, build SaaS products, optimize code, architect systems, deploy projects, and ship faster with AI.

CONTEXT · DEVOPS MODE
AI workspace · generating
▸ inspecting your live deployment · 18 services analysed
▸ visual root-cause located on the image pipeline node
▸ rerouting transform to a healthy runtime · auto-applying
✓ deployment restored · production canvas back online
1.2M
tokens / minute
47ms
median first token
12
specialist agents
99.98%
deploy success
Scenario 01 · 02:14 AMSCENE · WARROOM

Production has an issue. AI fixes it visually.

A live alert hits your workspace. AI traces the broken component on the canvas, proposes a visual patch, and ships the fix — without ever leaving the design surface.

incident-4471 · live workspaceSEV-1
LIVE PREVIEW · shop.app
ISSUE
ProductCard · render mismatch312 affected views
AI ACTIVITY● analysing
Locating affected component on canvas
Comparing rendered vs intended states
Locale + timezone differ between server & viewer
Visual patch generated · confidence 0.97
Patch applied to ProductCard
Rolled out to production · 0% errors
VISUAL PATCH · ProductCardauto-merging
BEFORE
timestamp rendered server-side
AFTER
localised on the viewer · hydration safe
ERROR RATE
0.00%
↓ from 11.3% · last 90s
P95 LATENCY
142ms
recovered
AI CONFIDENCE
0.97
component match
AGENT MESH
12 agents
collaborating
RELEASE FLOW● LIVE
analyse
design
review
assemble
canary
production
SYSTEM RECOVERED · INCIDENT CLOSED IN 1m 42s
Scenario 02 · solo founderSCENE · MVP

Type the company. Watch it ship.

One prompt becomes a folder tree, an API, a database, a deployed app — like an entire engineering team materializing in the room.

PROMPT · 21:08:44
"Build me a fintech SaaS dashboard with Stripe, charts and team auth."
frontend agentscaffolding
backend agentwiring api
db agentmigrating
devops agentprovisioning
files generated142
routes wired28
db tables11
deploylive · 6m 12s
FILESYSTEM · materialising
  • 📁 app/
  • 📄 page.tsx+ created
  • 📁 (dashboard)/
  • 📄 layout.tsx+ created
  • 📄 metrics.tsx+ created
  • 📄 ledger.tsx+ created
  • 📁 api/
  • 📄 stripe.webhook.ts+ created
  • 📄 transactions.ts+ created
  • 📁 db/
  • 📄 schema.sql+ created
  • 📁 infra/
  • 📄 wrangler.toml
ledgr.app/dashboard
● live
MRR
$48,210
+12%
Active
1,842
+8%
Churn
1.2%
-0.3
Recent payout
+ $2,140.00 stripe ✓
Team auth
RBAC · 4 roles wired
GIT STREAM ›a13f2feat(app): scaffold dashboard layout·b8c01feat(api): stripe webhook + idempotency·c44e9db: schema for orgs, users, txns·d09aaci: deploy to edge + canary·e7712fix(auth): refresh rotation·
Scenario 04 · learning modeSCENE · TUTOR

An AI that draws to teach.

Ask 'explain binary search' — and the screen becomes a whiteboard. Arrays animate, pointers move, complexity is shown, then you're quizzed.

PROF
Professor VCA
tutor agent · v4
Explain binary search.
Sure — start with a sorted array. We'll halve the search space each step. Watch →
Time complexity is O(log n). Want a quiz?
Yes, hit me.
QUIZ · 1 of 3
For an array of 1,048,576 items, max comparisons?
WHITEBOARD · live drawingstep 3 / 5
1
3
4
7
9
11
14
18
21lo
25
28
32
37mid
41
46
52hi
target 37 located in 3 comparisons.
comparisons
3
found at
index 12
O(log n)
optimal
Scenario 05 · multi-agent meshSCENE · AGENTS

Six minds. One repository.

Specialist agents pass tasks like jazz musicians pass solos. They review each other's PRs, argue over architecture, and converge on a deploy.

FRONTEND
rebuilding cart UI
BACKEND
patching /checkout
DATABASE
adding partial idx
DEVOPS
blue/green rollout
SECURITY
audit · OWASP scan
ARCHITECT
drafting RFC-12
NEURAL MESH · 14ms sync
● ALL CHANNELS HEALTHY
TASK BUS · live
  1. architect → backend
    draft API for /sessions
  2. backend → database
    migration: add sessions
  3. database → backend
    ✓ schema ready
  4. backend → frontend
    openapi types pushed
  5. security → backend
    rate-limit middleware required
  6. frontend → devops
    preview ready · push canary
  7. devops → all
    ✓ rolled out 10% · err 0%
Scenario 06 · screenshot → codeSCENE · SCREENSHOT

Drop a screenshot. Receive a codebase.

Layers separate. Tokens extract. Components self-assemble into a typed, accessible, responsive React tree.

INPUT · screenshot.png
NAV
extracting 8 layers…
OUTPUT · LandingPage.tsx● a11y AA · responsive
export function Landing() {
  return (
    <main className="min-h-screen bg-background">
      <Nav />
      <section className="grid lg:grid-cols-12 gap-8 py-24">
        <Hero className="lg:col-span-7" />
        <Pitch className="lg:col-span-5">
          <h1>{copy.title}</h1>
          <p>{copy.body}</p>
          <Button variant="hero">Get started</Button>
        </Pitch>
      </section>
      <FeatureGrid items={features} />
    </main>
  );
}
components
12
tokens
34
LCP est.
1.2s
Scenario 07 · architect modeSCENE · ARCHITECT

Design for 10 million users.

Watch the AI think in systems — CDN, queues, sharded Postgres, autoscaled k8s — drawn live, then defended in plain English.

10M usersCDNWAFAPI GWWS GWk8s · webk8s · authk8s · jobsk8s · streamRedisQueuePG · shardOLAP
TRAFFIC · 1.2M rps · p99 38ms
DECISION
Shard Postgres by tenant_id (hash, 16 shards)
TRADE-OFF
Read replicas vs cache: choosing Redis L1 + replica L2
RISK
Hot shard on top 1% tenants → vbucket migration runbook
COST
$18,400 / mo at peak · scales to 0 at trough
your next workspace

The future of building software
is already on screen.

You don't need a bigger team. You need the canvas — the one where AI is already designing, assembling and shipping products alongside you.

● 12 agents online ● 1.2M tokens/min ● 47ms first-token ● 99.98% uptime
VirtualCodeAssistant · build 4.4.71© engineered live · 2026