To the CTO: Our AI-Driven Development Policy

This post is intended to share our development policy with the entire team.

Premise: Our Tool Stack

ToolUse CaseImpact
Claude CodeCode generation, refactoring, debugging, testing10x implementation speed, task decomposition via parallel subagents
OpenClawAutonomous AI agent, self-improvement loop24/7 operation, automatic fixes and deployments
IronClaw/OuroborosSelf-compiling agent, LINE/Web/TUI integrationRuns improvement cycles without human intervention
GitHub CopilotInline code completionEliminates boilerplate

Development Process

Requirements → Design with Claude Code → Implementation (AI-generated) → Test → Deploy
   ^                                                                          |
   └────────── Sprint Review ← Blog Update ← Meeting ←───────────────────────┘

Cycle time: Previously 2 weeks → Now 2-3 days

What We Do and Don't Do

What we do (mandatory):

  • Write and run tests (across all projects)
  • Security reviews (OWASP Top 10)
  • Performance measurement (response time, memory)
  • Back up production data
  • Update the blog every sprint

What we don't do (waste of time):

  • Debating whether to implement dark mode
  • Endless loops of technology selection (we're going with Rust. End of discussion.)
  • Waiting for perfect UI/UX before releasing
  • Waiting for everyone's consensus before starting

Decision Criteria

When in doubt, ask: "Can we ship it?" If yes, ship it.

  1. Does it deliver value to users? → If yes, implement it
  2. Can we write tests for it? → If yes, quality is assured
  3. Can it be done in a day? → If yes, start without discussion
  4. Is it reversible? → If yes, we can roll back — ship without fear

Current Status of All Products

ProductStatusNext Action
StayFlow (vacation rental SaaS)SSR complete, 40 routes implementedBeds24 API integration, Stripe payments
StayFlowApp (production)Live, 500+ propertiesKPI monitoring, acquisition funnel optimization
chatweb.ai / nanobotRunning in productionExplore Mode improvements, cost optimization
IronClaw/OuroborosRunning autonomouslyAdd skills, improve trust model
MisebanAI (retail AI)Phase 1 MVP in developmentAPI refactor commit, inference pipeline
JitsuFlow (jiu-jitsu)MVP completeStart beta testing, dojo partners

What Changes with AI-Driven Development

Traditional flow:

  1. Write requirements in Jira (30 min)
  2. Design review meeting (1 hour)
  3. Implementation (2-5 days)
  4. Code review (1 day waiting)
  5. QA (1 day)
  6. Deploy (half a day)

AI-driven flow:

  1. Describe requirements to Claude Code (5 min)
  2. AI designs → implements → generates tests (30 min - 2 hours)
  3. Human reviews (15 min)
  4. Deploy (automatic)

Result: 7-12 days → Half a day to 1 day

A Request to the Team

  • Learn how to use AI tools. This is not optional — it's mandatory.
  • "AI-written code can't be trusted" is a thing of the past. With tests, quality is assured.
  • Don't spend time on minor technical debates. Focus on shipping.
  • Sprint results will be published on this blog, doubling as external communication.

Next sprint review: Will be reported on this blog.