Discipline without the hassle.
Disciplin.Run keeps your AI coding agent from silently breaking what already works.
Stop vibe coding. Start vibe spec'ing
4
MCPs in 30 days
7
Guardian Agents
51 min.
Ingest 17K lines of code
What they said
After seeing Disciplin.Run
That's gonna blow a lot of minds.
That's incredible.
The spec reverse-engineering and the
orchestrator setup were the parts that really stuck with me.
Elliott Johnson
AI-Stack indie builder
Built AI systems for 3 years. The feature regression problem is real —
lost a working reply handler twice in one week. If there is an 8-step
workflow, and it makes a mistake at the second and third step, it
compounds with each and every step. We really need this.
Usama Tanveer
AI Engineer
It's a great product.
It covers the gap. $100/month per repo? 100% [worth it]. $200/month per product manager? 100%.
Evgeny Bob
Director AI, Hilton
POC overnight. Product in 30 days.
Out-of-band structure alongside Claude Code, never in your way.
The Problem
Your AI house of cards is just one update from collapse. Untouchable. Un-onboardable. Un-refactorable.
Our Solution
Three AI managers above Claude Code:
Product, QA, Engineering.
Out-of-band. Release-gated.
Specs and QA Tests in your repo, owned by you.
LeanSpecs with reverse-engineered and inferred TubeMail Specs May 3, 2026 (549 Behaviors in total)
Open source TubeMail showing list of Claude workers with activity and context size
Quartermaster orchestrating successful release of jjstack to public with MIT license
The Cleanup Tax Compounds
Decades of wisdom from running Local, off-shore, outsourced and AI team
AI generates 1000+ lines of code per day
After a bit of vibe coding the cleanup tax outgrows the build
A viral r/vibecoding post April 2026:
Tried to refactor it myself last week. gave up after 2 hours. the thing is so tangled that touching one part breaks something completely unrelated.
2026 is tech debt at AI scale.
The longer you wait, the steeper the fix.
Speed: Free. Discipline: Scarce.
AI will revolutionize how we code, not how we structure
1000x
IDC projects agent token loads grow a thousandfold by 2027. Vendors that hit the LLM per keystroke die under that curve.
40%+
Gartner projects more than 40% of ungoverned agentic AI projects will be canceled by end of 2027. Autonomous agents without hard gates ship code that looks right and breaks at integration.
-15%
IDC: companies that skip data and process discipline in agentic deployments hit a 15% productivity loss. Speed without structure is regression.
70%
IDC: 70% of developers will partner with autonomous AI agents by 2030, shifting human work toward planning, design, and orchestration. The job moves up the stack.
58%
451 / S&P Global VotE: 58% of organizations are actively seeking to implement agent capabilities. The market is shopping today, not theorizing.
$1.5T
IDC: total AI spend reaches $1.3 trillion by 2029. Agentic systems claim roughly half.
Keep coding close. Keep QA closer.
My father was offshoring QA to India for CSC from 1980 to 2000. I've run offshore teams since 2004. The lesson didn't change: Control QA, you control the user-experience.
AI coding is offshoring at 1,000x speed. Same failure mode, new substrate.
Old lesson. New clockspeed. Same discipline.
Seven AI Guardian Agents. One hard-gated harness.
Decades of wisdom from running local, off-shore, outsourced and AI team
Leanspecs Prod. Mgr
Source of Truth
Specs from Code
Spec Grooming
Iris QA Mgr
Generates and runs tests
BDD, TDD, E2E, Red2Green
Tests Unit-tests, Release Gt
Quartermaster EngMgr
Orchestrate team.
Keep AI agents honest
Coder
Developer.
Trained on your teams Coding DNA
PR-Reviewer
Mission, Architecture and requirement alignment
Not just syntax check
Actuatrix
Comptroller
Independent KPI agent
Architrix
Systems Architect
Architectural diagrams
Data Dictionary
TubeMail for Claude
Communication between Claude code sessions
Open Source: MIT
Rescue Mode
1. Point at your repo.
2. Import Code to Specs - multipass ingestion and automatic clean-up - 17K Lines in 41 minutes
3. 2-3 hours - human spec grooming, using the AI Assisted tools, Vibe Spec'ing
4. 30 minutes Iris-QA generates E2E tests based on your new specs. - Tests live in your repo, you own them
5. run the tests - find issues, include the CLI [HALT|LAUNCH] in your release release pipeline
See screenshot above showing Tubemail's 17K-line import.
Dev Mode
1. Point at your repo.
2. Import your JJStack/Gstack docs to Specs
3. 30 min - human spec grooming, using the AI Assisted tools, Vibe Spec'ing for Behavior-Driven-Development (BDD)
4. 30 minutes Iris-QA generates End-to-End (E2E) tests based on your new specs. - Tests live in your repo, you own them
5. Test-Driven-Development (TDD: Code test first, see them fail, then code until test passes a.k.a. Red-to-green)
6. Actual implementation of both QA Tess and coding uncovers weaknesses and uncovered corner cases in the specs, automatically feeds back into the specs for overall improvement.
7. User Acceptance Testing uncovers needed tweeks tell your AI the changes you want to the Specs. then run the loop again for improved product.
About the Founder
Jesper Jurcenoks. 45+ years of coding, 24 years cybersecurity product leadership. 3 exits — Interspace (small-business ISP, Copenhagen, acquired), netVigilance (10 years profit, acquired), Critical Watch (acquired by Alert Logic). Plus CPO at Group-IB — P&L for the largest of 5 divisions, ~50% of company revenue.
Most recently VP Product at CloudOne Digital ($360M, 1,300 employees, LiquidWeb / Nexcess / Servers.com / Stellar). Seven months in I saw the same pattern at scale that I'd seen on every dev team I'd ever run: without coherent strategy and daily discipline to communicate it, no volume of talent produces a coherent outcome. I left to build the tool that makes coherence automatic.
In April 2026 I shipped 4 production MCP servers solo in 30 days under the discipline framework I'm now selling. The only thing that prevented me from losing my own codebase to AI was the system I built to prevent it.
InboundSavvy is my 12-year mission — low-cost marketing tools for small businesses Silicon Valley will never serve. Disciplin.Run exists to stabilize InboundSavvy. InboundSavvy exists to give Disciplin.Run a real production stress test. Each makes the other better.
I authored the Extended Kano prioritization model. The same framework drives LeanSpecs's spec-sharpening loop.
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