Maciej
Co-founder · PhD in mathematics
In AI since 2012. Hands-on CTO and engineering leader who has introduced agentic engineering practices across multiple teams.
LinkedInInstall an Agentic SDLC in your engineering team. In 4 weeks.
Your developers already use coding agents in different ways. We turn those individual workflows into one shared engineering system — on your real product and backlog.
Book a 30-minute call
- 4-week implementation pilot
- Your repository and backlog
- A system your team owns afterwards
AI adoption without a system
Individual productivity does not automatically become team capability.
- Uneven adoptionEveryone uses agents differently.
- Review overloadCode arrives faster than the team can validate it.
- Trust gapAutonomy grows faster than quality controls.
- No shared learningEach developer improves a private workflow.
- No numbersAI usage rises, but impact on delivery is unclear.
The missing piece is the engineering system around the agents.
An operating system, not more training
We install the shared context, workflows and quality gates that make agent work repeatable across the team.
Shared SDLC
One path from idea to release.
Context & skills
Reusable instructions embedded in the repo.
Guardrails
Explicit boundaries for agent autonomy.
Testing
Feedback loops agents can use themselves.
Review
Machine checks plus targeted human judgment.
Measurement
Lead time and cost per delivered feature.
Four weeks. One real team. Real backlog.
Each week combines a workshop, real engineering work and a review of what happened.
- 1Week 1
Foundations
Map the SDLC and define autonomy.
SDLC map + guardrails - 2Week 2
Spec & skills
Make work delegatable and reusable.
Templates + first skills - 3Week 3
Delegation
Review, tests and Definition of Done.
First end-to-end task - 4Week 4
Handover
Your team runs the system.
Owner + 30-day backlog
What you keep
The capability stays in your company.
- Documented Agentic SDLC and playbook.
- Skills library and repository context.
- Specification and tech-design templates.
- Agent Autonomy Matrix and guardrails.
- Definition of Done and AI review policy.
- Measurement framework and 30-day backlog.
Built by engineers who run this in production
We are hands-on practitioners. We build software with agents, design the workflows around them and help engineering teams make those workflows repeatable.
Łukasz
Co-founder · Data architect
Serial founder and hands-on engineer building data platforms with agentic coding at the core of his daily work.
LinkedInWho this is for
A good fit if you
- already have developers experimenting with coding agents,
- want one predictable team process,
- have real backlog work for the pilot,
- want the capability to stay in-house.
Not a fit if you
- want a one-day prompting workshop,
- want us to implement your backlog,
- want autonomy without engineering guardrails.
Questions CTOs ask us
Anything else? Write to us.
Is this Claude Code / Cursor / Codex training?
No. We build the engineering system around the tools: context, skills, autonomy rules, tests, review and measurement.
Isn't this just vibe coding?
No. Work starts from a specification, follows explicit boundaries, and ends with tests, review and human acceptance.
Won't more agent code make review worse?
Only if review stays unchanged. We redesign what machines check and where human judgment is actually required.
Will we depend on you afterwards?
No. In week four your team runs the process and takes ownership of the system.
Turn individual AI usage into a team engineering capability.
Four weeks. One product team. Your codebase. Your backlog.