Enterprise AI Architect

Dejan Guberinic

Agentic AI & Software Development Transformation

I help large organisations to deploy generative AI and AI agents safely and productively — particularly in software development and knowledge work. Focus: enterprise architecture, agentic SDLC, context engineering, governance, security, adoption and scaling AI across teams.

Focus enterprise agentic AI transformation, and within that agentic software development in particular. Not “expert on everything to do with AI”.

Three pieces of evidence, not three claims

Every statement in this portal has a source — a reference, a certificate, a repository or a passed check-in. What has no source is not in here.

Accessful GmbH

AI in production

Co-founder, Managing Director and Co-CTO

Platform in production use with clients from automotive, insurance, financial services and public administration.

SIGNAL IDUNA Group · self-declaration

Agentic SDLC inside a corporate

  • Introduction and further development of agentic software development within the company.
  • Contribution to a leading technical team responsible for planning, coordinating and delivering a proof of concept for agentic software development.
  • Production of playbooks, ways of working and guidelines for AI-assisted and agentic development practices.

iSAQB

Architecture with proof

CPSA Foundation Level — Examination certificate (passed), Examination 26.04.2023, Hamburg.

T 20 · M 30 · C 40 = 90

The number nobody else shows

On 10.08.2026 the domain knowledge for the target role was measured across 20 knowledge questions and 5 architecture cases — no aids, assessed by an agent instructed not to flatter.

2.65 / 4 Weighted overall score
3 / 4 Target
3 Areas at level 2 — of 7 · 40 % of the weighting combined

Target not yet reached

The score is public because it will be measured again. Every two weeks the agent tests against demonstrated answers and records the result — upwards or downwards. A level nobody can evidence is not shown here.

This portal maintains itself

Content, CV and learning status live as Markdown in a Git repository. An AI agent updates them on a two-week cycle, every change is a commit, and the website is generated from it. The change history is public.

How that works →

See the full picture

Skill matrix with evidence, career history and references, projects, learning path, CV and terms sit behind a personal access link — one per recipient, revocable, with an expiry date.

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