Cem Dinc
Let's talk
  • Dipl.-Ing. Electrical Engineering
  • 20+ years of experience
  • Germany

Cem Dinc

01Engineering.02Quality.03Artificial Intelligence.

Two decades of engineering, testing and quality – now applied to artificial intelligence. Responsible, traceable, effective.

Let's talk The story
Scroll

[01]Story

Experience that compounds.

From electrical engineering to artificial intelligence – not a change of direction, but a signal chain. Every stage builds on the one before.

  1. Stage 01

    Engineering

    It starts with electrical engineering: signals, circuits, physical limits. The habit of measuring things before judging them.

  2. Stage 02

    Embedded / Systems

    Software that runs directly on hardware. Real time, resources, interfaces – and systems that have to work inside a vehicle.

  3. Stage 03

    Software

    From circuit to architecture: requirements, structure and maintainability start to matter more than any single line of code.

  4. Stage 04

    Testing

    Testing means questioning assumptions systematically. Test strategy, test management and the question of when something is truly good enough.

  5. Stage 05

    Quality

    Quality is built into the process, not inspected in at the end. Automotive SPICE, quality management and assessments make it demonstrable.

  6. Stage 06

    Leadership

    Technical leadership and management: responsibility for teams, results and decisions – and eventually for a company of my own.

  7. Stage 07

    Artificial Intelligence

    AI does not replace this experience. It extends it. Evidence, risk management, change control and clear accountability – what has proven itself in engineering and quality holds for AI as well.

AI does not replace experience. It extends it.

[02]Expertise

Ten fields. One standard.

Understanding systems, proving quality, deploying AI responsibly. The fields are connected – which is why they belong together.

  1. Using AI where it genuinely improves work – with an engineer’s eye for requirements, risks and verifiability.

    • Use Cases
    • LLM
    • Automation
    • Prototyping
    Talk about this topic

  2. Rules, roles and processes for responsible AI – grounded in quality management and the EU AI Act.

    • EU AI Act
    • Policies
    • Risk
    • Compliance
    Talk about this topic

  3. Quality as a system: processes that work day to day, not only during an audit.

    • Processes
    • Audits
    • Improvement
    Talk about this topic

  4. Making software quality measurable – from requirements through architecture to verification.

    • Requirements
    • Architecture
    • Metrics
    Talk about this topic

  5. Test strategies, organisation and management that expose risk instead of collecting checkmarks.

    • Strategy
    • ISTQB
    • Test Management
    Talk about this topic

  6. Assessing and improving process capability in automotive development – practical and focused on the actual product.

    • Assessments
    • Gap Analysis
    • Improvement
    Talk about this topic

  7. Understanding systems in which hardware, software and safety are inseparable.

    • ISO 26262
    • ISO/SAE 21434
    • Systems
    Talk about this topic

  8. Independent technical evaluation of software, embedded systems and electronics – as an expert.

    • Gutachten
    • Software
    • Electronics
    Talk about this topic

  9. Advisory work and interim project responsibility – where engineering, quality and AI meet.

    • Advisory
    • Interim
    • Projects
    Talk about this topic

  10. Passing on knowledge so teams can apply it themselves – from workshops to expert formats.

    • Workshops
    • Coaching
    • Formats
    Talk about this topic

Standards & frameworks

  • Automotive SPICE®
  • ISO 26262
  • ISO/SAE 21434
  • EU AI Act

[03]Thought leadership

KI mit Verstand.

AI changes technology. Responsibility remains.

“KI mit Verstand” (AI with judgement) is an ongoing thought-leadership project by Cem Dinc. Artificial intelligence changes tools, processes and decisions. Yet organisations already have structures built for exactly that: quality and risk management, change control, approvals, audits, clear accountability and evidence. AI is no reason to discard them – it is a reason to evolve them.

How do we integrate AI into existing organisations without giving up quality, traceability and accountability?

Three focus areas

  1. 01 Engineering × AIAI in technical development, test and quality processes.
  2. 02 Quality × GovernanceQuality management, human oversight, change management, approvals, evidence and governance.
  3. 03 Regulated AIThe AI Act, governance and integration into regulated organisations and existing management systems.

The book

KI mit Verstand – Die ultimative Anleitung für den Einsatz von KI in Unternehmen.

In progress

A knowledge ecosystem

BookLiving BookArticlesPodcastVideosPractical tools

Talk about AI with judgement

[04]Projects

What I’m building.

Companies, publications and formats of my own – each project its own story.

Cem Dinc

Profile

Cem Dinc

Degree
Dipl.-Ing. (FH) Electrical Engineering
Experience
More than 20 years
Expert
DESAG-certified expert – IT systems / applications
Company
Founder & owner · DiNC-POSiTiVE
Based in
Lüdenscheid, Germany

[05]About

An engineer who treats quality as a mindset.

I am a graduate electrical engineer (Dipl.-Ing. FH) and have spent more than twenty years in technical and leadership roles – across embedded systems, software, software quality, testing and test management, automotive and Automotive SPICE, quality management, technical leadership and management.

Today I carry what I learned there over to artificial intelligence: quality, evidence, risk management, change control and clear accountability. As founder of DiNC-POSiTiVE and an independent expert, I help organisations integrate AI into their existing engineering and quality structures – instead of building around them.

  • Engineering
  • Embedded
  • Software
  • Testing
  • Quality
  • Leadership
  • Entrepreneurship
  • Artificial Intelligence

Qualifications

Expert services
DESAG-certified expert – IT systems / applicationsDESAG – German association of independent experts (opens in a new tab)
Process quality
intacs™ Provisional Assessor Automotive SPICE®
Testing
ISTQB® Certified Tester – Advanced Level Test Manager
Architecture
iSAQB® CPSA-F – Certified Professional for Software Architecture

Domains & standards

  • Automotive SPICE®
  • ISO 26262
  • ISO/SAE 21434
  • EU AI Act

Dipl.-Ing. (FH) Electrical Engineering
Founder & owner · DiNC-POSiTiVE

PersonalMy brother: Cemil Dinc (opens in a new tab)

[06]Resources

Sources & resources.

Selected official sources, standards and institutions I rely on for my work, publications and podcast research.

AI regulation

AI governance & standards

AI & cybersecurity

Automotive & engineering

Quality, testing & architecture

[07]Contact

Let's talk.

Tell me what it’s about. I reply personally.

Request a meeting Request a call back

Direct

01What is it about?
02Your message
Preferred way to reply

Request a meeting

Choose format, length and a preferred slot. This is a request – the meeting is confirmed only once I reply personally by email.

Format
Length

Day

Time

Your requested slot –

Time zone: Germany (CET/CEST)

Request a call back

Leave your number – I will call you back in your preferred time window.

When suits you?
Let's talk