Accelerating Bruhn NewTech & CBRN-Analysis NextGen with AI
Two decades as CTO, Head of Technology, and board member at SaaS and tech scale-ups.
Software developer, content creator, VP Growth at SaaS scale-up, 10 years as P&G Marketing Director.
SIDCOM helps organizations adopt AI through assessment, implementation, and hands-on training. We build AI solutions ourselves, every day.
Accelerate the migration from legacy C++ to a modern web-based CBRN-Analysis. Ship NG faster without cutting corners.
Higher development speed without sacrificing code quality, maintainability, or architectural integrity.
Move from individual experimentation to shared AI practices across the whole organization. Less friction, more output.
↺ We'll come back to these throughout the day
Where applied AI is today — and its impact on tech, people, and our macro environment.
Impressive demos. Frequent hallucinations. Copy-paste workflow.
Ask → AnswerReliable models integrated into tools. Suggestions, drafts, code completions.
Suggest → ReviewAI plans, executes, and delivers. Multi-step tasks directed by you.
Instruct → DeliverAI acts independently. Scheduled, event-driven, self-correcting. You monitor outcomes.
Define → MonitorNovember 2025 — Peter Steinberger builds a local AI agent connected to WhatsApp. In one hour.
January 2026 — Published. 34,000 GitHub stars in 48 hours.
February 2026 — OpenAI recruits Steinberger. Project moves to an independent foundation.
247,000+ stars within six weeks. The fastest-growing open-source project ever.
Jensen Huang, NVIDIA CEO, on stage:
“Every single company in the world today has to have an OpenClaw strategy.”
NVIDIA launches NemoClaw — the enterprise version of OpenClaw with security and privacy routing built in.
The skill that matters is no longer how fast you type or how many hours you put in. It's how clearly you can describe what you want — and how well you evaluate what you get back.
The goal is not replacement. It's amplification — AI handles the execution so you can focus on judgment.
When AI can write code, it can build its own tools — and that unlocks everything else.
How AI changes the way your team builds software.
You describe the intent. Claude delivers working code.
Developer writes all code, reviews own work, maintains documentation manually.
AI suggests completions, you review and accept. Faster iteration on known patterns.
You describe the intent. AI plans, writes, tests, and delivers working code.
The shift isn't about replacement — it's about moving from line-by-line coding to directing outcomes.
AI reads existing C++ patterns, suggests web equivalents, restructures into bounded contexts.
High ImpactAutomated test suites from existing code behavior. Catches regressions before they ship.
Quick WinAI generates docs from code. Accelerates onboarding, reduces knowledge silos.
Quick WinConsistent review against architectural standards. Catches issues humans miss at scale.
OngoingNew developers get AI-guided codebase walkthroughs. Months compressed to weeks.
High ImpactAddressing the concern: does faster mean sloppier?
Every commit reviewed against your architectural standards. No style drift, no shortcuts.
Test coverage that scales with your codebase. AI generates tests as code is written.
Code style enforcement, naming conventions, documentation requirements — applied uniformly.
Domain-driven design boundaries enforced automatically. Bounded contexts stay bounded.
Dorte's benchmark: “faster without sacrificing quality and maintainability” — this is how.
2–3 developers experimenting is a start. Here's how to make it a team capability.
What works for one developer should be available to all. Shared prompts, patterns, and learnings.
Common approaches to code review, testing, and documentation with AI. No more one-off experiments.
Pick the right tools, make them available to everyone, and invest in training. Consistency matters.
Track velocity, quality, and developer satisfaction. Data drives adoption decisions.
10 minutes — grab a coffee, stretch your legs.
Back at XX:XXFrom individual experiments to organizational capability.
Your value shifts from doing the work to knowing what work to do — and evaluating the result.
This will feel unfamiliar. The people who acknowledge that adapt faster than those who pretend it's not happening.
Every week brings new capabilities. The gap between curious and passive widens fast.
What mattered yesterday may not matter tomorrow. Willingness to change direction is a core skill.
Models, tools, and integrations.
Drive AI enablement, help deliver working solutions.
Training, mindset, capability building.
Each function owns its AI agenda. Not an IT project.
Set the tone. Set targets. Drive the mandate.
Map friction, identify highest-impact opportunities
Pick 2–3 opportunities, deliver results, learn fast
Scale what works across the organization
Trying to transform everything at once. Start narrow, prove value, expand.
AI projects without a stakeholder accountable for outcomes drift and die.
Giving people tools without teaching them how to use them effectively.
AI is only as good as the context it receives. Clean inputs, quality outputs.
Everyone using different tools differently. No shared patterns, no compounding.
Build the muscle and the mindset to adapt
Lead execution with your own people
Sustain through change, not just the first wave
Accelerate the ramp-up
Faster capability building
Execute on specific things to get momentum going
Identifying and prioritizing the friction points that slow you down.
Based on your survey responses, we've pre-loaded these friction points. Let's validate, add to, and prioritize them together.
Weak documentation means new developers take months to become productive
Converting legacy code to bounded contexts is time-consuming and error-prone
Maintaining the Windows product consumes half your engineering capacity
Individual experiments don't compound into team capability
Critical knowledge locked in senior developers' heads
Different coding styles and quality levels across the codebase
From today's workshop to real change.
Identify friction points, map AI opportunities, define success metrics
Select and deploy tools, create AI-enabled workflows, quick wins first
Hands-on training, shared practices, champion enablement
Embed across teams, measure impact, iterate on what delivers value
Questions, thoughts, ideas — the floor is yours.