Generative AI
39,057Claude Code messages3.5MClaude Code tokens242Claude Code sessions89active days on Claude Code
AI Capability Engineering
I help organizations learn how to build and deploy AI products.
Together we build a real AI product from business need to production. The first delivery solves a problem. The second one becomes easier. The third one belongs to your team.
01 / Positioning
Beyond AI consulting
I don't deliver presentations, proofs of concept or isolated agents. I embed with your team to transfer a practical capability: observing opportunities, designing workflows, building AI products, deploying them safely and repeating the process.
DINUM
Public sector · AI transformation
- Designed AI-assisted tools for civil servants across multiple French ministries.
- Facilitated adoption workshops with non-technical government teams.
- Mapped decision workflows to identify AI integration points.
- Built transparent, explainable AI interfaces trusted by civil servants.
A field-tested ability to deploy AI in high-stakes environments with complex stakeholder ecosystems.
Stack / Architecture
Transformation Stack
From tools to capability.
Tools alone do not create capabilities.
- InfrastructureIsolated tools and disconnected data.
- SoftwarePilot apps that never scale.
- ContextKnowledge fragmented across teams.
- WorkflowManual handoffs between steps.
- OrganizationUnclear ownership of AI outcomes.
- CultureExperimentation stays with a few.
- LearningLessons don't carry over.
03 / Principles
Every engagement creates a new capability
- 01Build with your real business data.
- 02Ship a production-ready AI product.
- 03Work alongside your team.
- 04Document everything.
- 05Transfer the methodology.
- 06Make the next project faster than the first.
MBA / 2026
AI Capability Engineer, Design Engineer and AI Product Builder.
I help organizations turn business challenges into deployed AI products. Together, we build a first product end to end — from opportunity to deployment — so teams can design the next one faster, with greater autonomy and confidence.
My experience across large organizations, the public sector, startups and higher education allows me to combine strategy, execution and knowledge transfer. I do not just deliver a product: I transfer a way to build, deploy and evolve the organization’s AI capabilities.
04 / Engagements
Typical engagements
- AI Opportunity Discovery
- AI Product Building
- Internal AI Agents
- Workflow Automation
- Knowledge Systems
- Executive & Team Enablement
Track record
A practice measured through real-world use.
These figures come from my working environments: AI assistants, prototypes, deployments and code contributions.
Platform counters, as of September 28, 2026.
39,057Claude Code messages3.5MClaude Code tokens242Claude Code sessions89active days on Claude CodeProduct & prototyping
118apps created on AI Studio
879v0 prompts over 12 months
279Netlify projects created
225days on CodexCode
3,454GitHub contributions in 20252,105GitHub contributions in 2026+5,559visible contributions, 2025–2026
1,430days on ChatGPT2,105 contributions in 2026
github.com/tewfiqJanFebMarAprMayJunJulAugSepOctNovDec
A volume of practice is useful only when it becomes understandable, usable and transferable systems.
05 / Method
AI Product Building E2E
- 01Observe
- 02Model
- 03Build
- 04Deploy
- 05Learn
- 06Build Again
06 / Outcome
What changes after we leave
Before
- One AI idea.
- External dependency.
- Slow experimentation.
- Scattered knowledge.
After
- A deployed AI product.
- A reusable operating method.
- Teams able to build the next solution.
- A continuously growing AI capability.
The first AI product is the project. The second is the proof. The third is your new capability.
Build one. Learn forever.
The objective isn't to deliver software. It's to help your organization become better at continuously building AI products.
Book an AI Product Clarity Call