From Solo Founder
to Full Company.
Building with agentic AI on AWS. One person. Twelve AWS services. Six departments running in production. This is the stack I actually use every day.
Context, not credentials.
I run every function of a startup using AI on AWS. Marketing. Sales. Engineering. Finance. Content. Operations. Same person. Same AWS account.
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20+Years in network & security architecture AT&T · Infosys · Kyndryl
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EDULecturer at TU Munich & Politehnica Bucharest Teaching what the industry is doing now, not five years ago
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📚Author of a 4-volume book series "Generative AI for Networking Engineers"
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🚀Founded vExpertAI mid-2024 Self-funded · Munich-based · Built entirely on AWS
The point
I run every function of a startup using AI on AWS.
Marketing. Sales. Engineering. Finance. Content. Operations.
Bedrock · SageMaker · Lambda · Step Functions · Neptune · S3.
This is my daily stack.
The numbers behind a one-person company.
// My AWS stack
A 5-layer guild — fully AWS-native.
Each layer has one job, one set of AWS services, and one clean interface. The same pattern scales from a single agent to a coordinated multi-agent system.
Orchestration
Multi-agent coordination, routing, state management.
Step Functions · Bedrock AgentsFoundation Models
Reasoning, generation, tool use via Action Groups.
Bedrock · Claude · MistralKnowledge
Graph relationships, RAG retrieval, document store.
Neptune · Bedrock KB · S3Execution
Containerised agent tasks, serverless compute.
Lambda · ECS FargateObservability
Monitoring, cost tracking, responsible-AI controls.
CloudWatch · Bedrock GuardrailsHow each function actually runs.
Every team in a normal company maps to a small set of AWS services plus a few well-trained agents. Here's what's behind each door.
📣 Marketing & Content
solo founder content machineOutbound automation
Bedrock generates personalised sequences. Lambda orchestrates scheduling. EventBridge triggers follow-ups automatically.
Technical content
Bedrock (Claude) drafts from my outline. S3 stores templates and brand voice. 3× faster than writing from scratch.
LinkedIn (DACH)
Bedrock calibrates tone for the German market. 50+ prompt iterations stored in S3. Cultural nuance, not robotic output.
4-volume book series
"GenAI for Networking Engineers." Bedrock-assisted research & structuring. SageMaker for domain fine-tuning.
💼 Sales & Outreach
AI doesn't close deals — it gets me to the table 10× fasterDealMind — real-time sales coach
Bedrock Agents feed context, objection handlers, and next-best-action during live calls.
Pipeline automation
AI-powered outbound at scale. Step Functions orchestrate multi-step prospecting workflows end-to-end.
Proposal generation
988-paragraph Airbus DS curriculum generated with Bedrock. Days, not weeks. Knowledge Bases feed the domain context.
Pipeline intelligence
Bedrock analyses conversations, suggests priorities, drafts follow-ups. Neptune maps relationship graphs.
🛠️ Engineering & R&D
AI writes production code · I architect & review5-layer agentic guild
The full pattern: Step Functions for flow, Bedrock Agents with Action Groups calling AWS services, Neptune for relationships.
NeT/RED — hybrid cyber platform
Hybrid red/blue-team cybersecurity platform. Network digital twin running on Containerlab on EC2.
Domain fine-tuning
Mistral-7B on SageMaker for NOC/SOC domain data. Where prompts hit their ceiling, fine-tuning takes over.
Infra-as-code & cost control
CDK deploys everything — reproducible, versioned. Cost Explorer + budgets keep the full stack under $500/mo.
⚙️ Operations & Knowledge
the unsexy stuff that makes everything else possibleKnowledge pipeline
599 R&D conversations classified and searchable via Bedrock Knowledge Bases. S3 as the document store, auto-indexed.
Finance & admin
Bedrock drafts contracts, proposals, invoices. Lambda automates formatting. I review and sign.
Daily automation
EventBridge triggers morning briefings. Bedrock summarises overnight emails. Lambda prepares priority lists.
Guardrails
Bedrock Guardrails enforce content policies. CloudWatch monitors cost & latency. IAM least-privilege across all services.
Every hour, an AWS service does the heavy lifting.
This is a real Tuesday. Same shape on a Friday. Most of the work is finished before I open my laptop.
EventBridge triggers Lambda
Bedrock summarises overnight emails into a single morning brief.
Daily research drop
Knowledge Bases surface the 3 papers that actually matter, out of 20+ new uploads from arXiv & co.
Customer prep
Bedrock Agents prep briefing docs from the Neptune relationship graph — every meeting walks in pre-loaded.
Content drafting
Bedrock drafts the Substack article from a bullet-point outline stored in S3.
NOC/SOC inference
SageMaker fine-tuned model runs domain-specific inference for network & security analysis.
End-of-day workflow
Step Functions run follow-ups, CRM updates, and tomorrow's priority list. Then I close the laptop.
AWS didn't replace my work. It replaced the work that kept me from doing my real work.
Topics to inspire your customers on practical AI.
If you're hosting a customer day, an internal kickoff, or an enablement session — these are the four conversations I run most often. Each one is grounded in a working system, not a slide.
The daily AI research agent
A custom-built agent that monitors arXiv, Hacker News, and YouTube every morning — and lands a 3-paper summary in your inbox before coffee. Live walkthrough of the pipeline, prompts, and failure modes.
5-agent system for network & security ops
How a small fleet of specialised agents handles complex network and security operations — including autonomous fault detection, triage, and remediation. The orchestration patterns, the guardrails, and what breaks first.
Digital twins for pre-validating AI actions
Why letting agents touch production directly is the wrong question. Using network digital twins (Containerlab on EC2) to pre-validate every AI-generated action before it reaches a real device. The blast-radius math, end-to-end.
Local AI for DORA, NIS2 & the EU AI Act
How to deploy AI platforms locally — meeting strict DORA, NIS2, and EU AI Act requirements — without sending a single byte of customer data to an external service. Architecture, trade-offs, and the parts that surprise everyone.
Honest lessons. No hype.
// Do this on AWS
- ✓Start with Bedrock — don't build infra first.
- ✓Use Knowledge Bases before reaching for fine-tuning.
- ✓Lambda for glue, Step Functions for flow.
- ✓Bedrock Guardrails from day one — not day 90.
- ✓Check Cost Explorer weekly. Surprises compound.
- ✓Human reviews everything customer-facing.
// Don't do this
- ✗Don't fine-tune when prompting still works.
- ✗Don't build agents before you've nailed the prompts.
- ✗Don't skip IAM least-privilege. Ever.
- ✗Don't ignore Bedrock Guardrails.
- ✗Don't confuse AI speed with AI accuracy.
- ✗Don't wait for the "perfect" service launch.
What this actually costs a bootstrapped startup.
Six departments. Production workloads. Real customers. Numbers, not vibes.
That's less than one freelancer's lunch budget — for an entire company's AI infrastructure.
AI on AWS won't replace your company.
But a company using AI on AWS
will replace one that doesn't.
You don't need a 50-person AI team. You need one person, one AWS account, and the willingness to start tomorrow.