Christian Mülder

73% of enterprise customers choose Anthropic. In the EU? CLOUD Act hits all US providers. We run agentic workflows on self-hosted GPUs with open-source models. No lock-in. GDPR-compliant by design. Not "best model" — "which one survives the next regulation shift?"

@bezalelnet 💯 %

@CMuelderAI 88% reporting incidents vs 14% with security approval is the stat that should terrify every enterprise deploying agents right now. Security can not be an afterthought when you are giving software autonomous decision-making power

1/4 88% of enterprises report AI agent security incidents. Only 14% have security approval for their agents. The gap between those two numbers is where breaches happen.

4/4 Step one is boring but essential: inventory. You can't secure what you can't see. Map every agent, every data flow, every tool call. Then decide what stays and what goes.

3/4 Prompt injection — manipulating AI through crafted inputs — went from research to production incidents in 12 months. Most teams treat agents like SaaS tools. They're not. They decide, access data, and act. That needs its own security model.

4/4 This should be automated. Missing test case? Flag it. Outdated after requirement change? Surface it instantly. Not three weeks before the audit. Traceability should be a byproduct of your workflow. Not the most expensive line item on the assessment invoice.

3/4 Worse: the link exists but the requirement changed. Test case still passes — but tests something that's no longer valid. At 500 requirements, no human catches that manually.

1/4 ASPICE Level 2 doesn't fail because of bad engineers. It fails because of manual traceability. Requirements in DOORS. Code in Git. Tests in Excel. Traceability maintained by one person. Manually. Everyone hopes that person doesn't quit.

@ashvinkolhe For me it will always be VALUE-first!

@CMuelderAI Future ERP = AI-first, not process-first

1/4 GPT-5.4 can now operate your computer. Click buttons. Fill forms. Run legacy ERP systems. Live via API. Everyone talks benchmarks. Nobody asks: what happens when an AI agent has mouse and keyboard access to your SAP?

4/4 Computer Use will transform enterprise operations. No doubt. But the companies that win are not the ones who deploy fastest. They're the ones who deploy with guardrails that actually work. Speed without governance is just a faster way to break things.

3/4 The real question for CISOs: who controls what the agent clicks? IAM systems were built for humans. Humans don't execute 200 actions per minute or copy customer data into 4 systems at once. Agents need their own access model. Not shared API keys.

5/ The question nobody's asking: If DeepSeek V4 delivers on these specs — what happens to pricing? Western frontier models charge $15-75/M tokens. DeepSeek charges under $2. At trillion-parameter scale. The race to zero isn't slowing down. #AIModels #EnterpriseAI #DeepSeek

4/ For enterprise: DeepSeek R1 already proved Chinese models can match Western performance at a fraction of the cost. V4 with 1M context + multimodal could make that gap even wider. Especially for document-heavy enterprise workflows.

3/ The real story isn't the model. It's the hardware. V4 is optimized for Huawei and Cambricon chips. Not NVIDIA. This is the first major model built specifically for non-Western AI infrastructure. If it performs, the NVIDIA dependency narrative changes.

2/ The architecture: trillion total parameters, ~32B active at once (Mixture of Experts). Image, video, and text — native multimodal. Not bolted on. First trillion-parameter model from a Chinese lab. Built to compete with GPT-5 and Gemini Ultra.

1/ DeepSeek V4 is about to drop. Trillion parameters. Native multimodal. 1M token context. Optimized for Huawei Ascend chips — not NVIDIA. China's answer to GPT-5 and Gemini. Here's what matters for enterprise.