What I'm seeing across the industry right now is that the biggest bottleneck to AI adoption isn't model capabilities. It's data infrastructure. Today, we're expanding the Eon Data Foundation with the launch of Eon Yukon, a new serverless data engine purposely built to change that. AI agents need fresh, contextualized data to act. Specialized models need a continuous feed of data and feedback to improve. Both are still served by a stack, an architecture, and methods built for dashboards: -Spark and Flink clusters sized for peak, plus compaction jobs to keep tables usable. -A pipeline and a copy for every consumer, staged bronze to silver to gold. -Hand-written jobs, wired together by an orchestrator and kept alive by specialists. The result: shipping data is complicated, risky, and expensive. While coding agents ship apps in hours, they rarely build or run data pipelines. The data is too volatile, and a mistake costs too much. With Yukon, data moves from ingestion to processing to serving in one continuous flow, without the infrastructure and pipelines traditionally required to connect them. Events become compacted, sorted, deduplicated Iceberg tables within seconds. Real-time aggregations run inline, with fully managed state. Agents and applications can access fresh data with sub-millisecond latency through a Redis-compatible API or through our SQL and spark compatible query engine. Beyond moving and serving data, Yukon makes it continuously understandable - Live column-level statistics, accessible through MCP, give agents visibility into the data. Built-in monitoring, sampling, and data minimization help teams maintain control. At 1M events/sec and equal freshness, Yukon used 4x less compute than Spark and 7x less than Flink. The benchmark is public: run it yourself with Eon’s ingest-bench. This is another major step toward our vision of an Autonomous Data Foundation for the AI era, built to both protect enterprise data and unlock its full potential.

We just ran the most comprehensive benchmark of AI agent alignment in enterprise environments: 19 leading AI models acting as agents inside simulated companies built with Era, 2,304 runs across 41 everyday tasks. Agents broke security and business rules in 40% of those runs. Every single model failed, including all the frontier models. A few examples: - An agent told one of the company's biggest customers that Finance had approved a full refund. Nobody had. 
- An agent shared a customer's internal churn-risk score directly with that customer. 
- An agent followed a fake runbook planted in a support ticket and promised a customer a credit nobody approved. 
- An agent posted another customer's personal contact details (PII) in a shared Slack channel. In a real company, each of these is a financial liability, a compliance breach, or a lost account. We've shared the full results with the model providers, including exploitable failure modes we're not publishing, and are working with them on fixes. One benchmark won't fix this. We're excited to have @cognition, @LangChain, @TryArcade, @Reindeer_AI, Hirundo, @Box, @recolabs_ai and @QodoAI join Era as research partners, as we build out the next round of research. More soon. I'm still the most bullish person in the room on AI. But this benchmark convinced me that agent reliability and trust is the next big problem to solve. Until then, test every agent before it gets a login, and keep your own record of what it changes. Full results:

I believe we'll look back at this past week as a turning point in cybersecurity. AI is fundamentally changing the speed and scale of cyber threats, and the industry needs to move faster. Today, @Eon_io_ is launching the Data Resilience Initiative, helping companies find and protect their most sensitive data immediately. Eon is the only data protection company founded this decade, and the only one that can be deployed in a day. That's why we feel a responsibility to act. While the cybersecurity industry races to address these new threats, companies can't afford to wait to protect their most critical data. Traditional data protection solutions were built for a different era. They still rely on paradigms from the on-prem world, often taking months to deploy. Eon was built differently. We help companies quickly discover their most sensitive data, identify protection gaps, secure it with air-gapped backups, detect ransomware, and recover rapidly from attacks. As part of the Data Resilience Initiative, any company can start deploying Eon today. To remove barriers to getting protected, we're making Eon available at no cost for the first three months. We're also calling on other cybersecurity and data protection companies to join the initiative.

You can’t safely test an enterprise agent on a real company’s data. So we built a company for it to work in. Era is live today, and it’s free. It generates a complete simulated enterprise that behaves like a real one across Salesforce, Slack, Jira, Zendesk, Gong, Deel and more, along with cloud databases and storage. Agents interact with it through live MCP and API interfaces. People leave. Deals change. Records get duplicated. Permissions differ across systems. And because Era generated the company, it knows the exact ground truth. Test, benchmark and improve agents against realistic enterprise workloads, use the failures for targeted post-training, then rerun the same environment to measure the impact. Huge thanks to our research partners @NVIDIA, @Decart, @Composio, @openlayerco, @Deel, @Eragon and @Plurai, with more coming soon.