Engineering
A customer asked us a fair question last month. They run two near-identical e-commerce brands, same SKU catalog, same support workflow, same Shopify setup. They wanted to clone their Customer Success employee — call her Enide-A — and stand up Enide-B for the second brand. "Same employee, two stores. Just duplicate
Engineering
Every few weeks somebody lands in our inbox asking whether Geta.Team can run air-gapped. The conversation usually opens with the word "DORA" or "HIPAA" or "EU AI Act" and continues with the buyer describing a deployment so isolated that even the typing of
Engineering
v2.1.8 ships one big new thing — Clone Employee — plus three fixes we caught while testing it. Quick run-through. Clone Employee You can now duplicate an employee from the dashboard kebab menu. Click Clone, give the copy a name, and you get a brand-new employee with the same skills,
Engineering
v2.1.7 is a release with one big plumbing job, one quiet cleanup, and a sweep of dashboard fixes that mostly close papercuts you already noticed but never reported. The biggest item is GPT-5+ models on direct-to-OpenAI custom_llm — which sounds like a one-line param swap and was actually
Engineering
v2.1.6 closes a chain of four bugs that all looked the same from the outside — "I started a fresh chat and the old conversation came back" — but had four completely different root causes. We found them while investigating one report, then kept pulling the thread until
Engineering
v2.1.5 is the biggest reliability sprint we've shipped this quarter. Fourteen fixes and small features, almost all in service of "the thing should do what it looked like it was doing." Two of them are structural enough to call out before the line-item tour.
Engineering
Two days after v2.1.1 shipped the OpenAI Codex integration, Codex pushed an auto-update. Two days after that, we started getting reports of employees going silent on the first user message. No response, no error in the UI, just a quiet [TERMINAL-EXIT] in the logs two seconds after the
Engineering
Multi-agent architecture diagrams are a lie. They show clean arrows between labeled boxes — Agent A hands work to Agent B, Agent B enriches it, Agent C takes the enriched result and publishes. In the diagram, the arrow is free. In production, the arrow is where everything breaks. We run a
Engineering
OWASP has published security frameworks for web applications for over two decades. SQL injection, XSS, broken authentication, the classics. But in early 2026, they released something new: the first Top 10 specifically for agentic AI applications. And it reads like a different planet. The traditional OWASP Top 10 assumes a
Engineering
Anthropic shipped Claude Opus 4.7 on April 16. The headline numbers are real: 64.3% on SWE-bench Pro, 87.6% on SWE-bench Verified, 78% on OSWorld, and a 14% improvement on complex multi-step workflows with one-third fewer tool errors. If you're building agents in production, these numbers
Engineering
The npm ecosystem had left-pad. Python had the PyPI typosquatting wave. Docker Hub had cryptominers hiding in official-looking images. Every software supply chain eventually gets poisoned. AI agent skills just joined the list. By February 2026, Antiy CERT confirmed 1,184 malicious skills on ClawHub, the marketplace for the OpenClaw
Product
You know the feeling. You're working with your AI employee, you send a message, and then while it's processing you think of something else. Maybe a follow-up instruction, maybe a correction, maybe a completely different task. But the send button is gone. You're stuck