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Announcements, product updates, and engineering insights.

AI Workflows for Internal Processes: The Fastest Path to Higher Productivity
Most companies today approach AI from the visible surface-a chatbot, a copilot in the inbox, or a single smart feature on the website. However, the fastest business impact often lies elsewhere: in internal processes that cost dozens of hours of manual labor every week. This is exactly where it makes sense to build small internal systems and workflows on top of your data. Systems that gather background information, sort requests, prepare outputs, monitor dependencies, and speed up tedious operations. The result isn't just saved time. It's a faster company, cleaner operations, and a team that can focus on more important work.

From Chatting to Doing: What Actually Shifted in May
Codex, Claude, Gemini, and Cursor delivered a consistent message in May: agents are moving from chat to production. The focus isn't on a better model, but on environment, governance, and integration with work systems. For companies, this isn't a signal to buy another chat window—it's a signal to rebuild their operating model for AI.

Ship From Your Phone: Your Own AI Delivery System
A single message from your phone triggers the entire delivery engine: PR reviews, incident response, fixes, and preview releases. Within minutes, you get an analysis, a proposed patch, test results, and an audit trail. Everything runs self-hosted, meaning the server, rules, integrations, and data stay fully under your control.

RAG vs. File-Based Agents.
Instead of a simple 'File-based search vs. RAG' debate, a practical comparison is more useful: what starts faster, what offers better control, and what actually scales. This article summarizes current 2026 data and translates it into a straightforward decision-making framework.

The Real 2026 Playbook: Orchestrating Coding Agents in Production
In 2026, it's no longer about which coding agent is the absolute best. Every team might prefer a different style of assistant. The key is to actually integrate these AI assistants into a real delivery process, measure their impact, and maintain senior-level oversight over quality and security.

AI-Assisted Development: Why We Build Faster?
Today, Claude Code generates over 134,000 GitHub commits daily. Spotify's top developers haven't written a single line of code since December; AI writes most of it. We explain exactly what is changing in software development and how we are responding to it.
Team
Profiles and stories from the people building TameTeq.

Meet Marian Krotil
Marian Krotil is Co-Founder at TameTeq and an AI engineer focused on building intelligent systems that work in real operations. He combines machine learning and software engineering to turn complex ideas into practical products.

Meet Matyáš Krotil
Matyáš Krotil is a frontend architect and entrepreneurial builder behind TameTeq's digital products. He combines creativity, discipline, and continuous self-development to turn ambitious ideas into software that looks sharp and works properly.