Insights

Page 6 of 7

RAG architecture diagram in production showing the common failure points in retrieval, re-ranking and generation with cost indicators

RAG in production: common mistakes that drain your AI budget

Visual comparison between an MVP built without a specification with multiple rework iterations and an MVP guided by Spec-Driven Development with a clean, controlled flow

MVP vs Specification: how Spec-Driven Development corrects the "Quick Ship" bias

Visual comparison of proprietary and open source LLM models with performance, cost and privacy charts for an enterprise decision

Proprietary vs. open source LLMs in 2026: an enterprise decision guide

Diagram of multi-stage workflows with AI agents running complete software development processes with human control points

From tasks to workflows: AI agents already run complete multi-stage processes

Infographic with data from Deloitte's State of AI in the Enterprise 2026 report showing gaps between aspiration and execution in enterprise AI adoption

74% aspire to revenue with AI. Only 20% achieve it. The Deloitte report explains the gap.

Development team configuring Skills and capabilities for AI agents with modular architecture diagrams

Skills for AI agents: a practical guide for development teams

Enterprise RAG architecture with data pipelines, vector search and intelligent agents in a technical diagram

RAG for enterprise applications: from theory to production in 2026

Analytics dashboard showing return-on-investment metrics for AI agents deployed in an enterprise environment

AI agents in 2026: 80% of companies already generate measurable ROI. The obstacle isn't the technology.

Startup team planning MVP development on a whiteboard with product diagrams and user flows

Transformation10 Mar 2026

MVP for a startup: how to launch it fast without mortgaging the product

Agentic AI architecture diagram with multiple autonomous agents coordinating software development tasks

Agentic AI: what it is and how it will transform software development in 2026

Development team analyzing the organizational integration of AI into their way of working, with process diagrams and metrics

Transformation4 Mar 2026

70% of AI success in development teams isn't technical. It's organizational.

KPI dashboard for AI development teams showing impact, rework and technical debt metrics on screens

Advanced KPIs for AI development teams: what to measure (and what to stop measuring)

Development team reviewing the quality of AI-generated code on screens with architecture and maintainability metrics

In the AI Coding era, code quality matters more than ever

Development team configuring context and specifications for AI agents in a collaborative environment

Context engineering: the discipline that levels up teams with and without AI

Technical leadership team analyzing priorities on a whiteboard with a decision matrix and strategic roadmap

Leadership14 Feb 2026

Prioritization frameworks: decide better to ship faster

Contact

Want to put these ideas to work in your team?

Let's talk about how to transform your organization with AI, DevOps and modern architectures.

What happens next

You write to us. Two lines are enough.
We reply within 24 working hours and set up a call.
On the call we tell you whether we can help and where to start.

Prefer to talk? Call us 682 384 429

Tell us what you want to solve

Tell us who you are and what you need.