TechMag 1 - May 26

Short summary

AI engineering in 2026 requires choosing the right harness and conventions over just the raw model—Claude Code beats Copilot through environment setup. Building repeatable processes where each run sets up the next compounds advantage far beyond session-by-session prompt fixes. Even when AI handles the headline task, the surrounding 80% of work—testing, compliance, deployment, regulatory approval—remains untouched, fundamentally reshaping software economics.

• •Choose AI frameworks and conventions over raw models to compound advantage
• •Build repeatable harnesses where each run improves the next, versus session-by-session prompt fixes
• •Headline AI tasks are only 20% of effort; remaining 80% (testing, compliance, deployment) still requires substantial work

Generated with AI, which can make mistakes.