Digest #48: April 2026
April at Mad Devs was all about safer releases, better AI evaluation, and clearer ways to explain how modern systems work. This month's digest brings together practical release engineering, AI quality checks, glossary updates on security and workflows, and new slide-based explainers for teams.
Tech Journal: safer releases, smarter checks
This month's Tech Journal focuses on reducing delivery risk and making AI features easier to trust in production.
This guide shows why feature flags alone are not enough once real traffic, concurrency, and runtime behavior enter the picture. It moves from flag hygiene to progressive delivery, covering canary releases, blue-green deployments, observability gates, and automated rollbacks as part of a safer release system.
Look at AI feature testing beyond ordinary unit tests. Our guide explains how LLM evals help teams validate outputs, compare behavior across prompts or models, and build more reliable quality checks for AI-powered features before they reach users.
Glossary: security, data, and AI workflows
This month's glossary entries focus on threats, failures, and the new patterns that shape AI-enabled systems.
π Supply chain attacksΒ
Learn how attackers exploit trusted vendors, tools, or dependencies to reach their real targets indirectly, and why supply chain security has become a critical part of modern software defense.
π Data breach
Understand what happens when sensitive information is exposed, stolen, or accessed without authorization, and why prevention depends on both technical controls and response readiness.
π Agentic workflow
Explore how AI moves from one-shot generation to multi-step workflows where models reason, use tools, self-correct, and break larger goals into smaller tasks.
Visual Glossary: big Ideas, short explanations
This section continues our slide-based format for explaining complex concepts in a way that is quicker to scan, easier to share, and more useful in team discussions.
See how step-by-step prompting improves reasoning on more complex tasks and why structured thinking often leads to better outcomes than direct answer generation.
A concise guide to why an agent is never just one prompt. The slides focus on orchestration, memory, tools, and the extra logic that turns a model into a useful system.
Learn how structured markup helps search engines understand your content better and why it matters for discoverability, indexing, and richer search results.
Learn why some devices need local, lightweight computing instead of heavy software or constant cloud calls, and why microcontrollers matter even more as systems move toward local intelligence.
Open roles this month
We are hiring across engineering and AI-focused roles for teams building production systems, testing workflows, and delivery infrastructure.
ENGINEERING POSITIONS
π Middle+/Senior C# Developer
π Senior C++ Developer
π Middle Reach Native Developer
π Middle QA Automation Engineer
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AI & ML POSITIONS
π Junior+ ML Engineer