Exaud

28/08/2026

Is your solution designed to scale beyond the prototype?

From connectivity and power constraints to security and cloud architecture, critical decisions made early can have a lasting impact on the final product. Our latest article explores how to structure IoT development from concept to production. Read more here:

Here's how to organize a connected product project from architecture to production.

20/08/2026

Manufacturing has one of the strongest business cases for .

Every production line generates measurable data. Every hour of downtime has a known cost. That makes AI's impact easier to quantify than in many other industries.

With 42% of manufacturers already deploying AI and average returns reaching 200% ROI, the opportunity is clear. The challenge is moving from pilot projects to production-scale results.

Our latest article explores where manufacturers create the most value with AI and the common pitfalls to avoid. Read here:

AI in manufacturing delivers measurable results, but only in the right functions and in the right order. Here is where to start and what to measure.

13/08/2026

Is your supply chain actually ready for AI? The biggest barrier to successful adoption isn't the technology. It's the foundation behind it.

Only 29% of supply chain organizations have built the capabilities needed for AI readiness, and just 23% have a formal AI strategy in place.

Our latest article outlines a practical framework for assessing AI readiness before investing in implementation. Read here:

Most supply chain AI projects stall not on technology but on readiness. Here is a practical framework for assessing yours before you invest.

30/07/2026

Most supply chains still respond to problems after they happen. Here is how AI shifts operations from reactive to predictive, and what that shift requires:

Most supply chains still respond to problems after they happen. Here is how AI shifts operations from reactive to predictive, and what that shift requires.

23/07/2026

Retail logistics runs on . From inventory management and warehouse operations to order routing, carrier selection, and last-mile delivery, every process depends on technology that can scale with your business.

One of the biggest decisions retailers face is whether to rely on off-the-shelf platforms or invest in custom software tailored to their operations. The right choice can have a lasting impact on efficiency, scalability, and long-term competitiveness.

In our latest guide, we explore where custom development delivers the greatest value, where commercial solutions make more sense, and how to evaluate the trade-offs with confidence.

Read the full guide here:

Choosing retail logistics software shapes your operations for years. Here is how to decide what to build custom and what to buy off the shelf.

17/07/2026

Exaud was proud to be part of GITEX Europe 2026, engaging with business and technology leaders to discuss how AI can be successfully integrated into real-world products, operations, and enterprise systems.

Here are some of the key insights and highlights from the event: https://exaud.com/blog/inside-gitex-europe-2026

09/07/2026

embedded software fails most often at the architecture layer. Here are the decisions that matter, the patterns that work, and the pitfalls to avoid:

IoT embedded software fails most often at the architecture layer. Here are the decisions that matter, the patterns that work, and the pitfalls to avoid.

25/06/2026

Fine-tuning, RAG, or prompt engineering? Learn how to choose the right strategy for your product based on cost, data needs, and scale:

Fine-tuning, RAG, or prompt engineering? Learn how to choose the right LLM strategy for your product based on cost, data needs, and scale.

18/06/2026

Say hello to Telmo Ribeiro, Exaud’s ! With a background in Computer Science and a passion for embedded systems, Telmo thrives on tackling new challenges and discovering emerging technologies. Ready to learn more about his journey, interests, and perspective on embedded engineering?

Read here:

Meet Telmo Ribeiro: Exaud’s Software Developer! Check out this interview and discover about his journey, interests, and perspective on embedded engineering.

09/06/2026

Andrej Karpathy coined the term “vibe coding” in February 2025. Collins English Dictionary made it Word of the Year. By April 2026, three major AI platform security failures had occurred in a single week, OWASP had added a dedicated category to its Top 10 specifically calling out as a security risk pattern, and the term had completed its journey from marketing buzzword to systemic concern.

That trajectory matters for anyone evaluating how to build . The question is not whether LLM-assisted development has value. It clearly does: 92% of US developers now use AI coding tools daily, and the productivity gains at the prototype and MVP stage are real and well-documented. The question is what happens when the thing you are building is not a prototype. Specifically, what happens when it is an AI agent: an autonomous system with access to your data, your APIs, your business logic, and in many cases your customers. As explored in our post on building trust in AI systems, trust is not a feature you add after the fact. It is a property of how a system is designed from the start. That principle applies with particular force to agents built with vibe coding.

This post is an honest attempt to answer a question that most vendors have an interest in obscuring: when is LLM-assisted development genuinely sufficient for building AI agents, and when does it create risks that specialized engineering expertise is the only reliable way to manage?

Read more here:

Where does vibe coding work for AI agents, and where does it fail? An honest comparison with specialized engineering, with a decision framework.