Ardan Labs partnered with Deliveroo invites you to take the conversation further at our Go, AI, Community event designed to bring developers together for an evening of insight, inspiration, and connection.

Engineers, AI, and the Cognitive Tradeoff Every generation creates tools to offload effort. In the 1960s, when electronic calculators entered classrooms, educators worried students would lose the ability to do math on their own. Why? Because the …

With no access to critical DB metrics, a fintech team faced serious transaction latency. Ardan Labs embedded engineers directly into their team—cutting insert delays by 90% and leaving behind scalable systems and sustainable performance practices.

To meet strict compliance demands while scaling fast, a growing AI startup brought in Ardan Labs engineers to co-build secure, cloud- and airgap-ready infrastructure—accelerating delivery without sacrificing ownership or momentum.

How Ardan Labs’ embedded engineers helped a telecom company build a high-throughput, cross-cloud data platform in Go and gRPC—integrating with teams, enabling full observability, and delivering production-ready systems across AWS, GCP, and on-prem Kubernetes.

Ardan Labs embedded engineers to lead a complex API integration for a fast-growing SaaS company—delivering the solution early without impacting the internal team. The work boosted user engagement and gave the client a scalable, maintainable integration.

Ardan Labs embedded engineers to build a real-time CRM sync platform—eliminating data silos, streamlining onboarding, and enabling the client to scale with confidence.

How Ardan Labs helped a telecom company integrate a Rust-based vector database with their .NET AI infrastructure—unlocking high-performance RAG without changing existing tools.

Introduction: Welcome to the final episode of our Intro to Generative AI series! In this episode, Daniel Whitenack takes the concepts you’ve been learning and shows you how to apply advanced techniques like message chaining and factuality …

Introduction: In Episode 6 of the Intro to Generative A.I. series, Daniel shifts the focus from basic search techniques to more dynamic, on-the-fly AI applications. He demonstrates how to enhance AI-driven interactions by integrating real-time data …

Introduction: Welcome to Episode 5 of our Intro to Generative AI series! In this episode, Daniel explores practical techniques for enhancing AI models’ ability to handle large volumes of text data effectively. He addresses the challenges …

Introduction: Welcome to Episode 4 of our Intro to Generative AI series! In this episode, Daniel dives into the essential technique of prompt engineering, focusing on creating dynamic and interactive prompts to enhance the capabilities of AI models. …

Introduction LibreQoS is an open source project for monitoring and providing quality-of-experience for Internet Service Providers (ISPs) and large networks. It runs as a “middle-box”, monitoring traffic that passes through it. It recently …

Introduction: Welcome to Episode 3 of our Intro to Generative AI series! In this episode, Daniel explores the critical aspect of prompt formatting when working with AI models, emphasizing how proper formatting can significantly enhance the quality of …

Introduction: Welcome to Episode 2 of our Intro to Generative AI series! In this segment, Daniel dives into the practical aspects of working with large language models (LLMs) using the Go programming language and the Prediction Guard API. Accessing …

Introduction: Welcome to the first episode of our “Intro to Generative A.I” series! In this episode, Daniel dives into the intriguing world of large language models (LLMs), providing a comprehensive understanding of how these powerful …