{"componentChunkName":"component---src-templates-newsletters-js","path":"/newsletters","result":{"pageContext":{"group":[{"node":{"id":"307f1df6-aed9-5837-af51-d9b50bf50bbc","slug":"operationalizing-ai","date":"2025-11-17T20:28:03.000Z","title":"Operationalizing AI","acf":{"content":"

 

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Newsletter

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November 2025

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Operationalizing AI

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Trends and Technologies to Watch in 2026

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2026 will not be about AI hype anymore. It will be about operationalizing AI, tightening governance, and building reliable platforms that ship value faster, while smartly adopting the frameworks and tools that move the needle.

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To make that concrete, here are a few resources to help you understand what 2026 will look like.

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\"gartner-top-strategic-tech-trends-2026\"

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Gartner Identifies the Top Strategic Technology Trends for 2026

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By Matt LoDolce

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Gartner announced its list of top strategic technology trends  that organizations need to explore in 2026:

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  • AI Super Computing Platform: AI supercomputing platforms integrate CPUs, GPUs, AI ASICs, neuromorphic and alternative computing paradigms.
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  • Multiagent Systems: Collections of AI agents that interact to achieve individual or shared complex goals.
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  • Domain-Specific Language Models (DSLMs):  Domain-specific language models (DSLMs) provide higher accuracy, lower costs, and better compliance.
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  • AI Security Platforms: A unified way to secure third-party and custom-built AI applications.
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  • AI-Native Development Platforms: Use GenAI to create software faster and easier than was previously possible.
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  • Confidential Computing: Isolating workloads inside hardware-based trusted execution environments (TEEs).
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  • Physical AI: Bring intelligence into machines and devices that sense, decide, and act, such as robots, drones, and smart equipment.
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  • Preemptive Cybersecurity: Defend against threats targeting networks, data, and connected systems.
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  • Digital Provenance: Verifying digital provenance has become essential.
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  • Geopatriation: Moving company data and applications out of global public clouds and into local options.
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Top 10 Technology Trends in 2026 That Will Shape the Next Decade

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By Cambridge Open Academy

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Here is another list of the top 10 new technology inventions in tech trends poised to dominate 2026:

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  • AI: From Assistants to Augmentation
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  • Smart Cities: Building a Sustainable and Connected Future
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  • Extended Reality (XR): Bridging the Gap Between Physical and Digital Worlds
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  • The Internet of Things (IoT): A Web of Connected Devices
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  • Cybersecurity: Evolving Threats and Solutions
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  • Quantum Computing: Breaking the Computational Barrier
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  • Bioprinting: Revolutionising Medicine and Manufacturing
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  • Hyper Automation: Robots Taking Over Repetitive Tasks
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  • Blockchain: Beyond Cryptocurrency
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  • The Future of Work: Embracing Flexibility and Collaboration
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The 7 Cyber Security Trends of 2026 That Everyone Must Be Ready For

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By Bernard Marr

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Experts say that if cybercrime were a nation in 2026, it would be the world’s third-largest economy, behind the U.S. and China, costing businesses an estimated $20 trillion.

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So here are the top trends driving this unprecedented global crime wave over the next 12 months.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

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Check here for more information and to explore our technology assessment and maturity framework.

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Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/operationalizing-ai"}},{"node":{"id":"e73ec431-9904-577c-8866-38c7a3fa1b55","slug":"cloud-resiliency","date":"2025-10-21T13:45:19.000Z","title":"Cloud Resiliency","acf":{"content":"

 

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Newsletter

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October 2025

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Cloud Resiliency

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Practical Patterns for Real-World Outages

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Cloud reliability is not a tool. It is an architectural discipline. The right mix of multi-availability-zone (multi-AZ) and multi-region deployments, thoughtful failover at the DNS and data layers, and routine game-days turns incidents into non-events.

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This month’s picks focus on clear, vendor-backed guidance you can act on right away, plus a couple of books your leaders can use to set a durable playbook.

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Reliability Pillar – AWS Well-Architected Framework

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By AWS Well Architected

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The AWS Well-Architected Framework helps you understand the pros and cons of decisions you make while building workloads on AWS. The Framework shows architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud.

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It provides a way to consistently measure your architectures against best practices and identify areas for improvement.  This paper focuses on the reliability pillar and how to apply it to your solutions.

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Disaster Recovery Planning Guide

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By Google Cloud Architecture Center

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This document provides an overview of the Disaster Recovery (DR) planning process.

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Service-interrupting events can occur at any time — from network failures and software bugs introduced during an application deployment to large-scale natural disasters. A well-designed and thoroughly tested DR plan ensures the organization can respond effectively to these and other potential service disruptions.

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What is Azure Reliability Documentation?

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By Microsoft Ignite

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The Azure reliability documentation provides service-specific guides on how each Azure service supports those platform reliability capabilities, such as transient fault handling, availability zones, multi-region support, and backup support.

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To see the current list of reliability service guides, see Reliability guides by service.

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Building Resilient Applications and Environments: Is Less More?

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By Michael Cade

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This concise 45-minute video covers application and environment resiliency. Even with the high availability and reliability of AWS, simply migrating or modernizing an application in the cloud does not guarantee resilience.

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This demo-driven session illustrates what true data resilience looks like and how to build it. It goes beyond basic backup strategies to show how to create a resilient environment that enhances efficiency and security.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

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Check here for more information and to explore our technology assessment and maturity framework.

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Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/cloud-resiliency"}},{"node":{"id":"6a6737f4-8bda-531b-a5db-b783caf12c70","slug":"improving-acquires-mangochango","date":"2025-09-16T19:31:41.000Z","title":"Improving Acquires MangoChango!","acf":{"content":"

 

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Newsletter

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September 2025

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Improving Acquires MangoChango!

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Expanding a Global Footprint

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\n"},"excerpt":"","path":"newsletters/improving-acquires-mangochango"}},{"node":{"id":"25a828f2-ce17-5b09-b132-68a39ef1b69e","slug":"opentelemetry","date":"2025-08-18T16:16:54.000Z","title":"OpenTelemetry?","acf":{"content":"

 

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Newsletter

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August 2025

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OpenTelemetry?

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A Practical Standard for Modern Observability

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As systems sprawl across microservices, clouds, and teams, “more dashboards” isn’t the answer.

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OpenTelemetry (OTel) gives you a common, vendor-neutral way to instrument software once and analyze anywhere. With a flexible Collector pipeline and growing support beyond traces, metrics, and logs, OTel is quickly becoming the baseline for reliable, portable observability.

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In this month’s newsletter, we explore these ideas in more detail.

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What Is OpenTelemetry?

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By Open Telemetry

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This is a brief overview of what OpenTelemetry (OTel) is.  It also includes a great 9-minute overview video.

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In essence, OTel is an observability framework and toolkit designed to facilitate the generation, export, and collection of telemetry data such as traces, metrics, and logs.

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OTel is open source, as well as vendor- and tool-agnostic.  It can be used with a broad variety of observability backends, including open source tools like Jaeger and Prometheus, as well as commercial offerings.

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The backend (storage) and the frontend (visualization) of telemetry data are intentionally left to other tools.

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Fundamentals of OpenTelemetry

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By Cloud Native Computing Foundation

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The “Fundamentals of OpenTelemetry” is a CNCF-hosted webinar recorded on December 4, 2020, and presented by Ted Young, the Director of Developer Education at Lightstep CNCF.

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The 1-hour session provides a clear introduction to OpenTelemetry—covering its overarching architecture, the core components (like APIs, SDKs, and the Collector), and key concepts that distinguish it from traditional logging systems. It also includes multi-language API usage demonstrations and guidance on effectively rolling out OpenTelemetry across service deployments

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OpenTelemetry Collector: A Complete Guide (2025)

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By SigNoz

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The OpenTelemetry Collector is a stand-alone service that acts as a powerful, vendor-neutral pipeline for your telemetry data. It can receive, process, and export logs, metrics, and traces, giving you full control over your observability data before it reaches a backend.

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This guide provides a comprehensive overview of the OpenTelemetry Collector, its architecture, deployment patterns, and how to configure it for production use.

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\"Learning-OptoTelemetry\"

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Learning OptoTelemetry

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By Ted Young

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OpenTelemetry is a revolution in observability data. Instead of running multiple uncoordinated pipelines, OpenTelemetry provides users with a single integrated stream of data, providing multiple sources of high-quality telemetry data: tracing, metrics, logs, RUM, eBPF, and more.

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This practical guide shows you how to set up, operate, and troubleshoot the OpenTelemetry observability system.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

\n

Check here for more information and to explore our technology assessment and maturity framework.

\n

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\n

Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/opentelemetry"}},{"node":{"id":"86f86437-b653-5d60-817c-e88b20463a56","slug":"team-topologies-and-near-shore","date":"2025-07-18T22:42:00.000Z","title":"Team Topologies and Near Shore","acf":{"content":"

 

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Newsletter

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July 2025

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Team Topologies and Near Shore

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Unlocking Agility and Innovation in a Distributed World

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In today’s fast-paced digital landscape, CIOs and CTOs face immense pressure to enhance efficiency, mitigate risk, and drive innovation amidst a persistent global IT talent shortage.

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The synergy of “Team Topologies,” a framework for structuring teams for optimized flow, and “Nearshore” outsourcing, which provides access to skilled talent with time zone and cultural alignment, offers a powerful solution to build truly “super-powered teams” capable of navigating these complex challenges and securing significant competitive advantage.

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In this month’s newsletter, we explore these ideas in more detail.

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Team Topologies: Key Concepts

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By Team Topologies

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Team Topologies is an approach to designing team-of-teams organizations for fast flow of value.

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The approach is based on years of research across many organizations from different industries, different sizes and different technological backgrounds. It addresses the most dreaded challenges in technology:

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    How to maintain or even accelerate speed of value creation while scaling the organization?

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    How to evolve an architecture along with the evolution of the organization and avoid that one becomes a blocker for the other and a blocker for the growth of the business?

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The approach provides a pattern language and a thinking model, which allows you to identify the team-of-teams design most appropriate for the target architecture and fast flow of value.

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\"Why-Nearshore-IT-Outsourcing-is-Ideal-for-Rapid-Scaling\"

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Why Nearshore IT Outsourcing is Ideal for Rapid Scaling

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By Vanguard X

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In high-growth environments, speed and precision must coexist. Yet many companies make the mistake of chasing expansion without building a scalable structure. This often results in overextended teams, communication gaps, and inconsistent output.

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The need to grow quickly does not require aggressive hiring or resource strain. It demands a smarter approach to capacity building. Nearshore IT outsourcing supports modern scaling efforts by combining technical strength with operational alignment.

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Teams gain instant access to qualified talent, cultural compatibility, and seamless collaboration.

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Nearshore Industry Insights: Platforming the Near Shote IT Staffing Industry

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By Lonnie McRorey

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Traditional hiring models weren’t built for what you’re asking of them today: distributed engineering, AI-integrated workflows, microservice architectures, sprint-level agility, and multi-cloud orchestration. Yet somehow, most companies are still trying to scale tech teams using workflows last optimized during the Web 2.0 era.

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Platforming the nearshore IT industry is more than a strategic advantage. It’s a necessary architectural shift in how talent is identified, qualified, activated, and retained.

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Lessons Learned from GitLab About Remote Work

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By Team Topologies

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This is an insightful interview with Darren Murph, Head of Remote at GitLab, the world’s largest all-remote organization. Darren leads at the intersection of people, culture, operations, inclusivity, marketing, employer branding, and communication overall. He has spent his career shaping remote teams and charting remote transformations, and recently authored GitLab’s Remote Playbook, a set of tried and tested tactics for building remote fluency in any organization.

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Team Topologies spoke to Darren about the opportunities and challenges presented by remote working for organizations building software-based systems and services.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

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Check here for more information and to explore our technology assessment and maturity framework.

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Meet The Team

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Copyright © 2025 Mangochango, All rights reserved.
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\n"},"excerpt":"","path":"newsletters/team-topologies-and-near-shore"}},{"node":{"id":"25e64b72-ba23-569d-9967-b41a29d78f15","slug":"the-rise-of-private-llms","date":"2025-06-19T14:03:47.000Z","title":"The Rise of Private LLMs","acf":{"content":"

 

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Newsletter

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June 2025

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The Rise of Private LLMs

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Bring the Model to Your Data

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After a year of blockbuster public-AI launches, many CIOs are discovering that the real competitive edge comes from running large language models inside their own perimeter.

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Private LLMs shrink latency, cut per-token costs at scale, and—crucially—keep regulated or proprietary data where auditors expect it.

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Open-weight families such as Meta’s Llama 3 and Microsoft’s Phi-3 show that high-quality models can now run on a commodity GPU cluster or even a beefy workstation, while frameworks like NVIDIA NeMo add enterprise-grade guardrails.

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Add looming rules such as the EU AI Act, and the “bring the model to the data” pattern is fast moving from R&D to roadmap.

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Introducing Meta Llama 3: The most capable openly available LLM to date

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By Meta

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Meta AI, built with Llama 3 technology, is now one of the world’s leading AI assistants that can boost your intelligence and lighten your load—helping you learn, get things done, create content, and connect to make the most out of every moment.

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The release of Llama 3 features pre-trained and instruction-fine-tuned language models with 8B and 70B parameters that can support a broad range of use cases.

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This next generation of Llama demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning.

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In support of Meta’s longstanding open approach, Meta has put Llama 3 in the hands of the community.

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Private AI to Redefine Enterprise Data Privacy and Compliance with NVIDIA

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By Patricia Graciano

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Private AI, a leader in privacy-preserving artificial intelligence, integrates with  NVIDIA NeMo Guardrails to bring advanced privacy and compliance capabilities to enterprises leveraging large language models (LLMs), enabling them to unlock the potential of generative AI while safeguarding sensitive data.

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Generative AI offers transformative potential but poses challenges with unstructured data containing PII, PHI, or proprietary insights. While regulations like HIPAA mandate specific data best practices for healthcare organizations, these requirements can serve as valuable guidelines for any organization seeking to mitigate risks when working with sensitive data.

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\"phi-3-small-language-models\"

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Tiny But Mighty: The Phi-3 small language models with big potential

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By Sally Beaty

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Inspired by children’s books, Microsoft researchers developed a new way to train small language models using simple vocabulary.

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This led to the creation of the Phi-3 family—compact, efficient AI models that retain strong performance.

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The first model, Phi-3-mini, outperforms larger models and is now available on Azure, Hugging Face, Ollama, and NVIDIA NIM. Larger versions, Phi-3-small and Phi-3-medium, will be released soon.

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Keeping Things Local – Making Your Own Private LLM

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By Bronwen “Corvus”  Aker

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This video explains how to give individuals and small organizations control over their own large language models (LLMs).

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It highlights key technical components such as model pruning to reduce size, open‐source tools like LoRA and QLoRA for fine‑tuning, and local GPU optimization techniques.

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It emphasizes privacy and autonomy by demonstrating how users can deploy and run models entirely offline—on personal hardware like laptops or cheap cloud instances—with minimal performance loss, making powerful AI capabilities accessible without reliance on big tech providers.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

\n

Check here for more information and to explore our technology assessment and maturity framework.

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Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/the-rise-of-private-llms"}},{"node":{"id":"d842e7c7-a72b-5b13-98d4-f7086ffeb37d","slug":"cloud-cost-guardrails","date":"2025-05-15T16:51:28.000Z","title":"Cloud Cost Guardrails","acf":{"content":"

 

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Newsletter

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May 2025

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Cloud Cost Guardrails

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FinOps Practices to Stop Budget Blow-outs

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Cloud spend is one of the few budget lines that can double overnight—sometimes without anyone noticing until the invoice hits.

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With headlines about five- and six-figure “surprise” bills spooking boards and investors, disciplined cost governance is no longer optional.

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Modern FinOps practices, smarter tooling, and even new regulations now give technology leaders the levers they need to rein-in risk while preserving developer speed.

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Below are five resources every CIO, CTO, and VP of Engineering should bookmark before the next billing cycle closes.

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When Cloud Costs Go Wild – The $72K Bill in Two Hours

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By Tim Anderson

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An interesting story of how Sudeep Chauhan, founder of startup Milkie Way, suffered a bad case of bill shock when a test with a $7.00 billing budget and a free database plan on Google Cloud platform (GCP) generated a $72,000 invoice overnight.

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FinOps Framework Capabilities

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By FinOps Foundation

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Here is a succint dashboard with a list of FinOps capabilities necessary when managing cloud infrastructures and costs.  This dashboard includes discussions on capabilities like: allocation, anomalies management, architecting for cloud, benchmarking, budgeting, data ingestion and many others.

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Top Cloud Cost Management Tools for 2025

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By Perry Tapiero

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After finally making it to the cloud, there’s still the task of determining cloud costs.

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Microservices, containers, Kubernetes made resource costs, associated costs and more are near-impossible to sort though. Without a way to put a reason to a price tag and to break down where your money is going, justifying cloud costs is near impossible.

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This article claims that 32% of cloud budgets go to waste and that it can be made 0% with cloud cost management tools.

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In this article you will find topics like these:

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Preventing Cost Overruns in Your Cloud-Native Envorpnments

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By Nirmata

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In this 1-hour video, you will learn how to implement proactive cost controls on AWS using Kyverno and Kubecost.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
\n

\n

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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

\n

Check here for more information and to explore our technology assessment and maturity framework.

\n

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Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/cloud-cost-guardrails"}},{"node":{"id":"15603c23-0f2d-53b3-a3b0-937574f4ac8c","slug":"internal-developer-platforms","date":"2025-04-21T14:19:04.000Z","title":"Internal Developer Platforms","acf":{"content":"

 

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Newsletter

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April 2025

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Internal Developer Platforms

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Reshape DevOps for Speed, Governance, and Scalability

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DevOps has matured beyond the basic CI/CD pipeline, and organizations are seeking the next level of efficiency.

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Enter platform engineering—a focused approach to creating shared internal platforms and tools that empower developers, standardize best practices, and reduce friction.

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At the heart of this movement are Internal Developer Portals (IDPs), which consolidate everything from documentation and environment provisioning to automated guardrails in one place.

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In this newsletter, we’ll explore how these portals work, why they matter, and how to ensure your company reaps the benefits without losing flexibility.

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Best of 2024: Internal Developer Platform (IDP) Reference Architectures

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By Bill Doerrfeld

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The DevOps space is brewing with excitement around platform engineering.

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Gartner even expects that by 2026, 80% of software engineering organizations will have established platform teams.

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The platform engineering idea hinges on an internal tooling system known as an internal developer platform (IDP).

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This article examines the an IDP reference architecture and its components.

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An Open Source Framework for Building Developer Portals

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By Backstage

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Powered by a centralized software catalog, Backstage restores order to your infrastructure and enables your product teams to ship high-quality code quickly — without compromising autonomy.

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\"what-is-an-IDP\"

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What is an Internal Developer Platform (IDP)?

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By HashiCorp

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In this 15-minute white-boarding session, the role of an Internal Developer Platform (IDP) is explained.

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An IDP is the middle interface layer that sits in between the Developers and the Platform teams to separate the concerns of both teams.

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The goal is to package up a set of interfaces and experiences for developers so they can focus on Application lifecycle and the Platform teams can then own pieces that ultimately support and underpin the infrastructure.

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Build Internal Developer Platforms (IDP) that Scale

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By Humanitec

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A commercial platform where an organization can combine products and OSS building blocks to build an enterprise Internal Developer Platform (IDP).

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It includes a platform orchestrator which is the configuration engine that sits at the heart of your Internal Developer Platform.

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It lets you define clear templates and golden paths for developers. It drives automation and standardization across all your teams and workflows.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
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MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

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Check here for more information and to explore our technology assessment and maturity framework.

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Meet The Team

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Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/internal-developer-platforms"}},{"node":{"id":"6a5b30f6-9428-598c-ad2c-fbd7a6768b5f","slug":"ai-powered-developers","date":"2025-03-18T23:23:06.000Z","title":"AI-Powered Developers","acf":{"content":"

 

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Newsletter

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March 2025

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AI-Powered Developers

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AI Tools Are Way Beyond Copilot—Are You Keeping Up?

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While GitHub Copilot has become the go-to AI coding assistant for many developers, the landscape of AI-powered development tools has expanded far beyond just code completion.

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From intelligent terminals to automated UI design, AI is revolutionizing the entire software development lifecycle. These tools don’t just speed up coding—they enhance collaboration, optimize workflows, and unlock new levels of efficiency.

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However, tools alone aren’t enough—you need the right expertise to leverage them effectively.  At Mangochango, we don’t just know how to use AI tools; we can integrate them into workflows to maximize efficiency, maintain high code quality, and accelerate project timelines.

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Here are five AI-powered tools that every development team should know about in 2025:

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\"cursor-ai-powered-ide\"

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Cursor

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AI-Driven IDE for Smarter Coding

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Cursor is an AI-powered code editor that seamlessly integrates AI-assisted features directly into the development workflow.

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It enhances productivity by offering AI-driven code completion, inline debugging, and natural language codebase queries.

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Unlike Copilot, Cursor is designed to be a full-fledged AI companion for developers, making it easier to navigate and understand complex codebases.

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Teams leveraging Cursor can reduce context switching, accelerate development, and improve code maintainability.

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\"warp-terminal-reinvented-ai\"

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Warp

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The Terminal Reinvented with AI

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Warp is a Rust-based terminal that brings modern features, AI-assisted commands, and real-time collaboration to the command line.

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Traditional terminals haven’t evolved much over the years, but Warp changes the game by offering AI-powered command suggestions, intelligent auto-completions, and enhanced search capabilities.

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For development teams, this means less time spent searching for the right commands and more time building. With Warp Drive, teams can even share reusable command workflows, reducing redundant work and ensuring best practices are followed.

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\"qodo-code-integrity-testing-ai\"

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Qodo

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AI-Powered Code Integrity and Automated Testing

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Qodo, formerly known as Codium, is an AI-driven code integrity platform designed to improve software quality at every stage of development.

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Its TestGPT feature generates high-quality test cases automatically, reducing the burden on developers and improving code reliability.

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AlphaCodium enhances code generation, while other AI-powered tools streamline debugging and refactoring.

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Qodo helps teams catch issues earlier in the development process, ultimately leading to more stable and maintainable applications.

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\"AI-UI-Generation-v0\"

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V0

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AI-Powered UI Generation for Developers and Designers

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V0.dev is an AI-driven tool that allows developers to generate high-quality React components using natural language prompts.

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Instead of spending hours manually designing and coding UI components, teams can input descriptions, and V0 generates fully functional, Tailwind-styled React components ready for integration. This speeds up prototyping, enhances consistency, and ensures that design and development stay aligned.

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Whether building new interfaces or iterating on existing ones, V0 accelerates front-end workflows dramatically.

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\"figma-ui-prototyping\"

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First Draft by Figma

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AI-Powered UI Prototyping

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First Draft is an AI-powered feature within Figma that generates UI prototypes based on prompts, reducing the time needed to create user interfaces from scratch.

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By selecting from different design libraries and patterns, designers and developers can rapidly iterate on UI concepts, ensuring that user experience remains a priority while minimizing design bottlenecks.

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First Draft bridges the gap between ideation and execution, helping teams move from concept to implementation faster than ever before.

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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
\n

\n

\n\n\n\n\n\n\n
\n\n\n\n\n\n\n\n\n\n
\"\"
\n

MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

\n

Check here for more information and to explore our technology assessment and maturity framework.

\n

\n
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\n\n\n\n\n\n\n
\n

Meet The Team

\n

Talent Inside MangoChango

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\n"},"excerpt":"","path":"newsletters/ai-powered-developers"}},{"node":{"id":"624181c5-36ca-5987-8d88-6a0194244330","slug":"data-mesh-what-is-it","date":"2025-02-24T23:05:38.000Z","title":"Data Mesh: What Is It?","acf":{"content":"

 

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Newsletter

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February 2025

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Data Mesh: What Is It?

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A New Paradigm for Enterprise Data Architecture

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Data Mesh represents a shift from centralized data management to a decentralized, domain-oriented approach where data is treated as a product.

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By distributing data ownership to the teams closest to the source, it fosters agility, improves data quality, and enhances collaboration across the organization.

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In this newsletter, we’ll delve into how Data Mesh addresses the challenges of traditional data lakes and warehouses, and why it could be the key to unlocking more effective, scalable data strategies for modern enterprises.

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\"data-mesh-in-action-book\"

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Data Mesh In Action

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By Jacek Majchrzak

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This book reveals how this groundbreaking architecture looks for both small startups and large enterprises and how to start implementing a data mesh with flexible processes and organizational change.

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It also covers how to turn data into a data product, how to move from your current data architecture to a data mesh, how to identify data domains, how to decompose an organization into smaller, manageable domains, and how to set up the central and local governance levels over data.

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\"what-is-a-data-mesh\"

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What Is a Data Mesh?

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By Amberle McKee

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Centralized data architectures can be an effective data strategy – until they start to struggle with the growing volume and complexity creating bottlenecks.

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A data mesh is an architectural system with decentralized and domain-specific data management. This approach empowers teams to take charge of their own data, leading to better data quality and faster insights.  This article offers insights into what it is, how it works, and how to implement it.

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\"data-mesh-real-examples-lessons-learned\"

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Data Mesh: Real Examples and Lessons Learned

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By Divya Joshi

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This article includes examples and lessons learned with Data Mesh work with Gilead, Saxo Bank and other organizations.

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Some of those lessons learned include the fact that organizational and operational models are the most significant barriers to adopting Data Mesh and that educating stakeholders and domain teams about Data Mesh is critical to success.

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\"data-mesh-101\"

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Data Mesh 101: What Is Data Mesh?

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By Tim Berglund

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Follow along in this 10 minute video as Tim Berglund (Senior Director of Developer Experience, Confluent) introduces the concept of data mesh and its key four principles:

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  1. Data ownership by domain
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  2. Data as a product
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  3. Data available everywhere by self-serve
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  4. Data governed where it is.
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MangoChango’s ability to deliver unquestionable value to its clients is highly dependent on keeping abreast of new technologies and trends. Our clients value this commitment to leading-edge thinking and expertise.
\n

\n

\n\n\n\n\n\n\n
\n\n\n\n\n\n\n\n\n\n
\"\"
\n

MangoChango’s engineers are experts in a wide variety of technologies, frameworks, tools, and languages, with an emphasis on continuous learning as new thinking, tools, and techniques come to market.

\n

Check here for more information and to explore our technology assessment and maturity framework.

\n

\n
\n
\n\n\n\n\n\n\n

\n\n\n\n\n\n\n
\n

Meet The Team

\n

Talent Inside MangoChango

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\n

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View this email in your browser
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