Systems | Development | Analytics | API | Testing

antino

2026 Guide To Integrating AI Into Existing Apps

Jan 29, 2026 By Radhakanth Kodukula In Antino
Have you ever noticed how your favorite apps just know what you want? Whether it’s a curated playlist that suits your mood, a movie recommendation that hits the spot, or ads that seem oddly relevant, none of it feels surprising anymore. These experiences have become so routine that we barely pause to think, “How does this even work?” But maybe we should.
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ably

Why orchestrators become a bottleneck in multi-agent AI

Jan 29, 2026 By Faye McClenahan In Ably
Complex user tasks often need multiple AI agents working together, not just a single assistant. That’s what agent collaboration enables. Each agent has its own specialism - planning, fetching, checking, summarising - and they work in tandem to get the job done. The experience feels intelligent and joined-up, not monolithic or linear. But making that work means more than prompt chaining or orchestration logic.
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dreamfactory

Why Deterministic Queries and Stored Procedures Are the Future of AI Data Access

Jan 29, 2026 By Kevin McGahey In DreamFactory
Executive Summary: As enterprises integrate AI and large language models (LLMs) into their data workflows, the need for predictable, secure, and auditable database interactions has never been greater. Deterministic queries—particularly those encapsulated in stored procedures—provide the guardrails necessary for both human analysts and AI systems to access sensitive data safely.
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keploy

Copilot vs Cursor: A Complete AI Coding Assistant Comparison

Jan 28, 2026 By Keploy In Keploy
Coding with artificial intelligence is not just a nice-to-have; AI applications in computer programming are becoming integral to modern computer programming workflows. Presently, two primary applications dominate the discussions in this area: GitHub Copilot and Cursor AI. While both applications provide faster coding times and fewer bugs, fewer bugs, and smarter code, they offer such features in extremely different ways.
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Real Outcomes with Appian: How Customers Achieve Speed, Scale, and Efficiency

Jan 28, 2026 By Appian In Appian
What does real transformation look like in practice? Across industries, organizations are using Appian to simplify complexity, automate mission-critical work, and deliver measurable results fast. In this customer montage, hear directly from leaders who are driving meaningful change with the Appian Platform. From reducing onboarding from six months to just four days, to achieving immediate efficiency gains and scaling to thousands of clients without adding headcount, these stories show how organizations are evolving as the world changes.
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tideways

Performance Benchmark Report second half of 2025 for Shopware 6

Jan 28, 2026 By Benjamin In Tideways
How does your Shopware 6 store’s PHP backend performance compare to other operators of Shopware in general? To answer this question, we have aggregated and anonymized performance data from over 200 Shopware 6 stores over the second half of 2025 and computed benchmark numbers to compare to for the most important page types: Product details, Category, Search, and Homepage. We previously made these benchmarks for 2025 Q1, and 2025 Q2. Going forward, these will be published every 6 months.
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dreamfactory

How to Build REST APIs with Node.js & Express

Jan 28, 2026 By Kevin Hood In DreamFactory
In today’s fast-paced digital environment, REST APIs have become the backbone of modern application development, powering seamless communication between clients and servers. For developers, understanding how to build efficient and scalable REST APIs is essential. This article unpacks the foundational steps of creating REST APIs using Node.js and Express, offering actionable insights for building dynamic server-side applications.
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perforce

What is an MCP? Breaking Down the Model Context Protocol

Jan 27, 2026 By Perforce In Perforce
70% of teams are already integrating generative AI tools into their daily workflows, according to our 2025 State of Game Technology Report. Now more than ever, teams are looking to connect their AI tools to the services and applications they rely on to get work done. To address this issue, the industry has begun to standardize using the Model Context Protocol (MCP) to connect their existing tools and LLMs like Claude, GPT, and Gemini.
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kong

Building Secure AI Agents with Kong's MCP Proxy and Volcano SDK

Jan 27, 2026 By Eugene Tan In Kong
Modern AI applications are no longer just about sending prompts to an LLM and returning text. As soon as AI systems need to interact with real business data, internal APIs, or operational workflows, the problem becomes one of orchestration, security, and control. The challenge is to build secure AI agents without embedding fragile logic or exposing sensitive systems directly to a model. This is where a layered architecture using Volcano SDK, DataKit, and Kong MCP Proxy becomes compelling.
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honeybadger

Code coverage vs. test coverage in Python

Jan 27, 2026 By Muhammed Ali In Honeybadger
If you have been writing tests for a while, you have probably encountered code coverage and test coverage. These concepts can be difficult to differentiate because they are somewhat intertwined. In this article, you will learn what code coverage vs test coverage means, and the basis of these concepts. You will also learn the key differences between code coverage and test coverage in Python. You would discover tools, techniques, and best practices to improve your testing strategy.
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