Systems | Development | Analytics | API | Testing

How Will Software Engineers Interface with AI in the Future? aicoding #devops #techdebate #aiagents

Sep 23, 2026 By Speedscale In Speedscale
A breakdown of the three potential ways software engineers will interact with AI coding assistants, ranging from local desktop setups to fully automated software delivery factories. Learn more: speedscale.com.
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bitrise

Build Hub self-serve is live: bring us your slowest build

Sep 23, 2026 By Catherine Doyle In Bitrise
That's Nathan Hillyer, Director of Engineering at ForeFlight, on what happened after his team started running their GitHub Actions workflows on Bitrise Build Hub. Until last month, trying that for yourself meant talking to sales first. That’s fine for a 300-person engineering org evaluating a CI overhaul, but it made no sense for the two-pizza team that just wants to know whether changing one line of YAML will meaningfully speed up their Xcode builds. That's fixed.
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oril

AI Is Reopening the Build-versus-Buy Question in PropTech

Sep 23, 2026 By Zorian Fedoryga In ORIL
For much of the past decade, the PropTech default was straightforward: buy the commodity software and reserve engineering capacity for what differentiated the product. AI-assisted development is moving that line, and the answer looks less obvious than it did two years ago. For the broader framework, including cost, integrations, vendor lock-in, data ownership, and long-term maintenance, see our guide to build vs buy real estate software.
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Ep 92 | Making AI Fluent in Your Business

Sep 23, 2026 By Cloudera, Inc. In Cloudera
Every new AI chat is another first day on the job. Rob Collie describes today’s general-purpose AI as a brilliant new hire who wakes up on their first day every time you start a new conversation. It may understand your industry, but your workflows and business context have to be explained all over again. In this episode of The AI Forecast, Paul Muller speaks with Rob Collie, founder and CEO of P3 Adaptive, former Microsoft product leader for Excel and Power BI, and author of “Fair Game: Bringing AI Into Reach for All Business” to explore why business context can make or break enterprise AI.
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bugraptors

Crowdsourced Testing for Mobile Apps: Overcoming the Device and OS Fragmentation Problem

Sep 23, 2026 By Raghav Vashishth In BugRaptors
The mobile sector has undergone massive transformations since the early days. What used to be a predictable verification exercise is now an intricate web of competing hardware manufacturers, custom firmware distributions, distinct chipset designs, and fast software update schedules. Modern software teams face hundreds of real-world variables every time they prepare a public build. Managing device fragmentation stands as one of the most demanding technical roadblocks in software verification.
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Kafka replication: high stakes, high lock-in

Sep 23, 2026 By LensesIO In Lenses
New research with 150 Kafka practitioners reveals they have a love-and-hate relationship with the replication tools. Most use MirrorMaker2 until it lacks enterprise compliance and complexity pinches. Confluent Cluster Linking is powerful, but organisations hate being locked in. 70% of respondents would make the switch to a different tool if they were assured the migration was easy. Join Guillaume Aymé, the CEO of Lenses.io, who will be discussing the state of Kafka replication with the author of the research, Dinesh Chandrasekhar, the Founder of Stratola Research.
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kong

AI Governance Tools and Platforms: An Enterprise Guide

Sep 23, 2026 By Kong In Kong
*Enterprise AI governance requires a composed stack connecting high-level risk and compliance oversight with real-time runtime enforcement. While oversight tools manage inventories, approvals, and evidence, AI gateways apply policy controls directly to live model, API, MCP, and agent traffic. Implementing both runtime controls and structured governance frameworks ensures comprehensive security, observability, and cost management across your entire AI estate.*
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smartbear

Autonomous doesn't mean unsupervised: Trusting agentic QA without losing oversight

Sep 23, 2026 By Bridges Smith In SmartBear
AI agents review code, triage incidents, summarize tickets, and draft documentation, and the industry has largely decided the help is worth having. Leadership is often pushing teams for AI productivity gains and many teams accept the mandate. The obstacle is what happens next: the agent works on the wrong thing, the time and money spent on it return nothing, and the team ends up less efficient than before it started by creating more work.
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thoughtspot

4 Signs Your AI has a Context Problem, Not a Model Problem

Sep 23, 2026 By Laura Cohen In ThoughtSpot
Most AI agents can write SQL. The problem is they write it against the wrong definition of revenue, for the wrong team, using the wrong business rules, and you won't catch that in a demo. Before you evaluate a single semantic layer vendor, there are four things worth getting right first. The semantic layer market has never been more crowded. Every major analytics vendor, data platform, and BI tool now claims to have one.
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appsignal

Add an App With Your Coding Agent

Sep 23, 2026 By Serena Chou In AppSignal
You can now ask your coding agent to set up AppSignal in your application. Give it a prompt, let it follow the installation instructions, and watch a checklist fill in as data starts arriving. Installing AppSignal was already straightforward, but it still meant checking your environment, adding the right integration, creating an app, handling credentials, and confirming that telemetry arrived. These are useful checks, but they don't all need your attention.
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