# airline Published articles for airline. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## AWS agents will suggest your new flights. Code decides what gets booked. DevFeed: [AWS agents will suggest your new flights. Code decides what gets booked.]() Original publisher: [Read original article]() Author: Meredith Shubel Published: 2026-09-15T21:27:21Z Content type: news Language: en Sources: [The New Stack]() Topics: [AWS Step Functions](), [Amazon Bedrock AgentCore](), [Orchestration](), [Generative AI](), [Amazon Web Services]() Tags: [ai-agents](), [ai-engineering](), [airline](), [amazon-bedrock-agentcore](), [aws](), [aws-step-functions](), [cloud-services](), [generative-ai](), [orchestration]() ### AI overview AWS published a Step Functions pattern for airline rebooking in which Amazon Bedrock AgentCore agents propose itineraries and compensation messages, while deterministic workflow steps validate proposals before reservations change or payments are issued. ### Source excerpt AWS published a new Step Functions pattern this week that gives AI agents a role in airline rebooking while keeping The post AWS agents will suggest your new flights. Code decides what gets booked. appeared first on The New Stack. ## How AvioBook builds turnaround insights from operational data with Amazon Bedrock AgentCore DevFeed: [How AvioBook builds turnaround insights from operational data with Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: Petra Lafond Published: 2026-09-10T15:53:05Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [data](), [Software]() Tags: [agentic](), [agents](), [airline](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [analytics](), [apis](), [customer-solutions]() ### AI overview AvioBook prototyped Connected Analytics on Amazon Bedrock AgentCore to turn flight and ground-operations data into evidence-based answers about airline turnaround delays. ### Source excerpt AvioBook, a Thales Group Company, prototyped Connected Analytics on Amazon Bedrock AgentCore to turn AvioBook Connect's operational data into plain-language, evidence-based answers for airline managers and dispatchers, helping them find and act on the causes of flight turnaround delays. ## Loyalty points fraud is funding hacker holidays (Lock and Code S07E18) DevFeed: [Loyalty points fraud is funding hacker holidays (Lock and Code S07E18)]() Original publisher: [Read original article]() Author: Malwarebytes Labs Published: 2026-09-07T18:23:18Z Content type: article Language: en Sources: [Malwarebytes]() Topics: [Cybercrime](), [passwords]() Tags: [account-takeover](), [airline](), [airline-miles](), [credit-card-points](), [cybercrime](), [fraud](), [hotel-rewards](), [loyalty-account](), [loyalty-points](), [loyalty-points-fraud](), [podcast](), [points](), [rewards-account](), [rewards-points]() ### AI overview A Lock and Code podcast episode examines loyalty-points theft, why criminals target points balances, and ways companies and consumers can protect against fraud. ### Source excerpt This week on the Lock and Code podcast, we speak with Kim Sutherland about loyalty points fraud and how everyday people can stay safe. ## This month in security with Tony Anscombe - August 2026 edition DevFeed: [This month in security with Tony Anscombe - August 2026 edition]() Original publisher: [Read original article]() Author: Editor Published: 2026-08-31T08:55:00Z Content type: news Language: en Sources: [WeLiveSecurity]() Topics: [Cybersecurity](), [Critical Infrastructure](), [hugging face](), [Artificial Intelligence](), [OpenAI](), [Flight](), [Network](), [spoofing](), [incident]() Tags: [ai](), [airline](), [critical-infrastructure](), [cybersecurity](), [hugging-face](), [incident](), [network](), [openai](), [spoof](), [video]() ### AI overview Tony Anscombe reviews major cybersecurity stories from August 2026, including the Hugging Face hack involving OpenAI agents, attacks on critical infrastructure, a spoofed airline Wi-Fi network, and the shutdown of fraudulent call centers in Ukraine. ### Source excerpt Details about the Hugging Face hack, critical infrastructure under attack, a spoofed in-flight Wi-Fi network, and more of this month's cybersecurity news ## Virgin Atlantic sharpens customer journeys with ChatGPT Work DevFeed: [Virgin Atlantic sharpens customer journeys with ChatGPT Work]() Original publisher: [Read original article]() Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [data](), [dataset]() Tags: [airline](), [analysis](), [analytics](), [chatgpt](), [data](), [explore](), [insights](), [product](), [strategy](), [tools](), [work]() ### AI overview Virgin Atlantic uses ChatGPT Work to connect customer-journey information, accelerate competitive research, support product planning, and turn insights into strategy and digital-experience decisions. ### Source excerpt Virgin Atlantic is accelerating research, product planning, and decision-making with ChatGPT Work, helping teams connect signals across the customer journey. ## Flight Booking & Airlines Quantitative UX: 3 High-Level Takeaways from 30+ Charts DevFeed: [Flight Booking & Airlines Quantitative UX: 3 High-Level Takeaways from 30+ Charts]() Original publisher: [Read original article]() Author: Richard Lam Published: 2026-06-24T08:04:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Flight](), [User experience (UX)](), [data](), [benchmarking](), [Mobile](), [A/B Testing]() Tags: [a-b-testing](), [airline](), [apps](), [article](), [booking](), [desktop](), [mobile](), [research](), [survey](), [travel](), [ux]() ### AI overview Baymard reports quantitative UX findings from a survey of 3,125 US online shoppers who use flight-booking and airline sites. The article highlights that shoppers use multiple sources when searching for flights, three quarters belong to at least one airline loyalty program, and business travelers are more likely to bundle travel-related bookings. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 30+ new insights on Flight Booking & Airline shopper habits and preferences 3,125 US online shoppers surveyed in this quantitative UX study Flight Booking & Airline shoppers use a variety of sources when looking for flights, are highly likely to participate in loyalty programs, and commonly bundle other travel-related bookings at the same time, particularly when travelling for business. At Baymard, we've just released new Quantitative Insights into people who shop on "Flight Booking & Airlines" sites, expanding our understanding of the habits and preferences of online shoppers in this category. These insights are visualizations based on survey data that supplement and support our large-scale UX research findings and benchmarking of the Flight Booking & Airlines industry. The 30+ insights address the Flight Booking & Airlines online shopping experience, spanning a breadth of topics: sources for flight searching, types of add-ons purchased, usage of apps and external tools, importance of cancellations, sales and scarcity incentives, and motivations for bundling and loyalty programs. Some of the charts also explore sub-segments of the broader audience such as business travelers and whether they are more likely to purchase add-ons, or how device usage between desktop and mobile changes as flight price becomes more expensive. These Quantitative Insights empower you to align stakeholders through objective, survey-backed data, streamline A/B testing with high-potential hypotheses, and discover and address industry-specific UX challenges. In this article, we'll highlight 3 high-level findings that reflect how shoppers evaluate and purchase flights online: Flight shoppers use a variety of sources when looking for flights Three quarters of flight shoppers are part of at leas ## Illegal vs Unwanted States DevFeed: [Illegal vs Unwanted States]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-04-28T15:14:09Z Content type: article Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [systems](), [Software](), [data](), [Network](), [Server]() Tags: [airline](), [data](), [data-type](), [event](), [network](), [optional](), [servers](), [software](), [state](), [systems]() ### AI overview The article distinguishes illegal states, which a system must never enter, from unwanted states, which may be temporarily acceptable but must not persist or develop into illegal states. It argues that systems should represent unwanted states because external inputs and unreliable infrastructure make them unavoidable, while detection and resolution mechanisms limit their consequences. ### Source excerpt An illegal state is a state we never want our system to be in. An unwanted state is a state we don't want to stay in. Many states that we wish were illegal are actually unwanted. Considering a calendaring software which stores calendar events as {user: {events: [event]}}, where each event has a start and end time. This allows one person to attend two events at the same time. We might consider this illegal and replace the data type with {user: {time: optional event}} which makes this impossible. However, a scheduling conflict isn't illegal, only unwanted! It is possible for a person to sign up for two overlapping events. Maybe they're supposed to choose one event, maybe they'll decide which event to go to later, maybe one of the events doesn't actually represent an in-person meeting. In that case it's acceptable, if not ideal, to remain in the unwanted state. Other unwanted states lead to invalid states if not exited quickly. An airline flight is in an unwanted state if there are more passengers booked to fly than seats available. This must be resolved before passengers actually board, as "more passengers physically on the plane than seats available" is an illegal state. In some cases, an unwanted state does not lead to illegal states, but permanently remaining in the unwanted state is still a problem. We might guarantee that a network partition does not ever lead to inconsistent data. Even though the unwanted state of a network partition cannot cause the illegal state of corrupt data, we still have a big problem if we don't ever fix the partition. Why systems must represent unwanted states Generally, unwanted states can happen if we don't have complete control over our system's behavior. We can't guarantee our network is perfectly reliable, our servers are always up, our users all put in correct data. If our system gets input from the external world then the world can push us into an unwanted state. We need to be able to detect these states so we can resolve them. E ## How Virgin Atlantic uses AI to enhance every step of travel DevFeed: [How Virgin Atlantic uses AI to enhance every step of travel]() Original publisher: [Read original article]() Published: 2025-12-08T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [Development](), [AI Development](), [OpenAI](), [ChatGPT](), [Finance](), [data](), [Mobile](), [Support]() Tags: [ai](), [airline](), [chatgpt](), [code](), [customer-experience](), [data](), [development](), [mobile](), [openai](), [real-time](), [software-development](), [speed](), [support](), [travel]() ### AI overview Virgin Atlantic is using AI, including OpenAI and ChatGPT Enterprise, to accelerate software development, improve finance analysis and decision-making, support employees, and enhance customer experiences across travel services. ### Source excerpt Virgin Atlantic CFO Oliver Byers shares how the airline is using AI to speed up development, improve decision-making, and elevate customer experience. ## Alaska Airlines reaches new heights with the help of variables DevFeed: [Alaska Airlines reaches new heights with the help of variables]() Original publisher: [Read original article]() Author: Caitlin Lee Published: 2024-04-16T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [User interface design](), [Accessibility](), [Sketch](), [Digital signage]() Tags: [airline](), [browser](), [collaboration](), [components](), [design](), [features](), [figma](), [mobile](), [prototyping](), [real-time](), [standards](), [tech-stack](), [tools]() ### AI overview Alaska Airlines uses Figma variables and its Auro design system to maintain consistent experiences across its website, mobile interfaces, digital signage, and kiosks. The change saved designers an average of 11 hours per week and improved documentation, collaboration, and consistency between design and engineering. ### Source excerpt By leveraging advanced design system features like variables, Alaska Airlines takes the experience of air travel to a new level. ## Passenger airlines will charge by volume and weight DevFeed: [Passenger airlines will charge by volume and weight]() Original publisher: [Read original article]() Author: Graham King Published: 2008-05-30T23:38:43Z Content type: opinion Language: en Sources: [Graham King]() Topics: [Flight]() Tags: [airline](), [ideas](), [volume]() ### AI overview The article argues that passenger airlines will eventually price travel based on passengers' total weight and the volume or weight of their luggage, because weight affects fuel costs. It predicts that competitive pressure will force airlines to adopt this model. ### Source excerpt I'm just saying