How will AI change the future of software development teams?
AI is revolutionizing the landscape of software development, but it isn’t about replacing human developers. Instead, we are entering an era of “AI-augmented development,” where AI tools are becoming invaluable allies, enhancing human abilities across the software lifecycle. AI will help close the gap between the high demand for custom software and the limited engineering capacity worldwide.
In this new paradigm, AI is stepping in to assist with repetitive and time-consuming tasks, allowing developers to focus on more complex problems. The evolution of software teams will include a new breed of AI-native developers specializing in integrating AI into applications and leveraging AI tools. With AI, the potential productivity boost for developers is extraordinary, allowing them to work faster and smarter. However, while AI can amplify a developer's capabilities, it cannot replace the human creativity, problem-solving, and decision-making that are essential to successful software development. The future belongs to teams that can skillfully blend AI with human expertise.
The magic of RAG is in the retrieval
Any leading large language model will do. To succeed with retrieval-augmented generation, focus on optimizing the retrieval model and ensuring high-quality data.
The decades-long pursuit to capture, organize and apply the collective knowledge within an enterprise has failed time and again because available software tools were incapable of understanding the noisy unstructured data that comprises the vast majority of the enterprise knowledge base. Until now. Large language models (LLMs) that power generative AI tools excel at processing and understanding unstructured data, making them ideal for powering enterprise knowledge management systems.
Supercharge your SaaS with an integration marketplace
The average company uses 342 SaaS apps prompting B2B software buyers to consider integrations a top priority in their purchasing decisions. However, simply providing connections between platforms is not enough for SaaS companies to deliver a good user experience. Customers should be able to discover, activate and monitor integrations without calling customer support.
An integration marketplace offers an elegant solution to software connectivity challenges. This feature provides a centralized, self-service hub for integrations that delivers a seamless experience for customers connecting your application to their other tools. Users can create a more cohesive tech stack with just a few clicks. Marketplaces save customers time and resources and position your company as a more flexible, scalable and indispensable partner, driving higher product adoption and customer retention.
SMBs IT challenges: The quest for data-centric talent
Decision-makers are increasingly relying on data analytics to inform everything from market strategies to operational efficiencies. S&P Market Intelligence 451 Research’s global survey of 2,362 executives working at small- to medium-sized businesses (SMBs) cites a greater appreciation for the value of data among organizations that have historically tended not to invest as heavily in tools and platforms that maximize the business value of the data collected.
And while large enterprises continue to invest in technology and staff to glean data findings, small- to medium-sized businesses can struggle to extract the full value from their data investments. The root of this issue often lies in the composition of their IT teams. small- to medium-sized businesses frequently employ IT generalists who, while skilled in various aspects of technology, may lack the deep expertise required to manage data effectively. This gap in specialized knowledge can prevent businesses from fully leveraging their data assets.
Log files: What are they, why do they matter and how to protect them?
Log files come with many challenges. Firstly, they exist as enormous volumes of data. Almost everything that a user does is recorded, meaning that they quickly pile up, and not all of them are useful.
Secondly, they aren’t all uniform as they come in various shapes and sizes, serving various purposes. Event logs, system logs, access logs and server logs are just some of the various types that are collected and stored. This large volume of data means that processing and analyzing logs for use can be time-consuming and complex.
Is your network future-proofed for the age of AI?
The internet was a massive, revolutionary invention. A once-in-a-lifetime breakthrough. And yet, it was not an overnight sensation in terms of consumer adoption. This may surprise some people today. From the early web browsers in 1992 to the explosion of dot-coms in 1998, it took roughly six years for the general public to truly embrace the world wide web. Fast forward to today, and the landscape has dramatically shifted.
Consider the recent phenomenon of ChatGPT, the large language model chatbot launched by OpenAI in late 2022. Within a year, consumer adoption of this AI technology reached a fever pitch. For a while, it was all anyone in tech and business circles could talk about. In fact, they still are. This highlights a critical difference in our current technological era, which is that innovation is happening and being adopted at an unprecedented pace.
Old habits, new threats -- Why more phishing attacks are bypassing outdated perimeter detection
Perimeter solutions such as Secure Email Gateways (SEGs) have long been a cornerstone of email security, historically serving as the primary line of defence against malicious emails entering an organization. Utilizing legacy technology such as signature and reputation-based detection, SEGs have provided pre-delivery intervention by quarantining malicious attacks before they reach the end recipient.
Why, then, are 91 percent of cybersecurity leaders frustrated with their SEGs, and 87 percent considering a replacement?
Why is the world witnessing a surge in data breaches?
While the world of cybersecurity has always been fairly unpredictable, what’s certain is that data breaches are on the rise. But what’s driving this trend, how long will it continue, and what can organizations do about it?
According to the 2023 Annual Data Breach Report by the Identity Theft Resource Center (ITRC), a non-profit organization, data compromises have leapt up in the past two years. From the previous record of 1,860 in 2021 they dropped slightly to 1,801 in 2022 but rebounded to reach a new high of 3,205 last year. That’s an increase of 72 percent over just two years.
The importance of preparing data for AI integration
Despite the importance and timely arrival of the EU AI Act, there remain some major compliance concerns and the impact it will have on AI adoption and governance strategies. In fact, a recent survey found that having the proper AI governance in place is a top priority for 41 percent of business decision-makers. However, around one-quarter of UK firms have yet to make preparations for AI, and this is partly due to lingering confusion over their obligations.
Yet, the requirements set out by the Act are specific, particularly for “businesses or public authorities that develop or use AI applications that constitute a high risk for the safety or fundamental rights of citizens.” This high-risk category can include anything from law enforcement and employment systems to those used by life sciences and critical infrastructure organizations.
Why enterprises need real-time visibility of their invisible threats
It's not what you know, it's what you don’t know that bites you. Cyber attacks, internal rogue employees, and general operational missteps are a constant at enterprises. The cost, both financially and human operationally, impacts morale and budgets.
Many enterprises think they have what they need to defend their attack surfaces, except for one thing: a clear view of ALL the assets that make up that attack surface -- devices, users, applications and vulnerabilities. Too many security teams are trying to protect expanding and increasingly complex infrastructures without knowing all their risk exposures.
Cheapfakes and deepfakes -- How to spot them
In recent weeks, the term ‘cheapfake’ has shot to the forefront of our national consciousness. Cheapfakes -- and their equally disruptive counterpart, deepfakes -- are becoming much more prevalent today, with the volume of this misleading content estimated to be doubling online every six months. That’s why the world’s leading search engines, social media networks and content publishers are taking notice. In recent weeks, Google announced a far-reaching plan to reduce the discoverability of deepfakes in their search rankings.
Luckily, you don’t need the resources of Google to spot altered media. Here, we’ll examine the primary differences between cheapfakes and deepfakes as well as the AI-based tools that can be used to decisively detect them.
A lack of resources and talent leaves UK SMEs dangerously exposed
In the last few years, we have witnessed some of the most seismic changes to the IT security landscape -- from global pandemics and geopolitical issues to a global energy crisis, growing cybersecurity threats, multiple country elections, and subdued economic conditions. But regardless of stretched IT and cybersecurity budgets, and a significant IT skills shortage, threat actors continue to innovate as cyber threats evolve at breakneck speed. Organizations have no choice but to defend themselves.
Today, cyberattacks are increasingly targeting small to medium-sized enterprises (SMEs), according to JumpCloud’s latest Q3 2024 SME IT Trends Report. Forty-four percent of UK SMEs have been victims of cybersecurity attacks. Nearly two-thirds (60 percent) report multiple attacks in 2024. Smaller organizations often lack the manpower of larger corporations, with nearly half (48 percent) of UK survey respondents claiming that despite their best efforts, they lack the resources and staff to secure their organization against cybersecurity threats. This is compounded by a lack of access to skilled cybersecurity professionals, with many SMEs having IT teams consisting of only one or two people.
The CrowdStrike incident exposed the urgent need for modern DevOps practices
On July 20th, 8.5 million devices running Windows crashed when cybersecurity giant CrowdStrike released a faulty software update. The ensuing outage wreaked havoc across nearly every major business sector: flights were grounded, medical procedures were delayed, and news stations couldn’t broadcast.
For the companies affected, the cost implications could reach tens of billions of dollars. However, this incident is part of a much larger, growing problem. Poor software quality cost the US economy at least $2.41 trillion in 2022. With customers and employees increasingly reliant on digital services, organizations urgently need to reassess how they deliver software to protect themselves from future failures.
How organizations can master incident reporting obligations under NIS2
The new NIS2 directive is designed to strengthen the cyber resilience of over 160,000 companies that operate in the EU -- either directly or indirectly. Coming into force by 17th October, NIS2 regulations will outline how these essential entities can combat increasingly sophisticated and frequent cyber attacks.
Notwithstanding delays in the implementation of local legislation, the NIS2 directive provides an indication of the compliance obligations affecting those organizations which fall within the scope of the new rules. Ultimately, NIS2 aims to reduce inconsistencies in cyber security resilience by being the “single source of truth” for regulatory bodies to oversee how organizations implement increasingly stringent cybersecurity frameworks. As we have seen in recent weeks, these are crucial, especially during large-scale cybersecurity incidents or crises.
The dawn of the AI-enabled intern
On paper, artificial intelligence makes for the perfect intern -- it’s keen to please, happy to do anything thrown its way, and gets on with tasks so efficiently. It’s also prone to making mistakes. And like a human intern, AI tools need training and monitoring rather than being catapulted straight into senior positions -- it is extremely well suited to the repetitive and predictable tasks that we often ask junior staff to handle.
Unlike people, AI works 24/7, never stresses out -- it can complete a vast number of tasks in a short period of time. This makes it ideal for the mundane jobs that people tend to find boring and time-consuming. Take a function such as VAT ledger data analysis, which can contain millions of rows of data -- for a human to correctly analyze every row would not only take an age but would also be mind-numbingly boring. By contrast, AI can examine it in seconds -- think of it as an ‘infinite intern’.
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