Forem: SlashData Team

How to harness AI Agents without breaking security

SlashData Team — Tue, 02 Dec 2025 16:58:25 +0000

We are entering a new era in which AI doesn’t just generate content, it acts. AI agents, capable of perceiving their environment, making decisions, and taking autonomous actions, are beginning to operate across the enterprise. Unlike traditional Large Language Models (LLMs) that work within a confined prompt-response loop, agents can research information, call APIs, write and execute code, update records, orchestrate workflows, and even collaborate with other agents, all with little to no human supervision.

The excitement and hype surrounding AI agents is understandable. When designed and implemented correctly, these agents can radically streamline operations, eliminate tedious manual tasks, accelerate service delivery, and redefine how teams collaborate. McKinsey predicts that agentic AI could unlock between $2.6 trillion and $4.4 trillion annually across more than sixty enterprise use cases.

Yet, this enthusiasm masks a growing and uncomfortable truth. Enterprises leveraging agentic AI face a fundamental tension: the trade-off between utility and security. An agent can only deliver real value when it’s entrusted with meaningful control, but every additional degree of control carries its own risks. With agents capable of accessing sensitive systems and acting autonomously at machine speed, organisations risk creating a new form of insider threat (on steroids), and many are not remotely prepared for the security risks that agentic AI introduces.

The vast majority of leaders with cybersecurity responsibilities (86%) reported at least one AI-related incident from January 2024 to January 2025, and fewer than half (45%) feel their company has the internal resources and expertise to conduct comprehensive AI security assessments. Rushing to deploy digital teammates into production before establishing meaningful security architecture has a predictable result. Gartner now forecasts that more than 40% of agentic AI projects will be cancelled by 2027, citing inadequate risk controls as a key reason.

This blog post covers the risks that pose the greatest challenges for organisations building or adopting AI agents today and how to minimise them, enabling technical leaders and developers to make informed, responsible decisions around this technology.

Harness the power of agentic AI with our analysts' help. Talk to an analyst.

The dark side of AI agents

Rogue actions and the observability gap

Traditional software behaves predictably. Given the same inputs, it produces the same outputs. Understanding results and debugging is therefore a matter of tracing logic, replicating conditions, and fixing the underlying error. However, agentic AI breaks this paradigm. Agents do not follow deterministic paths, meaning their behaviour isn’t always repeatable even with identical inputs, and complex, emergent behaviours can arise that weren’t explicitly programmed. Worse, most systems that agents interact with today lack any understanding of why an agent took a particular action. Traditional observability wasn’t designed to understand why a request happened, only that it did.

This creates a profound observability gap, where organisations can’t understand or replay an agent’s decision sequence. A minor change in context, memory, or input phrasing can lead to an entirely different chain of tool calls and outputs. As a result, traditional debugging techniques collapse. When something goes wrong, teams are often left guessing whether the issue came from the underlying model, the agent design, an external dependency, a misconfigured tool, corrupted memory, or adversarial input.

This problem is exacerbated by the degree of autonomy an agent has, as the longer an agent operates independently and the more steps it takes without human oversight, the larger the gap between intention and action can become. Without robust audit logs designed for agentic systems, organisations can’t reliably answer fundamental questions such as: What did the agent do? Why did it choose those actions? What data did it access? Which systems did it interact with? Could the behaviour repeat?

Expanded attack surface and agents as a new insider threat

When you give an AI agent the ability to act, particularly across internal systems, you effectively create a new privileged user inside your organisation. Too often, this user is granted broad, overly generous permissions, disregarding the principle of least privilege, a cornerstone of cybersecurity. Teams often grant generous permissions because restrictions seem to “block the agent from being helpful”. However, as highlighted earlier in this post, every added degree of autonomy or access carries its own risks. Your “highly efficient digital teammate” can very quickly become a potent insider threat.

Granting agents broad access and permissions to internal documents, systems, repositories, or databases dramatically expands an organisation's attack surface, especially when these agents interact with external services. If an attacker succeeds in injecting malicious instructions through poisoned data, manipulated content, compromised memory, tampered tools, or adversarial prompts, the agent can unknowingly carry out harmful actions on the attacker’s behalf. It may leak sensitive information, modify records, escalate privileges, execute financial transactions, trigger unwanted workflows, or expose data to external systems. The danger compounds in multi-agent environments, where one agent’s compromised output can cascade into others, amplifying the impact of even small vulnerabilities.

Agentic drift

Agents operate in dynamic environments, learn, adapt, and evolve. Over time, this evolution can lead to agentic drift. An agent that performs well today might degrade tomorrow, producing less accurate or entirely incorrect results. Many factors can influence this, such as updates to underlying models, changes to inputs, changes to business context, system integrations, or agent memory. Because drift often emerges gradually, organisations may not notice until the consequences are significant, especially for agents interacting with external stakeholders (e.g. customer service agents) or operating in multi-agent workflows, where drift can cause cascading failures.

Moreover, because AI agents are inherently goal-driven, drift can emerge in which agents start optimising for the metrics they can observe, rather than the ones humans intended. This leads to specification gaming, where agents find undesirable shortcuts that technically satisfy the objective while undermining policy, ethics, or safety. For example, an agent tasked to “reduce task completion time” may quietly eliminate necessary review steps; an agent configured to “increase customer satisfaction” might disclose information it shouldn’t; or a coding agent tasked to “fix errors” might make changes that violate security or compliance constraints.

How to build agents safely

The risks of agentic AI are significant, but the solution is not to avoid agents altogether. The value is too great, and the competitive pressure is too high. Instead, organisations must treat agentic AI as a new class of enterprise technology, requiring its own security model, governance structures, and operational rigour. As the saying goes, “a chain is only as strong as its weakest link”. Don’t introduce a weaker one. To position your organisation to harness the full potential of agentic AI safely, it’s essential to understand how to mitigate these risks.

Establish a rigid command hierarchy. To ensure accountability, AI agents must operate under a clearly defined chain of command where human supervision is technically enforced. Every agent should have a designated controller(s) whose directives are distinguishable from other inputs. This distinction is crucial because agents process vast amounts of untrusted data (such as emails or web content) that can contain hidden instructions designed to hijack the system (prompt injection). Therefore, the security architecture must prioritise the controller’s voice and system prompts above all other noise. Furthermore, for high-stakes actions, such as deleting important datasets, sharing sensitive data, authorising financial transactions, or modifying security configurations, explicit human confirmation should always be required (“human-in-the-loop”).

Enforce dynamic, context-aware limitations. Security teams must move beyond broad, static permissions and instead enforce strict, purpose-driven limits on what agents can do. Agents’ capabilities must adapt dynamically to the specific context of the current workflow, extending the traditional principle of least privilege. For example, an agent tasked with doing online research should be technically blocked from deleting files or sharing data, regardless of its base privileges. To achieve this, organisations require robust authentication and authorisation systems designed specifically for AI agents, with secure, traceable credentials that allow administrators to review an agent’s scope and revoke permissions at any time.

Ensure observability of reasoning and action. Transparency is the only way to safely integrate autonomous agents into enterprise workflows. To ensure agents act safely, their operations must be fully visible and auditable. This requires implementing a logging architecture that captures more than just the final result. It must record the agent’s chain of thought, including the inputs received, reasoning steps, tools used, parameters passed, and outputs, enabling organisations to understand why an agent made a specific decision. Crucially, this data cannot remain buried in server logs; it should be displayed in an intuitive interface that allows controllers to inspect the agent's behaviour in real time.

Organisations that fail to invest early in these foundations may find themselves facing a new generation of incidents, faster, more powerful, and more opaque than anything their current security posture was designed to handle.

The next wave of innovation will not be driven by models that generate text, but by systems that take action. Is your organisation ready for what those actions entail? At SlashData, we can help you navigate the challenges of implementing and scaling agentic AI systems by providing data-backed evidence and insights on how developers successfully create agentic AI workflows, avoiding common pitfalls along the way.

About the author

Alvaro Ruiz Cubero, Market Research Analyst, SlashData
Álvaro is a market research analyst with a background in strategy and operations consulting. He holds a Master’s in Business Management and believes in the power of data-driven decision-making. Álvaro is passionate about helping businesses tackle complex strategic business challenges and make strategic decisions that are backed by thorough research and analysis.

Agentic AI has moved from lab to production, ChatGPT and GitHub Copilot are the leaders, says AI analyst firm SlashData

SlashData Team — Fri, 07 Nov 2025 12:11:19 +0000

SlashData has released new findings revealing the real-world adoption of AI in late 2025.

As early adopters and reliable predictors of technology trends, developers provide a window into where AI is heading next. Based on their responses, SlashData highlights three trends transforming the AI landscape: Agentic AI goes mainstream, AI coding tools preferences, Gen AI adoption blockers.

AI coding tools: ChatGPT and Copilot dominate

ChatGPT (64%) and GitHub Copilot (49%) lead in adoption and satisfaction among professional developers using AI coding tools. JetBrains AI shows low adoption and high satisfaction, signalling a growth opportunity. Adoption varies by experience:

“Satisfaction with ChatGPT drops notably among experienced developers, as they appear less happy with its accuracy, scalability, and ease of use compared to newcomers”
says Bleona Bicaj, Senior Market Research Analyst at SlashData

Agentic AI goes live: half of adopters already in production

50% of professional developers adopting AI functionality have already deployed Agentic AI into production, marking the end of the experimental era. Text generation, summarisation or translation (28%) is the top use case for Agentic AI. AR/VR and IoT projects lead adoption. Reliability and security concerns might be slowing the adoption of agentic AI in backend systems.

“Large enterprises’ governance complexity may be neutralising their resource advantages in agentic AI deployment”,
says Alvaro Ruiz Cuber, Market Research Analyst at SlashData

Data privacy & security fears slow down AI rollout

Organisations face two core hurdles: privacy risks that delay approval and quality concerns that undermine developer trust as only 25% of professional developers are currently building applications powered by Generative AI.

“Organisations must prioritise enterprise-level safeguards to prevent projects from stalling under compliance reviews.”
urges Nikita Solodkov, Market Research and Statistics Consultant at SlashData

Full analysis and 29 charts are instantly available to all through the SlashData Research Space.

The insights come from 12,000 developers surveyed in Q3 2025. The six State of Developer Nation reports cover AI, FinOps, Cloud and Language communities.

About SlashData

SlashData is an AI analyst firm. For 20 years, we have been working with top Tech brands like Google, Microsoft and Meta. We track software technology trends to empower industry leaders to make product and marketing investment decisions with clarity and confidence, and drive the world forward with technology.

Developer Trends 2025: 2 webinars on how many developers are there and AI in Tech

SlashData Team — Fri, 25 Apr 2025 15:32:53 +0000

Staying true to our commitment to transform noise into actionable insights, SlashData is bringing you two webinars rich in data and insights and the developer trends you need to know in 2025.

TL;DR

Here's the quick preview. Keep reading for more details
How many developers are there? Ending the debate with data | April 24, 2025 | Watch here
Artificial Intelligence in Tech: usage, adoption and challenges in 2025 | May 14, 2025

Both events are free to attend, but registration is required.

Developer Trends 2025: Artificial Intelligence in Tech - Usage, Adoption, and Challenges in 2025

When 14 May 2025 - 9am PST/5pm UK
Platform YouTube
Presented by Konstantinos Korakitis, Director of Research, SlashData & more TBA
Hosted by Moschoula Kramvousanou, CEO, SlashData

How is AI used in Tech? This will be our main theme for this live session with SlashData's expert analysts.

More specifically, we will look at Generative AI and

How Tech professionals have incorporated it into their processes
How sales and marketing professionals utilise it for performance
What challenges are organisations facing with its adoption
How are developers integrating it into their projects
Concerns about its usage +Live Q&A with your questions

Save your spot for the AI in tech webinar.

Watch now: Global developer population trends: How Many Developers Are There?

When 24 April 2025 - 9am PST/5pm UK
Platform YouTube
Presented by Konstantinos Korakitis, Director of Research, SlashData
Hosted by Moschoula Kramvousanou, CEO, SlashData

In this session, we will look at the global developer population. More specifically, Konstantinos will present the latest data and insights on:

The growth of the developer population in the past years
The developer population breakdown by professional status
The developer population breakdown by region
The developer population breakdown by type of software project
The developer population breakdown by programming language community
The developer population breakdown by industry vertical
The developer population breakdown by company size +Live Q&A

You can now watch this session anytime:
.

All insights are drawn from SlashData's independent Developer Nation survey, which gathers over 9,000 responses per wave. Learn more about the Developer Nation survey, its community and our methodology.

Inside Technology Trends: AI Chatbots & Network APIs

SlashData Team — Thu, 13 Feb 2025 14:34:36 +0000

What role are artificial intelligence and network APIs playing in shaping the tumulus digital landscape?

How much traction have AI chatbots gained in the last six months?
What does the adoption of network APIs look like among developers?

Join us for an insightful webinar where industry experts will provide data-driven answers to these pressing questions. Register here.

What You’ll Learn

This exclusive webinar will offer deep insights into key technology trends. Together we will look at the most recent data, provided by real developers.

Dive into the world of AI chatbots and Network APIs. Our expert speakers will shed light on key findings, including:

The Rise of AI Chatbots for Problem-Solving

Which roles and industries are experiencing the fastest growth in AI chatbot usage?
How has the overall adoption of AI chatbots changed over the past six months across different user groups?
How does AI chatbot usage differ between professionals, hobbyists, and students?
What regional trends are emerging in AI chatbot adoption?
What specific challenges or needs are prompting beginners and non-technical users to increasingly turn to AI chatbots for problem-solving?

Network APIs: The New Oil in the 5G Economy

What percentage of developers use network APIs?
Which regions have higher adoption rates of network APIs?
In what types of projects are developers using network APIs involved?
What functionalities of network APIs do developers use?
Which roles and industries are experiencing the fastest growth in AI chatbot usage?

Join the Conversation

Don't miss this opportunity to stay ahead of emerging technology trends. Gain insights into AI chatbot growth, network API adoption, and more—straight from industry experts.

Live Q&A: Ask our analysts your questions.

Exclusive Reports

Each topic addressed in this webinar is backed by a free-to-access, in-depth report:
- The Rise of AI Chatbots for Problem-Solving
- Network APIs: The New Oil in the 5G Economy

Meet the Experts

Our presenters bring a wealth of experience in market research and technology analysis:

Álvaro Ruiz, Research Manager
Álvaro is a market research analyst with a background in strategy and operations consulting. He holds a Master’s in Business Management and believes in the power of data-driven decision-making. Álvaro is passionate about helping businesses tackle complex strategic business challenges and make strategic decisions that are backed by thorough research and analysis.

Bleona Bicaj, Senior Market Research Analyst
Bleona is a behavioral specialist, enthusiastic about data and behavioral science. She holds a Master's degree from Leiden University in Economic and Consumer Psychology. She has more than 6 years of professional experience as an analyst in the data analysis and market research industry.

Hosted by Moschoula Kramvousanou, SlashData CEO

Where the data come from

The insights presented in this webinar come from the global, independent State of Developer Nation survey and its 27th wave which reached over 9,000 respondents worldwide. As one of the most comprehensive independent studies on developers across mobile, desktop, Industrial IoT, consumer electronics, cloud, game development, AR/VR, and machine learning, this survey, and the expert analysis after it, provides essential perspectives on the evolving tech landscape.

Reducing bias

To eliminate the effect of regional sampling biases, we weighted the regional distribution across nine regions by a factor that was determined by the regional distribution and growth trends identified in our Developer Nation research. To minimise other important sampling biases across our outreach channels, we weighted the responses to derive a representative distribution for technologies used, and developer segments. Using ensemble modelling methods, we derived a weighted distribution based on data from independent, representative channels, excluding the channels of our research partners to eliminate sampling bias due to respondents recruited via these channels. Each of the separate branches: Industrial IoT, consumer electronics, 3rd party app ecosystems, cloud, embedded, augmented and virtual reality were weighted independently and then combined.

From Code to Consumer Magic - The Software Developers Behind Everyday Electronic Devices

SlashData Team — Mon, 29 Jan 2024 17:06:19 +0000

In this post, taken out of SlashData’s public report “The State of the Developer Nation”, we dive into the world of consumer electronics and explore the profiles of developers who target different types of applications in this space. We focus on comparing their experience levels and their involvement across other sectors.

What developers are working on

Today, the number of Internet of Things (IoT) connections (15B in 2023) outnumbers humans and is forecasted to nearly double by 2030. A subset of this space, consumer electronics(CE), is focused on devices that are targeted towards consumers and often individual use. Examples of CE devices range from home security devices such as digital door locks to cameras and fitness trackers.

4.4M Developers are involved in Consumer Electronics projects

As of Q3 2023, we estimate that there are 4.4M developers who work on CE projects, making up 11% of the total developer population. In our latest Developer Nation survey, we asked developers who are involved in this space about the CE categories that they are targeting with their applications. In first place, 28% report that they are working on software for security and access products such as door locks and CCTV systems. This is closely followed by communication devices (26%), network equipment (26%), energy appliances (25%), and entertainment systems (23%). These categories stand out far above the rest, with the next most popular category – home appliances – being targeted by 18% of the developers in the CE space.

The many similarities and differences between the top CE categories are reflected in the profiles of the developers who target them with their applications. One of the most interesting aspects to consider is how experience in software development impacts the projects that these developers take on.

Developers’ experience

We find that those who target energy appliances have the highest level of experience in CE projects*. More specifically, these developers have an average of 3.9 years of experience

in this space, which is significantly higher than that of their counterparts who are not involved in energy appliances (3.1 years). This indicates that the specific challenges encountered in this category are more likely to require specialised knowledge of the CE space than across other categories. Having experience with other CE devices can be highly beneficial for development, as energy appliances need to integrate with other household systems and the energy grid. The projects that the developers who are targeting this category are much more likely than average to be smart (59% vs 43%) and have an app (49% vs 35%).

Developers who target security and access products are highly experienced in general software development.

Interestingly, developers who target security and access products have significantly more experience in software development (4.9 years) than in CE (3.4 years). This corresponds to the most significant gap between experience levels in these two groups. It indicates that working on security and access products is more likely than average to require experience in other development areas beyond CE.

With above-average experience in software development, CE developers are involved in other areas of software development. The largest overlap comes from those involved

in the industrial IoT (IIoT) development sector (43%). In particular, 56% of those involved in energy appliances also work on IIoT projects and are the most likely to do so. Using this as an example, a household energy management device only needs to manage the energy usage of one household, while an equivalent IIoT system may need to consider an entire manufacturing plant. While there are differences in scale, these two systems share the essence of what they are designed to do. This showcases the close relationship between these two sectors in the broader IoT ecosystem.

Security and access

On closer inspection of the overlap with IIoT, we see that only 28% of those who work on software targeted at entertainment systems are involved in IIoT projects. This is significantly below that of any other target category in the CE space. Instead, they are the most likely to develop games (36%) and have an above-average representation in the mobile sector (40%). Similar to the case of energy appliances and IIoT, there is a natural overlap between devices aimed at entertainment systems and these two sectors. For example, developers who develop software for smart speakers may also work on accompanying mobile applications.

Developers leverage data science to enhance security and access products.

Another interesting example can be seen among developers who target security and access products. We find that 32% of them are also involved in data science, which is significantly above average across the other categories (20%). This suggests that data from security devices is analysed in detail to improve the functionality of security and access products. For instance, advanced analytics can be used to detect suspicious access patterns in digital door locks and alert both users and authorities of potential intruders.

We measure this by comparing the median number of years that the developers within each category have worked on software projects. Medians are estimated from grouped frequency data.

This article is part of the developer insights offered in the State of the Developer Nation 25th Edition. You can access the full report which covers:

Language communities - An update
Creating A Sense Of Community - How Developers Interact And Engage With Their Peers
How Generative AI Will Affect Developers' Work
Web3 Unveiled - Exploring The Diverse Landscape Of Web3 Development Projects
From Code To Consumer Magic - The Software Developers Behind Our Everyday Electronic Devices
What Are People Building In AR/VR?

Want to dive deeper into developer data on consumer electronics, IoT or Industrial IoT? Let’s talk.

What are developer marketing, relations and tooling professionals working on?

SlashData Team — Mon, 06 Nov 2023 12:42:09 +0000

The Developer Program Leaders survey is back! Time to refresh what we know about the work, challenges and priorities of developer marketing, developer relations and developer tooling professionals.

In the previous survey wave, we discovered that the

No1 challenge for Developer Relations professionals was growing their community.
Developer Program Leaders Survey - 10th Edition

Are you working in:

Developer Marketing
Developer Relations
Developer Advocacy
Developer Tooling
With a developer program?

What is yours? What KPIs are you using to measure success?

Answering questions like these helps map the world of Developer Marketing, Relations and tooling.

At the same time, it helps the global community understand, relate and learn about the challenges these professionals face, the metrics they use, and where they spend their time and budget.

Respond to the Developer Program Leaders survey.

What you gain by spending ±8 minutes responding:

Full access to the findings both in a report that illustrates the highlights and key graphs, and in an interactive session where our research analysts and the community will come together to discuss key findings and impact on the industry.
A chance to win exclusive DevRelX swag
You participate in a community effort to understand and improve how your peers work and set their strategy

How long is the survey?

It is short. You’ll need ±8 minutes

This survey helps better understand how and what developer marketing, relations and tooling professionals work on, including how they:

Run their developer programs
Prioritise their work
Segment their audience
Measure success
Justify the value of their developer program to senior management and more!

What types of questions does this survey ask?

Which regional markets does your strategy target?
Which resources take most of your budget?
What are the main challenges for your Developer Relations efforts this year?
Do you segment your developer audience? How?

Here are some results from the previous survey wave:

It’s insights like these that you will be able to access by responding.

Do you want to help professionals elevate their DevRel game?

Have your say!

What are the main challenges for developer programs?

SlashData Team — Wed, 22 Feb 2023 12:05:38 +0000

It’s that time of the year again! The time when we run the Developer Program Leaders survey to hear from those who work with developer programs.
It's a community effort!

The goal?

To understand the challenges developer program managers face, how they prioritise their resources and activities and offer insights into how they compare against other professionals in the field.
Interested already? You’ll need ±8 minutes. Take the survey

Who can participate?

We’re looking for professionals who are working in or with developer programs. This includes professionals in the following roles:

Developer relations practitioner
Developer marketing practitioner
Developer product architect/engineer
Community manager
VP/director/manager of a developer program
Analyst / analyst relations / research manager
Product management
General marketing (non-developer specific)
General management (CxO/VP/director/founder)
…and more

What do participants gain?

Those who will take the survey will gain:

1.Unlimited access to the survey results with a report that illustrates the highlights and key graphs
2.All findings will be discussed in an interactive session where our research analysts and the DevRelX community will come together to discuss – Are you a DevRelX member? Join our community here!
3.A chance to win exclusive DevRelX swag.
4.You become involved in a collective effort to understand and improve how your peers work and set their strategy

What types of questions does this survey ask?

Which regional markets does your strategy target?
Which resources take most of your budget?
What are the main challenges for your Developer Relations efforts this year?
Do you segment your developer audience? How?

Here are some results from the previous survey wave.

By responding you will gain access to more insights like these.
Do you want to help professionals elevate their DevRel game? Have your say!

How companies and DevRel serve the communities developers join

SlashData Team — Wed, 04 Jan 2023 12:29:02 +0000

If you have been following Developer Relations and Marketing for a while, you might have noticed how the community is becoming a more and more integral part of all strategic activities. Developer Relations is becoming (if not already) a community-led effort.

There is a huge benefit to any vendor to maintain a community for all the reasons that data shows us. If we can enable developers get more out of a product, if we can enable them to be excited about the product, share their experience with their peers and also progress through the community member’s lifescycle from new joiner to expert, we are helping them progress in their career and we’re also getting them more invested in our product and ecosystem. If you keep those core needs in mind, that’s when vendor communities start to add value.
Jamie Langskov, Community and change management strategist.

Naturally, this leaves us asking:

Where do communities fit in the perception of developers?
Why are developers joining communities?
How are developer-facing professionals address developers’ community needs?

We don’t have to guess these answers. We just need to look at the data Jamie is referring to. These data come from 2 surveys run by SlashData: the Developer Nation survey (developer-focused) and the Developer Program Leaders survey (DevRel-focused). Let’s look together at the insights these bring us.

Where do communities fit in the perception of developers?

Developers join communities to learn. According to the Q3 2022 Developer Nation survey, which surveyed 23,790+ developers, 19% of developers rank community in the top 5 resources that companies should offer to support developers. This makes the community 7th most important resource overall, just ahead of answers in public forums and only slightly behind professional certifications.

Student developers’ professional aspirations

Having understood what makes developers join a community, we look at what the “next generation of developers” aka developers who are currently identifying as “students” look forward to.

When asked about their top career aspirations, student developers (sample size of 4,790+) listed these as their top 3 aspirations:

Solve problems
Become an expert in a domain or technology
Build innovative products/services

You can see their full responses in the graph below. What the answers to this question show is how the community can be the place where student developers’ needs are getting addressed. The community can provide the space, the resources and the interactions that can help student developers meet with their top aspirations: solve problems and gain expertise in a domain or technology.

Are organisations paying attention to developers’ community needs?

Yes, they are. And we will data-back this affirmation by looking at the data from the latest Developer Program Leaders survey, where we surveyed ~130 industry professionals in developer-facing roles. The data speaks for itself. Communities are now sharing the spotlight with other traditional popular methods of developer education. And developer-facing organisations are aware.

According to their responses, when the professionals are setting their strategy on how to talk to developers and address their technical audience needs, 73% consider community as (at least) a key part of their strategy. More specifically

34% consider community as the most important part of their strategy
39% consider community as a key part of their strategy
Only 6% do not include the community in their strategy. You can see all responses at this graph:

What are developer program leaders’ roles?
By now we have established the importance of community in a developer marketing strategy. To better understand how this strategy is implemented, we will look at the hats these developer program professionals are wearing to implement this strategy and we will also look at the community sizes – for perspective.

With 73% of those professionals reporting community as a key part of their strategy, it comes as no surprise that 34% of them have “Community Manager” as their professional title, the second most popular, right behind “Developer Relations Practitioner” and only slightly above “Developer Marketing Practitioner”.

“I’ll have one large community, please”
Communities come in different sizes. While everyone strives to build a space with a massive, always active user base, the reality sometimes shows differently. In fact, only 4% of the Developer Program Leaders reported running an active community that counts more than 10M members. 27% responded to running communities smaller than 100 members.

The less people are in a community, the more effort is needed to keep the discussion going. Which begs the question: how can you engage the community members?

Driving participation in the community
To answer this question, we don’t look at what community managers are doing to increase engagement in their communities. We ask developers what makes a community fun for them.

33% of developers (sample size 10,478) responded that having a well-designed community platform is their #1 reason that encourages them to participate. Four more reasons are tied for the second place, with 29% of respondents saying that what encourages them to be active are:

Getting regular updates
Fun activities
A well-defined purpose for the community
Projects on which community members can work together.

The latter one is especially important for students.

Here is the full breakdown of their responses:

Developer community + DevRel strategy wrap up
In summary, looking at the latest data from our Developer Nation survey (developer-focused) and the Developer Program Leaders survey (DevRel-focused) we reach the following conclusions which we discussed in this hopefully-not-that-long article:

Developers rank community at their top-5 resources
Developers’ #1 reason for joining communities is training and resources
A community can be the means to address student developers’ top aspirations
Community is considered a key part of a developer-facing strategy by more than ⅔ of developer program leaders
Community management is the second most popular title
Communities come in all shapes, but even more sizes
Developers share what makes them engage in a community and are happy to share it. How are you addressing your developer community? Join the discussions with like minded people at the DevRelX community.

If you want more data on developer needs and wants or you are trying to better understand developers, SlashData has the insights you need.

This post was originally published on SlashData

How Education Helps Developers Reach Purchasing Decisions and Product Adoption

SlashData Team — Mon, 12 Dec 2022 09:45:20 +0000

One of the trends that we’ve seen in recent years, is not only the continuing growth of the developer population but also an increase in their decision-making power and influence in purchasing decisions.

For this reason, software companies can no longer focus their efforts on attracting the attention of the C-suite and educating them about their product. They need to work out how to reach developers. Spoiler alert: the same marketing tactics don’t work on the developer population.

With this in mind, Nate Aune, CEO of Appsembler recently led a session at the DevRelX Summit 2022 with Konstantinos Korakitis, Director of Research at SlashData, on how education helps developers reach purchasing decisions and product adoption. Yes, that’s right. The critical marketing tactic you need to focus on is not marketing, it’s education.

If you missed the session, or if you need a reminder of the important points we discussed, we’ve summarised the key takeaways below. The data we cite below is from SlashData’s latest Developer Nation survey. The State of the Developer Nation report is available to everyone and shares insights and trends on what matters most to developers.

More Developers Are Decision Makers Than Ever Before
While not all developers make the final tool buying decisions (many do), many influence purchase decisions and that number continues to grow. 41% of developers influence purchase decisions while 26% are decision makers. But who are these developers?

Developers are influencers and decision makers in companies of all sizes, particularly so in medium-sized businesses of 51 to 1,000 employees. In medium-sized businesses, 59% of developers influence purchase decisions (compared to 51% in large enterprises and 49% in small businesses) while 41% are decision makers (compared to 28% in large enterprises and 32% in small businesses).

One of the reasons behind this is that developers are likely to have a say in product and tooling decisions in these companies. In large enterprises, where we see the smallest proportion of decision makers, there is a sense that software purchasing decisions are made higher up in the hierarchy, or by centralised purchase departments.

Experience Levels Affect Level of Influence
The level of experience in software development is one of the strongest predictors of the amount of influence that developers have on tool purchasing decisions. Those developers holding leadership positions have the highest level of influence on decision making.

This isn’t surprising as these developers have accumulated expertise and knowledge over the years, meaning that their opinion matters. It's also due to the nature of their roles and the responsibilities that they gain as they progress in their careers.

Developers with highly technical roles also exert a lot of influence over purchasing decisions. More than half of technical specialists affect or influence buyers or make the final decision when it comes to choosing tools. For example, the vast majority of DevOps engineers are involved in the tool purchasing decision process. Similarly, more than three-quarters of architects, system administrators, and hardware engineers have some form of decision-making power.

This is likely linked to the nature of the specialised nature of development tools they use and the experience they have. For example, nearly 80% of architects have six or more years of experience in software development compared to only 54% of frontline coders.

Developers Expect You to Offer Educational Resources
Understanding what these developers expect from vendors is important because these expectations are likely to affect their decisions. SlashData's research has consistently found that three features come out top of developers’ wishlists and expectations from tool vendors. These are:

Documentation and sample code
Tutorials and how-to videos
Development tools, integrations, and libraries

These resources should be the starting point for every developer marketing program. Alongside these core resources, more than a quarter of developers say that tool vendors should offer technical support, training courses, and hands-on labs. In total, 40% of developers expect software companies to offer educational resources, including training courses and interactive learning environments. Investing in high-quality training resources is time and money well spent for developer program managers.

Developer Education is Crucial to Getting in Front of Decision Makers
Developer buy-in is becoming critically important for companies that are selling software to developers. More than a third of sales opportunities are lost because the seller failed to get developer buy-in.

This is happening because developers are evaluating the product early in the sales cycle and the buyer is getting involved at a much later stage. Software purchasing is happening from the bottom up. Developers are getting an API key, downloading an SDK, and playing around with the software; they only bring in the decision maker after they have checked that the solution is right for them.

If you're a software company and you're not onboarding developers quickly and helping them get to that aha moment, then they probably won’t ever introduce the buyer to your solution. That’s why it’s critical to think about how to onboard, to educate, and get developers up to speed quickly and easily.

Hands-On, Interactive, and Frictionless Training Environments are Key
Developers want to dig in and understand how your software works rather than watching someone explain it or read a brochure. Developers also want to get their hands on the software as soon as possible. They don't want to have to talk to sales or jump through hoops to access your product or have to spend a long time installing software on their computer and dealing with compatibility issues.

The faster you can give a developer access to your product, the better, and the quicker they will get to the stage where they recommend it to decision makers.

Create an Ongoing Developer Education Program
What are successful developer marketers doing to convert developers into paying customers? We know that developer-oriented software requires more education and training before a developer recommends the product. That means you need to help the developer move through the journey with relevant resources and content to ensure they don’t fall out of the funnel.

Think of education resources as stepping stones. The goal is to get the developer hooked on your product and to reach that aha moment. A developer might start with low-commitment resources, such as a five-minute teaser video that explains what the product is, who it's for, and what problems it solves. Then they might watch a 15-minute tutorial before digging into the documentation.

Next, they’ll take a self-paced course or live workshop that helps them to build sample apps or try out an integration. The culmination could be a multi-day proof of concept where they can try things out in a sandbox environment. It’s only at this point that they will bring in the decision maker.

All of these steps are designed to help the developer get familiar with the product at their own pace and to help them validate that the solution is going to work for them. You need to create a compelling and unified learning journey that you can track and see where the issues and blockers are and where you can make improvements.

Developer Education in Action

To bring it all together, we talked about software companies that are already using developer education to boost product adoption. Here are some examples to get inspiration from.

Chef Software

Chef Software, a DevOps automation tools company, wanted to be able to introduce developers not only to Chef products but also to the foundational skills that developers would need to be successful with Chef. They created the Learn Chef site, which provides these courses and also offers the ability to spin up sandbox environments. Within seconds, users can start using Chef software and learn how it saves time and solves their problems. It’s also a way to grow their audience and onboard and train new customers.

The Learn Chef site also acts as a marketing engine to draw developers in who may not even know about or be interested in Chef. Chef tracks user activity such as who is taking courses, what stage they are at, and what courses are they enrolling in, in Marketo. They use this data to send personalised emails to developers according to where they are in their learning journey. These nudge emails keep developers engaged and remind them that they enrolled in a course.

Chef can make personalised recommendations, such as enrolling in advanced courses once they have completed initial courses. The sales team can gauge buying intent and marketing can improve messaging, as they know which products to highlight.

Redis
Millions of people were downloading real-time data platform Redis, but they had no idea who they were. To solve this problem, they created the Redis University where, in exchange for getting free courses on databases and related technology, developers needed to register and provide an email address.

Redis found that the people who went through these six-week courses were highly qualified leads as they had spent so much time engaging with the company and product. Between 15 and 20% of people who took the online courses ended up becoming Redis customers.

Check out the 40-minute session recording to get the full story.

The importance of documentation in the DevRel space

SlashData Team — Wed, 07 Dec 2022 11:21:36 +0000

Technical writing is an important building block within any community, especially when advocating for a product. Documentation is the first direct contact you have with developers and users interested in getting to know and using the product.

The better the writing the better the odds of them coming back and getting involved with the community. But, what exactly is technical writing?

Technical writing is designed to make hard concepts as easy as possible for the readers. It’s more common than you think, whenever you read a user guide, a tutorial, case studies and many others are common examples of technical writing in the field. It is designed to explain specialised information to those that are not familiar with it and help those that are deepening their knowledge.

It’s important to notice that technical writing and documentation have their differences but keep in mind good documentation practices can help enrich your technical writing. Developer documentation is essential for technically communicating with users, now knowing how important it is, we can identify some common mistakes and we can avoid them when making our documentation.

Common mistakes

Assuming the reader has the same technical knowledge as you: By thinking this way you are limiting the number of users and developers that are going to interact with your product. This is why it is important to know your audience. You should always explain based on the different levels of background education your readers will have, not the ones you possess.
Not disclosing acronyms: You should always write in the text the meaning of the acronym before actively using it in your documentation enclosed in parenthesis. This is heavily tied to the previous point, don’t assume the reader has the same technical knowledge as the writer.
Using passive voice: This leads to less clarity and ambiguity. Using an active voice will urge the reader to take action and understand the document they are reading more clearly because it keeps sentences from becoming too wordy.
Skip minor steps: By skipping minor steps that the writer thinks are a given, the reader will be lost and won’t know what to do. Do not skip steps when the goal is to make the user complete a task or understand a concept.

What makes documentation good?

Good documentation is meant to explain to your audience heavy concepts in an easy way. It is a lightweight task with no direct flow of income but it's necessary. This is why documentation is often overlooked, but in the long run, the benefits are palpable. It helps not only instruct your user but to document the development process.

Here are some ways you can improve your documentation:

Write in simple terms: There is no need to use extremely technical terms when writing. The safe option is to write simply about what to do and a quick overview of the why. Think of a way to deliver the content in a way that’s easy for readers to understand whether or not they have prior experience with the product.
Have a style guide: It can help create a consistent voice within the company, the reader will respond to a standardized form of content, terminology and visuals. There is no need to start from zero, there are many documentations that can serve as a guide.
Get community feedback: This way you can get immediate feedback from the community on the guides that are working and those that are confusing.
Track changes: Have a version control that will help you track changes over time, in case a new feature is later removed because of the user’s reaction, you can revert back to the previous documentation.
Think about the users reading your documentation: Is your documentation accessible? Is it easy to follow? Can they easily find what they were looking for?. Help users have a frictionless interaction with your documentation.
Inclusivity and Accessibility: Avoid idioms to help cater to your international audience, consider people using screen readers, make sure you have a good contrast ratio in the design, and if you make use of screenshots make sure they have text.

Which audience should you focus on?

Depending on the type of audience your goal is you should adapt your writing to fit the audience's needs. We can identify two different target audiences with their different needs that need to be fulfilled, developers and users.

Developers

Developers play an active role when reading documentation, having clear guides in place will make them want to contribute and help with the product, making the code, documentation and community better. They have a way more different approach on documentation than users do, so let’s see what types of documentation they focus on:

Types:

API documentation: It serves as a reference on everything regarding API calls.
Read Me’s: It is meant to be an overview of the product, usually with the source code.
System documentation: The goal is to describe the product, technical design documents, software requirements and more.
Release notes: It shows information about releases, bug fixes or the latest version.

Users

They can play both an active and passive role when reading the documentation. They want to use your product, and an active voice should be used when talking to them. Some ways of targeting the users are writing easy-to-follow guides and adding code snippets and external sources when needed to expand the information. Some of the types of documentation they focus more on are:

Types:

How-to guides: It takes the user through a step-by-step detailed process to help them reach a goal. It is problem-oriented. It helps the user complete a task.
Tutorials: The goal is to leave the user with knowledge of a concept or process. It’s meant to provide a successful learning experience.
Explanations: They’re written to help users clarify certain topics that users might not have knowledge on.
Reference docs: Are made to share with the user more technical descriptions of the product.

Closing thoughts

Documentation is changing the way developers and users interact with products, good documentation motivates people to be active within the community, and it creates loyalty to the product and a sense of unity.

This is why documentation shouldn’t be an afterthought, good documentation can make or break your product and community.

Thank you so much for reading!

Make sure to connect with me on Twitter and check out more articles on my blog.

State of the Developer Nation 23rd edition: the fall of web frameworks, coding languages, blockchain, and more!

SlashData Team — Fri, 25 Nov 2022 09:25:00 +0000

It’s the most wonderful time of the year! Yes, the beginning of the “Merry” season but also the time when new insights from the world of developers come to everyone’s house (magic may or may not be involved)!

Stay up to date with the 23rd edition of the State of the Developer Nation report and get the insights you would only pick up by slashing through data with your own two hands.

Our 23rd Developer Nation global survey reached more than 26,000 developers in 160+ countries and its findings are bundled in a free “State of the Developer Nation” report.

This research report delves into key developer trends for Q3 2022:

The state of blockchain development
Students’ top career aspirations
Language communities – An update
Why developers contribute to vendor-owned open-source projects
Types of studios game developers work for
The rise and fall of web frameworks

In addition to outlining the report’s major findings, here are a few key takeaway points to spark your curiosity:

The state of blockchain development

25% of developers are currently working on or learning about blockchain applications other than cryptocurrencies.
Developers with 6-10 years of experience in software development are the most likely to be working on blockchain projects.
Though Ethereum is the dominant blockchain platform, it is the only one more popular among learners than those currently working on blockchain applications.

Language communities – An update

Javascript remains the largest programming language community, with an estimated 19.6M developers worldwide using it.
In the last two years, Java has almost doubled the size of its community, from 8.3M to 16.5M. For perspective, the global developer population grew about half as fast over the same period.
Kotlin and Rust are the two fastest-growing language communities, having more than doubled in size in the past two years.

The rise and fall of web frameworks

Web developers who use frameworks are more likely to be high-performers in software delivery than those who don’t.
Web developers are gradually settling for a smaller number of frameworks as they stop experimenting with a wide range of tools.
React is currently the most widely used client-side framework and its adoption has remained stable over the past two years. By comparison, jQuery’s popularity is decreasing rapidly.

As you’ll notice, most of the trends we discuss in this report are takeaways from how developers use technology. Our goal is to share these insights with the world to help guide the next generation of development.

You can download the full report for free and access all data and insights within.

If you need additional information or looking to understand developer preferences’, please get in touch with us and we will dive into it together.

Using SlashData custom questions to understand AI software developers

SlashData Team — Fri, 11 Nov 2022 16:24:03 +0000

Our mission is to help our clients understand what the market looks like, what developers need, what excites developers, what doesn’t, and what they expect from our clients’ (and their competitors’) products and the developer programs that go along with them. So, when we are approached with a request for some custom work, we roll up our sleeves and dive deep into the data.

In this case study, we will be looking at how one of our clients, worked with us to understand the needs and preferences of software developers working with AI.

The client is a company among the top 50 in the 2022 Fortune 500 ranking, which for the purposes of this case study we will be calling “Client”. This is the third installment in our “how we work with clients” series, and you can read part 2 and part 1 with Okta for more details.

In this article, we will look into their request and more specifically:

The questions our Client wanted to answer
How we worked together on their problem
How they used the insights we offered them

The request

Understanding the needs of AI software developers

The Client wanted to better understand the needs of AI software developers, so we worked with them closely to understand the problem they were trying to solve.
Then, together we made sure that we added custom questions to our Developer Nation survey, to get the answers from developers.

Question: What was the goal/challenge you were looking to accomplish?

Client: We wanted to get feedback from our customers, who are software developers that work on AI, so we could get a better understanding of their needs:

What they’re actually doing
The specific points that we are trying to optimize.
We wanted to answer high-level questions such as what language they are using and high-level computing preferences. This is why we decided we want to have this survey.

Q: Why did you choose SlashData?

At Client, we have had the experience of working with SlashData. And we did get a high value out of the previous report that you did for us. I was impressed by the support that I got when I needed it, the responsiveness, how you were always on schedule. The real part of working together. I felt how you put the customer at the front, the priority. All of these were very important to us. This is why we chose to work with you again on this project.

Working together

I really got the feeling that you’re trying to understand real problems

Q: What did you like about the process of working with SlashData?

I really liked the execution: the ability to execute fast and answer our questions. We worked very well, very collaborative. Truth is, we did have a slow start. But then you said

“let’s do this: you will write your assumptions, we will ask questions and approach this project this way”.

Once we started that, work was progressing in a much better way. It was hard at the beginning, but I got excellent support. You had excellent questions, I really got the feeling that you’re trying to understand real problems.

“What is it that we are trying to solve?”.

You also asked questions to learn more about what we are doing, which I found very professional.

Q: What are the things you found challenging when working with SlashData?

We said that we would be adding X custom questions to your survey. But from our side, we tried to add more and more and we were left with all those very complex questions.

Very complex questions are tougher to answer when you are looking to gain something specific. You did tell us to get the simple questions answered. This is what comes to mind in retrospect: Don’t make the questions too complex, trying to squeeze in more. You will get more value out of the simple questions, not the very complex ones.

Deciding using the data

I used a significant part of those questions to presentations I gave to our senior executives.

Q: How did this project/report/data solve your problem/challenge overall? Did you understand the developers’ problems more based on the report?

I used a significant part of those questions to presentations I gave to our senior executives. I was especially more confident to use the less complex questions we asked.
If I had my current experience in the beginning, I would have managed to secure a higher budget to ask more, simpler questions.

data that show what our customers think and therefore, we could work with more than just our own thoughts and assumptions

Q: What decisions did you make using the data/research?

The work we did together was part of a huge project that Client is working on. I’m afraid I can’t disclose exactly the steps we did take after going through the analysis you gave us. What I can tell you is that senior management really liked the fact that we spoke to our customers and asked them directly. And not only that, but we also brought data that show what our customers think and therefore, we could work with more than just our own thoughts and assumptions. Client is planning for some huge products and of course there are a lot of parameters and a lot of things being done. But this data helped us pick a direction.

How would you describe the service quality?

The service was excellent, really.

This interview is part 3 of the “How we work with our clients” series. The product this client worked with was custom questions and analysis and a custom report, to target their specific needs.
You can also see how Okta managed to reach the top 3 in developer satisfaction using our Developer Program Benchmarking and how another client used our Deep Dives to boost their Developer Experience.

Working on a new initiative or want to make sure your product will win developers’ hearts? Talk to us.