Executive Summary
AI builders were shipping the future in public
A data portrait of AI-aided software builder communities on Reddit, based on 261,511 posts across 15 subreddits from December 2022 through mid-May 2026.
This report examines how builder culture and interest in building software products, services, and solutions increased as AI technologies became more powerful and grew in utilization, including by people with limited technical backgrounds.
This research is designed to improve understanding of how AI builder communities on Reddit have evolved since the launch of ChatGPT, where builder attention has concentrated, how early builder discussion compares with mainstream public interest, and what blind spots appear when posts are analyzed over time.
To develop the report, 261,511 Reddit posts were analyzed across seven core builder communities and eight broader AI-influenced communities. Topic modeling and phrase analysis were used to surface recurring themes. Google Trends data was also used to compare Reddit posts with mainstream public search behavior.
The study found that builder culture accelerated sharply as AI coding and productivity tools improved. Builders were actively using AI to ship products, launch side projects, build automations, test agents, seek feedback, and create new services in public.
Several findings stand out.
- Builder Reddit often identified important AI concepts before they reached mainstream search interest. AI agents, agentic AI, and MCP appeared in builder posts months, and in some cases years, before comparable Google Trends search interest crossed the study threshold.
- Builder-focused language spread beyond explicitly builder-centered communities. Concepts connected to shipping, agents, workflows, product development, and vibe/ship culture became more visible in broader AI-influenced Reddit communities over time.
- Public AI interest and Reddit AI discussion overlap, but they reflect different mindsets. Public search is more focused on access, cost, discovery, and brands. Builder discussion is more focused on implementation, workflows, product development, and launch activity.
- Security is not one of the highest-mindshare builder topics, but security-related discussion is rising. When builders talk about security, they tend to use practical, operational language: API keys, environment variables, authentication, rate limits, encryption, cost exposure, and systems that can fail in production.
- AI builders are moving from experimentation to dependence. As AI-generated and AI-assisted systems become more central to real products and workflows, questions about reliability, safety, cost, security, and long-term product viability become harder to ignore.
This research provides a data portrait of a fast-changing ecosystem: people using AI to build, learn and launch faster, all in public.
AI agents, agentic AI, and MCP appeared in builder Reddit posts before comparable mainstream Google Trends search interest.
Builder security posts center on concrete production risks: API keys, authentication, rate limits, encryption, privacy, cost exposure, and systems that can fail after launch.
Data based on analysis of 261,511 Reddit posts published between December 2022 and mid-May 2026. Fifteen communities were analyzed: seven core builder communities and eight broader AI-influenced communities. Frequent post themes were surfaced through topic modeling and phrase analysis; selected findings were compared with Google Trends search behavior.
Forward
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Reddit
Why Shipping the Future?
I’ve had the privilege of living through several different periods of significant technological change.
One of them was the advent of social media and blogging.
Back in 2006, blogging was just coming into the mainstream. That year, Huffington Post and BuzzFeed launched, and a novel concept began to spread: the idea that regular people, non-experts, could capture eyeballs and gain influence by posting … whatever they wanted.
This was significant because traditionally, experts, such as academics and journalists, were the ultimate authority figures. They controlled what people learned about and had an outsized impact on public opinion. Now, they were being challenged.
I learned first-hand about the influence bloggers were gaining. I launched my own healthcare blog in February 2006 and quickly gained an audience. And, I received lots of questions: were patients sharing stories and advice on blogs spreading misinformation? Were they taking the place of experts? Could they be trusted?
I’ve always been the curious type, so I decided to conduct research to answer these questions. In April 2006, I released The Emerging Healthcare Blogosphere: What Is It & Why Does It Matter?, a 110-page report.
I’m sharing this story because the present moment feels very familiar. Once again, a new technology (in this case AI) has emerged that is upending established norms and power structures. People are grappling with what AI means and what the new world will look like.
One of the most significant changes that AI has driven is the democratization of technical ability. Only a few short years ago, creating a SaaS product or even launching a website required hiring a coder or having technical ability. Now, people can prompt an AI and build a working application in a few hours.
People have questions, lots of questions. Do we need software engineers, designers or marketers? Can AI help one person do the work of 100? The answers to these questions are still being discovered. And, I’m helping to write this story as someone who is actively using AI tools.
But I also know that other questions can be answered by doing a little bit of what my friend Susannah Fox, former Chief Technology Officer of the U.S. Department of Health and Human Services, calls Internet Geology. She defines it as: “paying close attention to the present [to] catch trends as they are developing” by collecting and analyzing online data.
It’s been about three-and-a-half years since the launch of ChatGPT. What can we learn about the people using AI-aided coding, marketing, writing and design tools to ship the future? What are they concerned about? What are they ignoring? How is this community of builders maturing?
Shipping the Future is my effort to answer some of these questions. It’s a first-of-its-kind study of more than 260,000 popular Reddit posts written by AI enthusiasts, builders and dreamers since December 2022.
The first chapter of the new age of AI is being written. Now is the perfect time to look back, reflect and use what we learn to anticipate the future.
Introduction
December 2022. r/ChatGPT was barely a month old. One user posted: “I cannot live without ChatGPT … self-learning programming is such a struggle … now I have a loyal bot who will spit out mostly accurate answers.” The upvotes poured in. That same month, on r/artificial, another Redditor shared how ChatGPT helped them generate Unity code for procedural terrain.
What makes these conversations interesting is that only a few weeks prior, ChatGPT had burst onto the scene. Many were using ChatGPT to have wide-ranging conversations or write essays. Few were thinking about how to use this technology to gain vital skills or help build.
But Redditors were.
Over the years, Reddit has become a vital community for people using AI to build personal tools, applications, products and services. And, in subreddits like r/buildinpublic, r/SideProject, r/SaaS, r/AI_Agents, r/automation, r/startups, and r/Entrepreneur, Redditors are sharing their experiments, failures, first attempts and successes.
Reddit is also a place where important AI topics are discussed first. For example, Redditors were talking about AI agents in 2023, years before the term went mainstream.
All this makes Reddit a vital source of information about where AI is going next and how the AI builder community is maturing. It can help improve understanding of:
- How AI is accelerating builders with little to no technical background
- What AI tools are being implemented across use cases
- AI’s recent history and how builder culture has embraced AI as a source of knowledge, technical resource and change agent
- Blind spots revealed by examining what builders on Reddit aren’t talking about
This report provides a data portrait of the AI builder ecosystem on Reddit from late 2022 through mid-2026.
It covers:
- How conversation about building with AI intensified across tracked subreddits—and where attention clustered
- Where Redditors anticipated AI developments before they hit mainstream awareness
- How segments of the AI builder community are shifting from shipping to survival
- The ways the ecosystem is maturing in the face of new threats
What this study measures
261,511 posts across 15 subreddits from December 2022 through mid-May 2026 were analyzed. Frequent discussion themes were surfaced via topic analysis: shipping, side projects, automation, startups, and AI tool threads.
This study examines how builder culture and interest in building software products, services and solutions increased as AI technologies became more powerful and grew in utilization, including by people with limited technical backgrounds.
Builder Culture Interest Index
To help track how builder culture changed and expanded as AI capabilities increased, the Builder Culture Interest Index was developed. It measures how much attention builder-related topics were receiving across subreddits over time across seven core builder communities: r/buildinpublic, r/SideProject, r/SaaS, r/startups, r/Entrepreneur, r/automation, and r/AI_Agents.
The Index provides a view into how builder culture accelerated on Reddit as AI, especially coding tools, improved in power and scope.
How these topics were identified
For this study, 261,511 posts published on 15 subreddits between December 2022 and mid-May 2026 were analyzed. Using topic modeling, seven conversation clusters were identified. These capture how builders discuss topics like shipping products, using AI-powered pipelines, generating revenue from products, technical implementation and other subjects.
The table below summarizes each topic. For full details on data collection, subreddit selection, and analysis methods, see the Methodology section.
| Topic | What it captures | Example phrases |
|---|---|---|
| Build & Launch Culture | Shipping products, seeking feedback, public accountability | build in public, product hunt, honest feedback |
| Automation & Workflows | AI-powered pipelines, tool orchestration, reducing manual work | workflow, automation, tool use |
| Solo & Side Projects | Independent builders, weekend projects, bootstrapped launches | solo founder, side project, just shipped |
| Monetization & Growth | Revenue strategies, user acquisition, scaling businesses | revenue, traffic, monetize |
| Coding & Dev | Technical implementation, debugging, open-source contributions | python, debug, open source |
| Ops, Cost & Scale | Infrastructure constraints, API limits, cost management | rate limit, billing, hit a wall |
| AI Reliability & Limits | Model failures, hallucinations, trust and safety concerns | hallucination, model limits, reliability |
From ChatGPT to Agentic Workflows: How AI Improvements Sparked Builder Culture
ChatGPT Launch
On November 30, 2022, OpenAI released ChatGPT, a research preview powered by the GPT 3.5 language model. Although ChatGPT was initially meant to mainly be a conversational agent, people quickly began using it for a range of other purposes, including writing poetry.
ChatGPT wasn’t the first large language model, but it was the first one to be widely used. ChatGPT had an immediate cultural impact, becoming the fastest-growing app in the history of the Web. By March 2023, it was being used by more than 100 million people.
Shortly after ChatGPT’s launch, people began to see the potential for building products and services using GPT models and started to explore OpenAI’s API. Initially, interest in the API, which had been launched March 2022, was limited. But this changed after ChatGPT’s outsized success.
ChatGPT’s emergence was also an important moment on Reddit. The r/ChatGPT subreddit was founded on December 1, 2022, days after ChatGPT’s release. And, across Reddit, people quickly began to post about their experiences building tools with ChatGPT’s assistance.
The Builder Culture Interest Index was 11 as of December 2022 (0–100, relative to the study peak).
AutoGPT Released
As 2023 progressed, OpenAI continued to improve ChatGPT’s capabilities. On March 14, 2023, GPT-4 was launched and made available to developers via the API.
Another milestone was the release of AutoGPT on March 30, 2023. AutoGPT is an open-source application that demonstrated the potential for GPT models to be used to complete tasks. When given a prompt, LLMs would develop a plan, write needed code, and execute until the task was achieved.
AutoGPT was an immediate hit. Builders started using it to create agents that could develop software or draft content. Despite its promise, AutoGPT had many limitations, including high API fees and a tendency to hallucinate. AutoGPT’s true impact wasn’t in the number of applications it helped users develop. Instead, it demonstrated that LLMs could guide themselves toward completing difficult tasks and, with the right support scaffolding, succeed at them.
Between December 2022 and March 2023, when GPT-4 and AutoGPT launched, the Builder Culture Interest Index rose from 11 to 17. Builder-community engagement in those subreddits was climbing.
OpenAI Function Calling
OpenAI introduced function calling in June 2023. The innovation was important because before this it could be cumbersome to integrate functionality like document search into LLM-aided workflows.
For example, to activate a certain response, one strategy might be to scan incoming text for a specific word or phrase that would trigger an action. Another approach would be to use prompt engineering to encourage the agent to engage in a specific task. Both of these strategies have drawbacks.
In contrast, function calling allows developers to turn functions into tools for LLMs. Tools make LLMs much more predictable and controllable. One use case is providing LLMs with knowledge beyond their training set from document databases or the Web. When an agent is asked a question it does not have the answer for, it can call a tool to get further information, making their responses more reliable and less prone to hallucination.
Between March and June 2023, the index climbed from 17 to 21.
Release: Claude 3.5 Sonnet
Anthropic released Claude 3.5 Sonnet on June 21, 2024. On coding benchmarks it outperformed or matched every available model. Benchmarks are fine, but they can be a poor measure of how models perform in the real world. Claude 3.5 achieved the difficult task of satisfying the demanding developer community. Claude 3.5 Sonnet was widely cited as the first model able to produce higher quality code reliably.
This is distinct from incremental quality improvements. When reliability improves, the coding workflow shifts. For some, Claude 3.5 Sonnet felt like a trusted coding partner.
Claude 3.5 Sonnet also made reliable AI-assisted development broadly accessible for the first time. Early adopters and some teams had been using AI coding assistants for years. Claude 3.5 Sonnet lowered the barrier to entry for everyone, from individual coders to users with limited technical knowledge and proficiency.
Release: DeepSeek-R1
DeepSeek, a Chinese AI lab, released DeepSeek-R1 on January 20, 2025. DeepSeek is an ‘open weight’ model meaning its parameters are public. What was surprising about DeepSeek is that it matched or exceeded leading frontier models on key benchmarks while costing $6 million to train.
DeepSeek’s release caused significant turbulence in financial markets and ignited public debate about the assumptions underlying AI infrastructure investment to date. Specifically, that large investments would be required to train models that could operate at a high standard.
Cost is not a minor variable in builder decisions. Cheaper models that deliver comparable performance to more expensive options provide greater optionality. Complex products and services become more viable to produce. Pipelines and agentic systems that were once not economically possible are feasible.
DeepSeek-R1 unlocked the economics of multi-step automation for solo builders. Workflows that called a capable model repeatedly across complex tasks—checking conditions, generating outputs, routing decisions—had previously carried meaningful per-task costs. With DeepSeek-class pricing, those costs collapsed. A solo builder with a modest budget could now run AI-powered automation that previously required significant spending.
During this, and previous milestones, the Builder Culture Interest Index continued to increase steadily. DeepSeek’s release would add to the growing momentum behind builders experimenting with and discussing AI tools.
Vibe Coding Coined
On February 2, 2025, shortly after DeepSeek-R1’s release, Andrej Karpathy, a founding member of OpenAI (now at Anthropic), posted on X describing a mode of working he called “vibe coding.” He said: “fully give in to the vibes, embrace exponentials, and forget that the code even exists”. The term shortly went viral in developer and builder communities.
The naming of a practice can be a cultural milestone. Once “vibe coding” was defined, builders who felt they were doing something wrong by shipping code they didn’t fully understand, or developing products with components they couldn’t explain, felt vindicated.
The message: You don’t need to be a “real programmer” to build software. All that’s required is a capable model.
Founders without engineering backgrounds, domain experts building vertical tools, and marketers automating their own workflows, were already a part of builder communities. However, they often operated at the margins.
Vibe coding gave them permission to claim the builder identity, post publicly about projects that previously felt too “hacked together” to share, and start thinking seriously about launching revenue-generating products.
The two milestones of January and February 2025, economic (DeepSeek) and cultural (vibe coding), were two important catalysts that helped to further accelerate the growth of builder communities on Reddit and beyond.
Launch: Claude Code
Anthropic made Claude Code available to the public on May 22, 2025. Unlike earlier AI coding tools that functioned as enhanced autocomplete or chat-based code suggestions, Claude Code is an agentic coding system. Given a task, it can navigate a codebase autonomously, read files to understand context, edit code across multiple files, run terminal commands, interpret error output, and iterate until the task is complete.
A combination of an improved model, greater tool calling capabilities, and a sophisticated harness (software that helps guide the model on tasks) helps Claude Code operate more like a junior developer than an LLM responding to single prompts.
Agentic coding tools change the unit of work. With Claude Code, a builder can specify a feature or a bug fix and receive a completed set of functions, or even a fully developed application. The cognitive mode shifts from “write code with AI assistance” to “delegate a coding task and review the result.”
Claude Code facilitates larger projects and faster iteration cycles. Because Claude Code can hold codebase-wide context, solo builders can rely on it to create ever more sophisticated systems. Faster iteration cycles are possible because the agentic loop—write code, run it, observe errors, adjust—can be delegated across multiple agents simultaneously.
Claude Code arrived at a moment when the vibe coding identity had already expanded the population of builders willing to use AI for implementation. Now these AI-aided builders had access to a more capable tool able to fulfill their ambitions.
Launch: Claude Opus 4.5
Anthropic released Claude Opus 4.5 in November 2025 as a frontier-class model that was among the most capable available at the time of release. While other models had impressed across a range of benchmarks, to many builders, Claude Opus felt different, more responsive and better able to handle complex coding assignments.
People reported that they trusted Opus to develop more complex code, could let it run longer to develop applications end-to-end and more. It was clear that a new milestone had been reached. The ceiling on what one person could attempt with AI had risen significantly.
Products that had once required robust technical development, expertise and resources became feasible solo projects.
The Builder Culture Interest Index rose by 173 percent between the release of DeepSeek-R1 and Claude Opus 4.5, illustrating just how much builder activity on Reddit had expanded as AI coding agent capabilities continued to improve.
The Rising Security Gap
Alongside the Builder Culture Interest Index, this study separately tracked post content related to AI reliability and limits. Post volume about hallucinations, model limitations, and occasional security-related issues such as prompt injection rose in absolute terms, but remained roughly 0.3% of total builder post volume.
This does not mean builders on Reddit are ignoring security. It’s just that content about shipping, agents, tooling, launches and revenue attract significant attention. Posts about the dangers of prompt injection are much less likely to be published.
The gap matters because AI coding tools give builders significant technical firepower and expose them to a lot of risk. Consider Moltbook, a vibe coded social network for AI agents. It was launched with a serious vulnerability: a database misconfiguration that exposed users’ API keys. The AI that helped build the product did not flag it and the builder did not catch it before launch.
Agents add another layer of danger. Builders report agents leaking secrets, deleting production databases, and running destructive commands without adequate guardrails. The tools that make solo shipping possible can also make catastrophic mistakes more likely.
The AI-aided builder ecosystem is starting to mature. More products are attracting real users. Awareness of security problems in AI-generated code is growing, and certain segments of the builder community are starting to pay very close attention.
Peak interest
As of mid-May 2026, builder interest in using AI to build products, services and solutions had reached its peak. New applications were being launched daily, Redditors actively discussed the pros and cons of different models, and were working to optimize their workflows to get more outputs at a cheaper cost.
This interest has also led to another milestone: AI agents are increasingly being used to engage on Reddit—especially in builder communities. This has not only increased the amount of posts and comments on Reddit, but is raising serious concerns about whether Reddit will remain a place for human-to-human discourse, advice seeking and engagement across builder communities and beyond.
Transitions: Tracing How Builders Think
Baseline: ChatGPT Launch (2022-Q4)
To understand how builder culture shifted since ChatGPT's launch, tracking what builders were actually thinking about at key points in time is critical. This goes beyond looking at what topics were trending, but understanding what themes were consistently showing up in conversations, which provides a deeper view of community concerns and preoccupations.
The approach: topic modeling. Using a technique called LDA (Latent Dirichlet Allocation), posts were analyzed from core builder and broader AI/tech communities. on Reddit. The model surfaced recurring themes from the text itself, producing 25 topic clusters. From those, seven emerged that were builder-centric, themes like shipping culture, monetization, automation, and coding. Those were grouped into the seven categories shown here.
This analysis method was selected to reduce potential bias. Because topic clusters were not defined in advance, the data can reveal what builders were actually thinking about across the study period.
The chart shows the result at Q4 2022, shortly after ChatGPT launched, as the baseline.
At that point, builder conversations were split fairly evenly across the top themes. Monetization & Growth and Build & Launch Culture each claimed about 7% of the conversation. Builders were focused on the fundamentals: How do you build something, and how do you make money from it?
Automation & Workflows was already present at 4.7%. That’s notable. Builders were thinking about how to reduce manual steps and scale output. The seed of what would later become a dominant conversation topic was already present.
AI Reliability & Limits is at just 1.2%. Builders were excited. The risks of depending on models that hallucinate, fail unpredictably, or break workflows was not top of mind.
These seven themes accounted for 29.8% of all sampled builder posts in Q4 2022.
A Focus on Coding and Workflow Optimization (2024-Q4)
Between Q4 2022 and Q4 2024, builder communities on Reddit grew dramatically and post content topics shifted.
In the two years following ChatGPT’s launch, Automation & Workflows saw the largest increase. The context around this shift in topic focus is important. By late 2024, tools like LangChain, AutoGPT and OpenAI’s function calling framework had increased builders’ ability to expand LLM’s capabilities with smart tooling.
While not every post in this category was artificial intelligence-focused, AI was a major theme. Builders were starting to ask questions about how AI could successfully be integrated into workflows, along with other commonly-used frameworks and systems.
Coding & development-related topics continued to capture post volume share. During this period, people were using ‘tab-complete’ to have functions and methods auto-generated while coding. Another strategy was ‘copy and paste’ AI-aided coding. Builders were pasting code into ChatGPT to ask questions or receive solutions to specific problems and then integrating this code into their codebases.
Meanwhile, the topics that had dominated at baseline, Monetization & Growth and Build & Launch Culture, held their share or declined slightly. Builders still cared about growing and generating revenue, but were more heavily focused on workflow and development-related topics.
Despite the growth in other categories conversations about AI Reliability & Limits remained largely flat. Issues like hallucination and infinite LLM task loops were known failure modes, but captured lower mind share.
Peak Interest and Builder Culture Breakout (2026-Q1)
By mid-May 2026, the builder community on Reddit had grown substantially and their areas of focus had shifted once again.
Automation & Workflows had climbed to become one of the common themes in builder conversations. By this point, AI is dominating discussions about how to build reliable, scalable workflows using agentic AI systems.
Build and launch-related conversations also grew. The vibe coding moment of early 2025 had helped to popularize a form of software development that didn’t require significant technical expertise. Builders were now regularly developing and launching vibe coded products and services.
AI Reliability & Limits topics began to attract additional mindshare — although at a lower rate than other topics. Builders were starting to bump up against the limitations of LLMs and efforts of some AI labs to reduce compute costs.
Living in the AI Future
AI Agents: Builders Were 27 Months Ahead of the Public
In January 2023, Reddit published research arguing that Redditors are early adopters of new technologies. According to Reddit's survey, 53% of respondents said they are "the first among their friends to buy a new gadget", and 68% said they "like staying up to date on new technologies and gadgets."
If Reddit attracts early technology innovators and adopters, could builder communities on Reddit surface emerging AI trends months, or even years, before the general public starts paying sustained attention?
To answer this question, an analysis was conducted on posts published in builder Reddit communities between December 2022 and mid-May 2026. The focus was on measuring when key AI-related terms started to be referenced regularly. The threshold: the first month where a keyword appears at least 3 times in core builder subreddits. The terms selected were "AI agents," "agentic AI," and "Model Context Protocol."
Google Trends data was also examined to determine when the general public (in the US) started showing meaningful search interest. Specifically when the Google Trends monthly search score for a term was greater than or equal to 10.
Builder communities first crossed the study's discussion threshold for AI agents in March 2023. This timing is notable. March 2023 was the month AutoGPT was released, which helped popularize the idea that large language models could be more than chatbots. LLM capability could be greatly increased by wrapping them in systems that enable task planning, tool calling, auto-generated code development, and task-oriented activities.
These conversations were happening among people experimenting with tools, testing workflows, and imagining what these systems could become.
The broader public was not yet searching for "AI agents" at meaningful levels. Google Trends did not cross the study's mainstream search threshold, a monthly score of >=10, for "AI agents" until June 2025.
This represents a 27-month gap between when Reddit builder communities first started meaningfully discussing AI agents and when the term began registering in mainstream search behavior.
Agentic AI and MCP Follow the Same Pattern
The "AI agents" finding is the clearest example of builder Reddit being ahead of the mainstream, but it was not the only one.
The same is true for "agentic AI" and "Model Context Protocol."
For agentic AI, builder communities crossed the study's discussion threshold in April 2024. The public (as measured by Google Trends) did not cross the mainstream search threshold for the term until January 2025. That represents a 9-month gap.
This timing is important because "agentic AI" is more than a label. It reflects a shift in how builders think about AI systems. Instead of treating models as chatbots or autocomplete tools, builders were developing systems that could plan, use tools, manage workflows, and complete tasks with less step-by-step human direction.
Model Context Protocol, or MCP, followed a similar pattern.
Anthropic introduced MCP on November 25, 2024 as an open standard for connecting AI assistants to external systems, data sources, and tools. MCP gives AI agents a common way to connect with file systems, code repositories, databases, business tools, and other services.
That matters because agentic systems become much more useful when they can access context and take action through tools. A model that can only respond to a prompt is limited. A model connected to relevant data and tool interfaces can participate in more complex workflows.
Builder Reddit crossed the study's discussion threshold for Model Context Protocol in December 2024, shortly after Anthropic introduced it. Google Trends did not cross the mainstream search threshold for "Model Context Protocol" until July 2025. That represents a 7-month gap.
Taken together, the pattern is consistent: builder communities become aware of, and start leveraging key AI technologies before the mainstream.
Mind Virus: Builder Culture Spread and Evolution
Where topics converge and diverge
The previous section looked at whether builder Reddit identified emerging AI concepts before they appeared in mainstream search behavior.
This section looks at a related question: how did key topics appear across builder and broader AI communities over time?
To explore this, two groups of subreddits were compared. The first included core builder communities, such as r/SaaS, r/buildinpublic, r/SideProject, r/automation, and r/AI_Agents. The second group features broader AI communities, such as r/ChatGPT, r/OpenAI, r/Anthropic, r/ClaudeAI, r/LocalLLaMA, r/artificial, and r/GenerativeAI.
The goal was to compare topic timing and concentration. Some topics are tightly connected to builder culture, including business building, vibe/ship culture, and agent building. Others, such as tool frustration, prompt injection, and access control, reflect operational or security-related concerns of relevance to both community groups.
The chart shows how engagement with these topics changed between 2022 and mid-May 2026.
Darker areas indicate higher engagement within each community group. Each panel is normalized independently, which makes it easier to see patterns inside each cohort.
Business building and vibe/ship culture are much more concentrated in builder communities. This makes sense. These are communities where people talk about launching products, finding customers, monetizing tools, and shipping quickly.
But the broader AI communities also begin to show more interest in several builder-oriented concepts over time. For example, agent building becomes much more visible starting in mid-to-late 2024. Tool frustration rises as more people start using AI tools in real workflows. Vibe/ship culture also becomes more visible outside core builder spaces.
The pattern is not uniform. Some topics stayed builder-heavy. Others became more visible across both groups.
The bottom line: builder culture did not remain isolated.
The vocabulary and concerns associated with building started to appear more frequently in broader AI communities over time.
As AI tools became more practical, more agentic, and more widely used this trend accelerated in some areas.
Subreddit Areas of Focus
The previous chart shows topic concentration patterns across builder and broader AI communities over time. This chart provides a more granular view.
To better understand whether specific topics concentrate in certain communities, an analysis was conducted across subreddits. A selection of communities reviewed is shown in this chart.
The top row features example builder communities and the bottom row highlights broader AI communities.
The lines show the share of each community's annual conversation in key topic areas. Instead of simply measuring raw post volume, the analysis focuses on revealing the concentration of conversations in specific topic areas over time.
The builder communities show different facets of builder culture.
In r/SaaS, startup and business-related topics are prominent. In r/AI_Agents and r/automation, workflows (using AI and other tools) are increasingly important.
The broader AI communities show a different pattern. r/ChatGPT remains more advice- and usage-oriented. r/artificial is interesting because we can see topics related to startup growth and agentic development becoming more prominent over time.
This data illustrates how builder and AI culture are not monolithic. The same concepts can rise at different speeds, peak in different places, and mean different things depending on the community.
Topic crossover
This chart compares topic engagement rates across core builder communities and broader AI communities from 2025 to 2026.
Builder communities are shown on the right. Broader AI communities are shown on the left. The numbers represent mean engagement rate per 1,000 posts.
The story in the data is not just that builders talk more about building.
It's that builder communities appear to have a different mental model for AI.
In broader AI communities, AI is often discussed as a tool category. People compare models, ask which product is better, react to releases, and discuss what the technology can do.
In builder communities, AI is discussed as infrastructure for action. The dominant themes are business building and vibe / ship culture. That means AI is being framed around launching products, attracting users, creating revenue, automating work, and getting things into the world quickly.
That difference matters because it helps explain the broader arc of the report. Builders are not only adopting AI tools. They are reorganizing their work around them.
Agent building is the bridge between the two worlds.
By 2025 and 2026, agent building appears at similar levels in builder and broader AI communities. The concept is no longer confined to communities explicitly focused on shipping products or workflows. It has become part of the broader AI conversation.
Some operational concerns also sit in this shared middle. Tool frustration, credential exposure, and security awareness appear across both groups. As more people use AI systems for real tasks, the conversation becomes less theoretical and more practical.
The chart separates three kinds of topic behavior: builder-dominant, shared, and broader-AI-dominant.
The strongest builder-culture signal is still business building and vibe / ship culture. Those topics describe what builders are trying to do with AI: move faster, ship more, and turn technical capability into something useful.
From Shipping to Survival: Signs of Operational Maturity
Reliability Frustration
Builders, especially vibe coders, are often criticized for not paying enough attention to security when they ship products developed with AI assistance.
There is truth to this critique. Thousands of AI-generated applications have major security and privacy gaps.
This research has revealed that security topics do not capture as much mindshare in builder communities as other subjects. Product launches, customer growth, revenue milestones, workflow hacks: these are all much more exciting and interesting. Security can be confusing, scary, and not very sexy.
But the data shows a more interesting story than simple topic avoidance.
The data suggests two things are happening:
1. Builders are aware of (and vocal about) AI reliability issues, including hallucinations and broken workflows.
2. As dialogue about frustration has risen, builders have also been talking about key security topics.
This chart tracks several signals of AI reliability frustration in builder communities: hallucinations, context window limits, tools that stop working, and posts where builders describe getting tired of AI or agent systems.
The change is sharp. These signals were low from 2022 through 2024. They rise in 2025 and accelerate again in 2026.
Complaints about AI systems rose as builders began to rely on them for complex workflows, major product features, and ambitious projects.
When AI tools are experimental, failures are annoying.
When AI tools become part of a workflow, failures are serious operational problems.
A hallucination can cause significant damage. LLMs get 'dumber' as context windows fill up. An agent that runs in an infinite loop can waste money.
Builders started by trying to ship faster. As builder-developed software systems become more mission-critical, AI agent reliability can be the difference between success and failure.
And, when the focus is on reliability, additional questions naturally arise, such as what is that agent doing with my API keys?
Security Awareness Is Rising
As discussed previously, security topics receive less attention than shipping, launching, monetization, tool comparison, or agent building. But builder communities are not completely indifferent to security.
This chart tracks mentions of formal security terms in core builder communities, including CVE, security audit, security review, red team, OWASP, threat model, penetration test, and pen test.
For most of the study period, references to these terms were limited.
This changed in 2025 and 2026.
Mentions of terms like security audit, CVE, security review, red team, OWASP, and threat model all rise in the later part of the study period. The absolute numbers are still modest, but the direction is clear.
This trend suggests builder communities are maturing. More products built with AI assistance are reaching real users. More builders are connecting models to APIs, databases, payment systems, customer data, and production workflows.
At this point, security is becoming harder to treat as a minor or distant concern.
This is an important shift. Security awareness is not yet a defining feature of builder culture, but it is becoming more visible.
Security Vocabulary
This chart shows the security terms that are mentioned most often in core builder communities. The largest category is operational security language: API keys, authentication, credentials, rate limits, encryption, and environment variables.
It is unsurprising that builders are focused on operational security concerns like these. API keys and environment variables are the keys to the kingdom. And, protecting these secrets is a practical, concrete problem with proven solutions.
Formal security terms, such as prompt injection and penetration testing, are much less frequently mentioned. This may be due to lower awareness, but it may also reflect the fact that these issues are more abstract and potentially difficult to mitigate.
The growth chart on the right shows that all three security categories increased over time. Operational security language grew the most. Regulatory terms also rose, especially GDPR and HIPAA. Formal security language increased too, but from a smaller base.
This data suggests that improving builders' security posture may require meeting them where they already are. For example, while helping them prevent their agents from committing API keys to GitHub, also giving them tools to defend against prompt injection.
It's not about pulling builders out of shipping mode, but giving them security support that enables them to ship with greater confidence.
Moving Outside the AI Bubble
Same vocabulary, different priorities
This analysis compares two different windows into AI interest.
The first is Google Trends search behavior between January 2025 to mid-May 2026. This reflects what the general public is looking for when they search around AI, ChatGPT, artificial intelligence, and AI tools.
The second is Reddit posts from broader AI and core builder communities during the same period. This reflects what people are posting about, debating, recommending, building, and troubleshooting.
The purpose was to compare and contrast general public AI interest with Reddit AI discussion.
The chart groups terms into five buckets: access and cost, tools and comparison, building and infrastructure, models and brands, and content creation.
Some overlap is apparent. ChatGPT, Claude, Gemini, AI tools, free tools, and image generation appear in different forms across the data.
But the differences are just as important.
The general public is more likely to focus on basic understanding, access, cost, and product discovery: what AI is, which tools are best, whether ChatGPT is free, how to log in, and which branded products are worth trying.
Broader AI communities on Reddit are more focused on models, product capabilities, creative output, and technical discussion: Claude Code, image generation, local LLMs, MCP servers, ChatGPT Plus, voice mode, and model comparisons.
Reddit builder communities are more focused on implementation: built tools, side projects, SaaS, landing pages, feedback, Product Hunt, open source, agents, and shipping in public.
What this analysis reveals is how different groups operate at varying levels of expertise and attention. The general public is still very much in AI discovery mode while builders understand what these tools offer and are focused on utilizing them to their fullest potential.
Same terms, different context
The Venn-style chart shows how even when each group uses the same words and phrases, their meaning and intent is very different.
For the general public, access and cost often means discovery: what AI is, whether a tool is free, how to log in, and which tools are available.
For broader AI communities, models and brands are often part of a capability conversation: which model is better, what changed, what features launched, and how people are using those systems.
For builders, building and infrastructure has a more practical meaning. It is connected to implementation: open source tools, agents, SaaS products, landing pages, feedback loops, and launch channels.
There are also clear areas of similarity.
All three audiences are interested in practical AI utility. Tools, models, and use cases appear across the data.
The public and builder communities both show interest in useful tools, especially free or business-oriented solutions.
Broader AI communities and builder communities overlap around infrastructure and workflow terms, including Claude Code, MCP servers, open source, and agent-oriented development.
The main difference is mindset.
Public search often asks: what is this, how do I access it, and which tool should I use?
Reddit AI communities focus on: what changed, what works, and how does this model or feature compare?
Builder communities often ask: what can I make with this, how do I ship it, and how do I turn it into a product?
The product-development orientation highlighted in this analysis aligns well with other data presented in this report.
Closing
What this research reveals and what to watch next.
This report features analysis on how builder culture and interest in building software products, services and solutions increased as AI technologies became more powerful and grew in utilization, including by people with limited technical backgrounds.
The research helps to improve our understanding of how AI builder communities on Reddit have evolved since the launch of ChatGPT, where builder attention has concentrated, how early builder discussion compares with mainstream public interest, and community blind spots.
It reveals several important patterns:
- Builder culture accelerated sharply as AI coding and productivity tools improved.
- Reddit builder communities often discussed major AI concepts before they gained mainstream public interest.
- Builder-focused language did not remain isolated to builder communities. Concepts connected to shipping, agents, workflows, and product development became more visible in broader AI-influenced Reddit communities over time.
- Public AI interest and Reddit AI posts overlap, but they reflect different mindsets. Public search is more focused on access, cost, discovery, and brands. Builder discourse is more focused on implementation, workflows, product development, and launch activity.
- Security is not one of the highest-mindshare builder topics, but security-related discussion is rising.
- When builders do talk about security, the language is practical and operational: API keys, environment variables, authentication, rate limits, encryption, cost exposure, and systems that can fail in production.
Future Builder Challenges
The bigger story is that AI builders are moving from experimentation to dependence.
Early AI building was often about speed: building, launching, and testing ideas faster.
As AI-generated and AI-assisted systems become more central to products and workflows, people are starting to ask serious questions, including:
- Can the system be trusted?
- Is this AI-powered product safe?
- Is the solution robust? Can it survive model changes, platform shifts, cost spikes, and security failures?
These questions will likely shape the next phase of AI builder culture.
Another emerging issue is related to the increasing capabilities of AI models.
Builders are creating products and services, but many may be vulnerable. AI labs are searching for revenue to justify the enormous investment dollars they have received. They are looking for any opportunity to generate business across many areas, including finance and productivity.
This poses a serious challenge to builders. A feature that looks differentiated today may become a default model capability tomorrow. Is a builder's product just one AI lab announcement away from being rendered obsolete? The very capabilities that enable rapid product development also pose a risk to long-term product viability.
A related challenge is the buy-versus-build problem.
In a world where AI can be used to create a reasonable facsimile of many products, builders will have to identify true moats. Code is becoming more commoditized. It will become increasingly easy for an agent to spin up a 'pretty good' facsimile of a solution. The value of a product will depend less on whether it can be built and more on whether it solves a real problem, reaches the right users, earns trust, fits into a workflow, and keeps improving after launch.
A third challenge is related to the viability of human-first communities like those on Reddit.
Currently, Reddit remains a rich source of human-to-human conversation and a valuable signal about where technology culture is moving. But AI-generated content is already flooding many subreddits analyzed for this research. Builders and others are increasingly using AI tools on Reddit to advertise, test, or market products and services. That activity can produce useful signals, but it could also crowd out the human voices that made Reddit valuable for this kind of research in the first place.
The question is whether this type of research will still be possible four years from now.
Human conversations are already harder to separate from automated promotion and AI-generated posts. Because of this, the work required to understand what humans are thinking about and doing will become more difficult.
The Security Question
Finally, security is a vital issue even if these topics are currently less present in Reddit builder community posts.
A signal about what the future holds from a security perspective is that builders are not ignoring this issue. They talk about security in very specific ways, focusing on immediate concerns such as exposed keys, privacy, and failure modes that can damage a product or business.
The data provides a clearer picture of how builders think about security and where they may be most receptive to help. Builders are never going to stop moving quickly and taking the shortest path to viability. Meeting builders where they are (and where they're going) could be the quickest path to a world where AI-aided app production is safer and more secure by default.
Methodology: How This Research Was Done
Study goal
In November 2022, ChatGPT launched. Almost immediately, people began thinking about how AI could help them develop products, workflows, and other solutions. Over the years, as the power and capabilities of AI-powered coding and productivity tools have improved, Reddit has become a central hub for builders to discuss their work. They discuss strategies for optimizing workflows, how to get the most out of coding tools, and increasingly ship new products, services, and solutions in public. The goal: gain new customers, collaborators, or simply awareness (and celebration) of their creations.
The purpose of this research is to create a “data portrait” of these communities to understand:
- How discussions have evolved
- The differences between conversations in product builder-focused subreddits (e.g., r/SaaS) and generalist AI communities (r/artificial and others)
- Whether builder culture has diffused into more generalist AI communities
- The ways communities are grappling with the limitations of AI, and what privacy and security issues are rising to the forefront of builder and non-builder posts
Why Reddit?
Reddit was selected because it is a hub of technology and builder-oriented conversations. Although Reddit is facing challenges from bot- or AI-generated content, it is still a source of organic, human-to-human conversations that provide rich insights and information.
Why focus on frequently discussed themes?
Recurring themes across a large post corpus provide a reliable signal of what communities returned to most during key periods. Topic modeling (Latent Dirichlet Allocation) was used to surface these themes from the text itself, without assuming in advance what would be found.
How posts were sampled
Reddit data was obtained from key AI and builder communities between December 2022 and mid-May 2026. Collection used fixed monthly sampling targets to keep coverage distributed across the study period. Historical gaps were backfilled from available Reddit archives using the same monthly target, with up to 800 posts per subreddit-month retained before quality filtering. The goal was not to capture every Reddit post, but to build a corpus large enough to show how discussion patterns evolved across communities and years.
380,445 posts were collected. Posts were then filtered for quality (removing removed or deleted content, ensuring minimum text length), with 261,511 posts remaining in the analysis corpus.
How text was analyzed
A major goal of this research was to discover what types of topics dominated Reddit conversations without making assumptions about what would be found. To achieve this, topic modeling (LDA, Latent Dirichlet Allocation) was used to model patterns in the preprocessed Reddit text. The model produced 25 topic clusters.
To interpret those clusters, lift scoring was applied to the model’s topic-word weights. A high lift score means that a term is used disproportionately within one topic compared with its average use across all topics. This helped surface the words and short terms that best differentiated each cluster, rather than relying only on the most frequent words.
Each post was assigned to the topic with the highest probability in its document-topic distribution. Topic share was then tracked by subreddit and year.
A separate bigram extraction step was used as an interpretation and validation layer. LDA produces topic-word patterns, but single words can be ambiguous. For example, a cluster containing the word “vibe” does not necessarily mean that posts were discussing “vibe coding.” For each topic cluster and year, posts where that topic was dominant were analyzed for common two-word phrases, such as “vibe coding,” “prompt injection,” and “API key.” This helped determine whether a trend was present as a specific phrase-level concept rather than inferred from loose single-word overlap.
Longitudinal analysis was conducted to understand topic share per subreddit between December 2022 and mid-May 2026.
Additional analysis was conducted using Google Trends data to understand the similarities and differences between what AI topics Redditors focus on versus the general public (by comparing search trend data to topics discovered via the analysis).
Study limitations
- Only English-language posts were analyzed for this study.
- The study focuses on sampled Reddit posts from December 2022 to mid-May 2026. Topics that appeared mainly outside the sampled posts or outside the collection period may be underrepresented.
- The seven builder-culture topic categories are not AI-specific. Themes like monetization, shipping culture, automation, and operational scaling existed in builder communities before AI tools became widely accessible.
- The study tracks shifts in how much attention each topic received over time. Some shifts align with major AI capability milestones, but the data does not establish a direct causal link between AI development and changes in builder conversation. Platform growth, macroeconomic conditions, broader developer culture trends, and subreddit-specific changes may also have contributed.
- Reddit builder communities saw a significant increase in post volume in 2025 and 2026. Some portion of this growth may reflect AI-generated or bot-authored content, which Reddit has acknowledged as an increasing platform-wide challenge. Earlier years in the analysis are less exposed to this issue, but findings specific to 2025 and 2026 should be read with this in mind.
- Data collection ends in mid-May 2026, so 2026 findings represent a partial year and should be interpreted as directional rather than full-year comparisons.
Data sources
- Primary: PullPush Reddit archive API providing historical post data. Used to collect Reddit data published from December 2022 to May 2025. PullPush did not provide posts past May 2025 at the time of analysis.
- Secondary: Arctic Shift used to collect Reddit posts published from May 2025 to mid-May 2026.
| Cohort | Subreddits | Posts (analysis corpus) |
|---|---|---|
| Core builders | 7 | 128,938 |
| Broader AI-influenced | 8 | 132,573 |
| Total | 15 | 261,511 |
