I’ve been spending more time working with AI recently, and one area that particularly interests me is the growth of AI work platforms—platforms where developers and specialists contribute to model training, evaluation, coding, reasoning, data quality, and other AI-related projects. What interests me is how this ecosystem may evolve over the next few years. As AI systems become more capable, companies still need skilled people to evaluate outputs, solve difficult technical problems, create high-quality data, and improve how models perform in real-world situations. I’m a software engineer, so I’m especially interested in the technical side: coding, AI tasks, development, evaluation, and project delivery. I’m also interested in connecting with people who understand operations, client communication, project coordination, and business development. I think combining strong technical execution with strong business and operational skills could create some interesting opportunities in the AI space. If you're currently working with AI platforms or exploring this field, I’d love to hear what you're seeing. Where do you think AI work platforms are heading in 2026 and beyond?

I’m a developer with experience working on AI-related projects and platforms similar to Outlier. I’m currently looking for a reliable partner interested in collaborating on AI platform opportunities. The collaboration would be straightforward: you would handle the platform workspace/account and the necessary client-facing communication, while I would focus on completing the technical/project tasks that come through the platform. I’m particularly interested in working with someone based in the US who is reliable, communicates well, and is interested in building a long-term working relationship. Responsibilities and profit sharing can be discussed openly and agreed upon based on each person’s contribution. If this sounds interesting to you, feel free to message me and we can discuss the details.

I’m a developer with experience working on AI-related projects and platforms similar to Outlier. I’m currently looking for a reliable partner interested in collaborating on AI platform opportunities. The collaboration would be straightforward: you would handle the platform workspace/account and the necessary client-facing communication, while I would focus on completing the technical/project tasks that come through the platform. I’m particularly interested in working with someone based in the US, Canada, UK, or Australia who is reliable, communicates well, and is interested in building a long-term working relationship. Responsibilities and profit sharing can be discussed openly and agreed upon based on each person’s contribution. If this sounds interesting to you, feel free to message me and we can discuss the details.

Hi everyone, First of all, thank you for the recommendations and positive feedback on my recent post about the direction of AI in 2026. I really appreciate everyone who took the time to read, react, and share their thoughts. I’m currently looking for a co-founder/partner who is interested in working with AI platforms and AI-related client projects. My background is on the technical side. I can take ownership of the AI engineering, development, integrations, automation, and overall technical delivery of the projects. I’m looking for a partner who can focus more on the client-facing and business side, including: Communicating with clients Understanding and clarifying requirements Managing client relationships and follow-ups Supporting project coordination Helping with business development and new opportunities The ideal partner does not need to be highly technical, but should be reliable, professional, and comfortable communicating with clients. For practical collaboration reasons, I’m currently looking for someone based in the United States, Canada, United Kingdom, or Australia. If you’re interested in AI platforms, client-based AI projects, and building a long-term working relationship, feel free to message me. I’d be happy to discuss how we could collaborate, divide responsibilities, and structure the partnership fairly.

I’ve recently started working more closely in the AI field, and the speed at which this industry is evolving has really caught my attention. As a developer, what interests me most is that AI is no longer simply about asking a chatbot a question and receiving an answer. We are moving toward a new stage where AI can reason, use tools, interact with software, and complete multi-step tasks on behalf of users. This transition from AI assistance to AI execution may be one of the most important technology shifts happening right now. The rise of AI agents For the last few years, generative AI was largely centered around prompts: write an email, summarize a document, generate some code, or answer a question. That is changing quickly. Companies are now building agents that can work across applications, retrieve information, modify files, execute workflows, and complete longer-running tasks with human supervision. Recent enterprise data from OpenAI illustrates how quickly this is happening. As of June 2026, agentic AI accounted for 64% of combined ChatGPT and Codex output tokens among its enterprise customers. Agent usage is also expanding beyond engineering into areas such as sales, recruiting, legal, and marketing. For developers, I think this changes the opportunity significantly. The question is becoming less: “How can I add AI to my application?” and more: “What complete workflow can AI take responsibility for?” Companies are investing enormous amounts in AI infrastructure Another thing that stands out is the scale of investment. AI requires GPUs, data centers, networking, storage, electricity, and increasingly specialized infrastructure. Gartner expects worldwide spending on AI-optimized infrastructure-as-a-service to reach about $42 billion in 2026, up 96%, with inference spending surpassing training spending this year. The biggest technology companies are investing at an even larger scale. TrendForce estimates that combined 2026 capital expenditure from nine major cloud and technology companies—including Google, Amazon, Meta, Microsoft, Oracle, Alibaba, Tencent, Baidu, and ByteDance—will exceed $886 billion. But this also creates pressure. Investors are increasingly asking whether this massive infrastructure spending will translate into sustainable revenue and profits. Recent reporting shows that companies are taking on substantially more debt to finance AI infrastructure, meaning the industry is moving from pure excitement toward a stronger focus on economics and returns.