18 Hot Takes On Where AI is Headed Next — DeepSeek Tips &…
    Neura MarketNeura Market/DeepSeek
    ChatGPTChatGPTClaudeClaudeGeminiGeminiCursorCursorGrokGrokPerplexityPerplexityDeepSeekDeepSeek
    CoPilotCoPilotStable DiffusionStable DiffusionMidjourneyMidjourney
    View All Directories
    OverviewRulesPromptsMCPsAgentsGamesBlogVideosGuidesCoursesCommunityTrending
    DeepSeekBlog18 Hot Takes On Where AI is Headed Next
    Back to Blog
    18 Hot Takes On Where AI is Headed Next
    aie

    18 Hot Takes On Where AI is Headed Next

    dev.to staff July 2, 2026
    0 views

    by Peter Yang, Behind the Craft Today, I want to share 18 hot takes on where I think the AI market...

    by Peter Yang, Behind the Craft

    Today, I want to share 18 hot takes on where I think the AI market is headed.

    AI is in a weird place right now. The government is restricting access to frontier models, enterprises are becoming conscious of token costs, and everyone’s trying to rebuild their product for agents first instead of humans.

    I’ve interviewed dozens of AI leaders and spent far too much time following these topics on X/Twitter. Here are 18 hot takes on where I think AI is headed next:

    1. The frontier-only AI stack is collapsing
    2. The AI super app era is here
    3. Traditional software risks becoming a dumb pipe for agents
    4. Cloud agents and collaboration are the next wave

    The Frontier-Only AI Stack Is Collapsing

    1. Tokenmaxxing at frontier API prices makes no sense. Uber burned through its entire 2026 AI budget in 4 months, Microsoft moved engineers off Claude Code due to cost, and companies are realizing that running everything on frontier models can get expensive fast. Tokenmaxxing makes sense when you’re on a subsidized $200/month plan but is unsustainable at API rates.

    2. Companies will rely on a portfolio of models. Coinbase recently cut its AI spend nearly in half by switching engineers to Chinese open-source models like GLM and Kimi. Airbnb and Pinterest have done the same with Alibaba’s Qwen models. I believe that this will be the default path forward — using frontier for high-stakes work and cheaper models for everything else.

    3. China’s open-source strategy is working. Chinese models are taking market share from frontier models at US companies. China is also building the full AI stack — from energy (e.g., solar, nuclear) to data centers to domestic chips. The Chinese government is planning a $295B investment in AI data centers with at least 80% of the chips built domestically.

    4. Frontier labs are in a catch-22 situation. If they release great open-source models, they might undercut their own frontier API revenue. If they gate the best models behind a trusted list, companies will just lean on open alternatives more. The last major US open-source model was OpenAI’s gpt-oss series back in August 2025, which already feels like decades ago in the AI space.

    5. The US needs to think about its AI strategy holistically. I believe that restricting access to frontier models will only hurt American innovation. Banning US companies from Chinese models won’t work either. Just look at how China took over the global electric vehicle market. To compete, we need the best closed and open models while scaling our energy grid and data centers much faster.

    The AI Super App Era Is Here

    1. Anthropic and OpenAI want to transform all knowledge work. Both labs want to remake how white-collar work gets done with agents. What started with coding has expanded to design, finance, legal, science, and more. Knowledge workers are now adopting Codex three times faster than developers.

    2. The race to build the best AI super app is on. Whoever wins it will take massive market share away from pre-AI knowledge work tools. The main players are Codex, Claude, Cursor, and a few others. With browser and computer use, I can already get Codex to handle almost everything I want to do on my computer.

    3. OpenAI is well positioned to win the super app race. ChatGPT has 800M+ weekly active users and Codex is arguably the best AI super app right now. OpenAI has a clear opportunity to merge ChatGPT and Codex into one app and push agents into the mainstream. I think this is imminent.

    4. Anthropic leads enterprise but has a fragmented product suite. Long term, I don’t think it makes sense for Claude, Cowork, Claude Code, and Claude Design to all exist as separate products. Working with Claude needs to feel more like working with a single capable coworker instead of a product suite. Claude Tag, Anthropic’s new agent for Slack, is a step in the right direction.

    Software Risks Becoming A Dumb Pipe For Agents

    1. Agents are becoming the default user. Most products are still designed for humans clicking buttons, but agents will very soon read, write, buy, and do a lot more on our behalf. Cloudflare’s data shows that bot traffic to websites already exceeds human traffic. This matches my personal experience — I rely on agents like Hermes and Codex to browse websites and steer traditional apps.

    2. If your product isn’t built for agents, it might as well not exist. Without clear APIs, documentation, and CLIs or MCPs, agents simply won’t discover your product, and neither will the humans who now lean on agents to find things. That’s why the best AI builders I’ve interviewed are all building for agents first.

    3. Existing knowledge work products risk becoming dumb pipes. There’s a dark side to building everything for agents first. Take Google Workspace, for example. If I can just use Codex to edit Google Docs for me, I might never touch the Google Docs interface. Today’s apps risk becoming tomorrow’s dumb pipes for agents, the same way cable became the dumb pipe for internet apps.

    4. Adding an AI chatbot to your product isn’t going to save you. A chatbot trapped inside a single app, with only that app’s context, can’t compete with an agent like Hermes or Codex that carries my personal context and gets work done across many apps. For example, I get a daily morning brief from Hermes that pulls info from my calendar, unread emails, and Slack.

    5. Pure-play SaaS is losing to services with SaaS bolted on. Companies don’t want another SaaS tool to onboard to and maintain. Instead, they want an outcome delivered to them. Pure-play SaaS will struggle to compete with AI skills that users and teams can build and personalize inside their favorite AI super app.

    Cloud Agents And Collaboration Are The Next Wave

    1. Startups can compete with AI labs by going deep and using a portfolio of models. For example, coding startups like Devin and Factory are doing well because their harnesses route across multiple models to help customers save on cost without giving up performance. They’re also focused on a few specific use cases instead of trying to be everything to everyone.

    2. Always-on cloud agents will be accessible from any device. Running agents with your laptop half-open will feel silly soon. Instead, many builders are already launching cloud agents using Cursor, Devin, and others. Codex and Claude Code are no doubt working on the same experience, and this will be the default soon.

    3. Collaboration between agents and teams has yet to be figured out. The default agent harness with a list of threads on the left is still very much a single-player experience. The multiplayer experience is still being defined — whether that’s Claude Tag in Slack, agents in Linear, or something else.

    4. “The future isn’t 20 terminal tabs. It’s better loops.” I watched Peter Steinberger share this in his keynote at yesterday’s AI Engineer conference. He no longer watches the agents code. Instead, he defines the requirements, and let agents plan, execute, and validate by themselves. I’m a bit wary of loops since they can lead to AI slop, but I’m sure better planning and models will make them more mainstream.

    The AI Market Is About To Get A Lot More Interesting

    Here are my 18 takes summarized in four bullets:

    1. The frontier-only AI stack is collapsing. Companies will use a portfolio of models to save costs, with everyday tasks defaulting to low-cost open models from China.

    2. The AI super app era is here. Codex, Claude, Cursor, and others are competing to disrupt knowledge work by using agents for everything you can do on a computer.

    3. Traditional software risks becoming a dumb pipe. Agents will become the default user. They’ll use APIs and browser use to access your website and app without humans ever seeing them.

    4. Cloud agents and collaboration are the next wave. The future is agents living in the cloud, accessible from any device, and collaborating closely with both you and your team. This will happen very soon.

    Let me know what you think about these takes in the comments!

    Tags

    aiediscusssoftwareai

    Comments

    More Blog

    View all
    Five Gemma-4 models, one accelerator: what porting E2B 31B to AWS Inferentia2 taught megemma

    Five Gemma-4 models, one accelerator: what porting E2B 31B to AWS Inferentia2 taught me

    I ported the whole Gemma-4 family — E2B, E4B, 12B, 31B, and the 26B-A4B MoE — to run on...

    X
    xbill
    Hey DEV, I'm Tobore. Let's actually connect.community

    Hey DEV, I'm Tobore. Let's actually connect.

    Hey DEV, I'm Tobore. Let's actually connect. I've been on here for a while now, mostly writing and...

    L
    Laurina Ayarah
    I burned through thousands of AI tokens. Then a friend did it for freeai

    I burned through thousands of AI tokens. Then a friend did it for free

    (yep, kinda clickbait, just for the funsies 😊) At the beginning of the year, I relaunched my...

    P
    Paulo Henrique
    Claude might be saturating your machineai

    Claude might be saturating your machine

    My laptop was sitting idle with the fan at full tilt. Nothing was running that I knew of. The culprit...

    S
    Sidhant Panda
    Automated GitHub Code Reviews Using Google Geminigithubactions

    Automated GitHub Code Reviews Using Google Gemini

    I Built a Thing! TL;DR — Google Gemini-based Pull Request reviews and Issue Triaging for...

    D
    Darren "Dazbo" Lester
    What is an "agentic harness," actually?ai

    What is an "agentic harness," actually?

    I've been hearing the word "harness" thrown around a lot lately. I assumed it just meant "the IDE" or...

    T
    Tilde A. Thurium

    Stay up to date

    Get the latest DeepSeek prompts, rules, and resources delivered to your inbox weekly.

    Neura Market LogoNeura Market

    Discover the best AI prompts, plugins, and resources for DeepSeek and more.

    Content Types

    • Rules
    • Prompts
    • MCPs
    • Agents
    • Guides

    Platforms

    • ChatGPT Directory
    • Claude Directory
    • Gemini Directory
    • Cursor Directory
    • Grok Directory
    • Perplexity Directory
    • DeepSeek Directory
    • CoPilot Directory
    • Stable Diffusion Directory
    • Midjourney Directory
    • All Directories

    Resources

    • Blog
    • Documentation
    • Help Center
    • Marketplace

    Legal

    • Privacy Policy
    • Terms of Service

    © 2026 Neura Market. All rights reserved.

    |

    Not affiliated with any AI platform vendors.

    Neura Market

    Custom AI Systems & Services

    Our team of experienced AI builders will help build custom AI systems, workflows, and solutions for your business.

    Request custom work

    Ready-made automations for this

    Workflows from the Neura Market marketplace related to this DeepSeek resource

    • Automate Blog Content Creation with Notion MCP, DeepSeek AI, and WordPressn8n · $9.99 · Related topic
    • Generate AI Videos from Scripts with DeepSeek, Synthesia, and Together.ain8n · $24.99 · Related topic
    • Compare Multi-Period Financial Data from Google Sheets with DeepSeek AI Analysisn8n · $14.99 · Related topic
    • PostgreSQL Conversational Agent with Claude & DeepSeek (Multi-KPI, Secure)n8n · $14.99 · Related topic
    Browse all workflows