Tools & Platforms

This startup thinks email could be the key to usable AI agents

Published

2 months ago

July 22, 2025

AI companies are pushing agents as the next Great Workplace Disruptor, but experts say they’re still not ready for prime time. AI agents often struggle to make decisions by themselves, hallucinate frequently, can’t cooperate with other agents, fail at confidentiality awareness, and integrate poorly with existing systems.

Industry pioneers like Andrej Karpathy and Ali Ghodsi have said that, like the deployment of autonomous vehicles, humans need to be in the loop in order for agents to succeed.

A startup called Mixus wants to address that with its AI agent platform that not only keeps humans in the workflow, it also lets users interact with agents directly from their email or Slack.

“We’re meeting customers where they are today,” Elliot Katz, Mixus’ co-founder, told TechCrunch. “Where is every person in the workforce today? For the most part, they’re on email. And so because we can do this through email, we believe that’s a way we can democratize access [to agents].”

If Mixus works reliably, it may solve a big problem in the AI agent space. Most AI companies today either give you a pre-built assistant, à la ChatGPT or Gemini, or developers have to build custom agents using frameworks like LangChain, AutoGen, or crewAI.

Mixus launched in beta out of Stanford only in late 2024, but it has already raised $2.3 million in pre-seed funding and brought on some customers, including clothing store chain Rainbow Shops, as well as others across finance and tech.

The startup says its biggest selling point is ease of use, from how it helps you create agents to how you can interact with them. Users can use text prompts to set up their agents within Mixus’s platform via a chat function, or by simply emailing instructions to agent@mixus.com. Then Mixus will build, run, and manage single- or multi-step agents directly from the inbox.

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For example, a salesperson may use a prompt that reads so:

Create an agent that finds all open tasks in Jira in project mixus-dummy, and send me a report with information on all tasks that are overdue. Draft emails to all the assignees who have overdue tasks, and have me review them in the chat and with simple clear formatting for email (no attachments/docs). Once I verify, send the emails. Run it now. And moving forward, run it every Monday at 7am PST.

Image Credits:Mixus

Katz and his co-founder Shai Magzimof demoed the agents for TechCrunch, showing how to add human verifiers for your agents by simply instructing at which step the agent should ask you for oversight.

For example, they ran an agent to do research on TechCrunch reporters before pitching them. The agent identified and gathered technology news and trends, analyzed the information to identify potential story angles, and compiled a research report summarizing the findings. At the last stage, the agent was directed to send the information to Katz for verification. Once approved, the agent would send the completed research report to Magzimof.

The founders noted that humans can be in the loop as much or as little as required — Magzimof said organizations can set up company-wide rules, like ensuring an email gets checked by a human if it’s being sent outside the company.

Bringing other colleagues into the workflow is as easy as tagging them in the chat with an AI agent, or copying them on the email to the agent. That’s another standout compared to agents on the markets today: Most models are single-user, and while Notion AI and Slack allow users to collaborate in shared spaces, they don’t let the AI manage conversations and tasks between teammates in real time.

Another core feature of Mixus is its ability to remember files, chats, prompts and agents.

“We created Spaces so that every team, every person, every group of people can have a shared memory,” Magzimof said. “Then all my agents, all my files, all the people can be in that very specific Space’s memory.”

While ChatGPT and Claude both support memory, their enterprise plans don’t yet support shared agent memory across users.

What else can Mixus do?

In our interview, the founders ran through an hour-long demo showing a range of use cases and abilities. Mixus’ agents do seem capable, reflecting a high degree of autonomy and memory that places the company towards the higher end of the AI agent spectrum. That is, if the product works as reliably as it did in the demo.

Like other agents, Mixus can integrate with other tools, from Gmail to Jira, and users can trigger agents to run immediately or on a schedule. Agents can run and edit documents or spreadsheets inline — similar to ChatGPT, Microsoft Copilot, and Google Gemini, but those are often limited to sandboxed environments.

Mixus also lets agents autonomously navigate organizational context — like figuring out who in an organization owns a task by looking through Jira tickets.

Built on a combination of Anthropic’s Claude 4 and OpenAI’s o3, Mixus agents also have access to the web, which Magzimof says can be tapped for tasks like live research or monitoring. He described it as “Google Alerts on steroids.”

Taken together, Mixus appears to be less of a productivity tool and more like a tireless digital colleague – yet another ambitious attempt to reimagine AI as a collaborator. If it works as advertised, your next “coworker” might not be human, but it might get through your inbox faster than you do.

Got a sensitive tip or confidential documents? We’re reporting on the inner workings of the AI industry — from the companies shaping its future to the people impacted by their decisions. Reach out to Rebecca Bellan at rebecca.bellan@techcrunch.com and Maxwell Zeff at maxwell.zeff@techcrunch.com. For secure communication, you can contact us via Signal at @rebeccabellan.491 and @mzeff.88.

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Tools & Platforms

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1 hour ago

September 7, 2025

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Tools & Platforms

Creating more jobs while transforming work

Published

2 hours ago

September 7, 2025

Krishna Kumar & Rakshitha Reddy

Artificial intelligence is reshaping employment in ways that challenge basic assumptions about work and human value. While headlines focus on job displacement fears, the data tells a different story: AI will create far more jobs than it eliminates, generating 78 million net new positions globally by 2030.

The World Economic Forum shows that economy-wide trends – including AI adoption, green transition, and demographic shifts – will create 170 million jobs while displacing 92 million. This isn’t simple technological substitution; it represents entirely new forms of human-machine collaboration that require rethinking the boundaries between human and artificial intelligence.

As AI handles routine cognitive tasks, humans are being pushed toward work demanding creativity, emotional intelligence, and nuanced judgment that remains uniquely human. The question isn’t whether we can adapt – it’s whether we can evolve quickly enough to thrive.

Emergence of human-AI collaboration roles

The most revealing development in AI employment isn’t traditional tech job creation, but roles that exist precisely because humans and machines think differently. Tesla’s AI generalists, commanding salaries from $118,000 to $390,000, represent a new professional category: individuals who translate between artificial and human intelligence.

These roles reveal a deeper truth. Rather than replacing human intelligence, AI is highlighting its uniqueness by contrast. The most valuable workers aren’t those competing with machines at computational tasks, but those complementing artificial intelligence with distinctly human capabilities -contextual understanding, ethical reasoning, and navigating ambiguity that remains beyond algorithmic reach.

This represents more than new job categories – it’s the emergence of professionals who serve as translators between artificial and human intelligence. Like social media creating community managers who understood both technology and human behavior, AI creates roles requiring fluency in both machine logic and human insight.

Specialized expertise in AI age

The AI job market is rapidly organizing around a crucial insight: as artificial intelligence handles routine analysis, human expertise becomes more specialized and valuable. Apple’s Machine Learning Algorithm Validation Engineers, earning $141,800-$258,600, don’t just test code – they make judgment calls about when AI systems are safe for real-world deployment.

This specialization reflects a broader pattern across industries. AI Security Specialists, commanding low-six figures to mid-$200,000s, aren’t just cybersecurity experts – they understand how adversaries might exploit AI systems’ tendency to hallucinate or misinterpret edge cases. Their expertise lies in understanding AI vulnerabilities in ways only human insight can provide.

The educational requirements tell a similar story. While many advanced AI roles still prefer graduate credentials, degree requirements have been easing in AI-exposed jobs since 2019 as employers prioritize skills and portfolios. Companies seek individuals who think critically about AI implications, understand limitations, and make nuanced decisions about deployment and oversight.

Education and the transformation of human development

Educational mobilization around AI reflects recognition that transformation goes beyond job training to fundamental questions about human development. In August 2025, Google announced a three-year, $1 billion commitment to provide AI training and tools to US higher-education institutions and nonprofits.

Some selective, cohort-based AI training programs report completion rates approaching 85 per cent, significantly higher than traditional online courses. This success reflects a deeper truth: effective AI education isn’t about learning to use tools, but developing new ways of thinking that complement rather than compete with artificial intelligence.

The paradox of progress and human value

The most counterintuitive aspect of AI employment transformation may be its effect on human value. As artificial intelligence becomes more capable, skills that remain uniquely human become more precious. Recent analyses find salary premiums for AI skills – around 28 per cent in job postings and up to 56 per cent in cross-country comparisons within occupations.

PwC projects AI could contribute $15.7 trillion to the global economy by 2030, while the International Monetary Fund warns that nearly 40 per cent of global employment faces AI exposure, with advanced economies experiencing approximately 60 per cent exposure. These figures suggest transformation rather than simple displacement – work requiring humans to collaborate with AI systems while providing oversight, creativity, and ethical reasoning that algorithms cannot supply.

The gaming industry exemplifies this paradox. Despite experiencing restructuring-related layoffs, 49 per cent of game development workplaces now use AI tools. Rather than eliminating creative work, AI is pushing human creativity toward higher-level conceptual thinking – story design, emotional narrative, and cultural understanding that gives entertainment meaning rather than just technical competence.

Preparing for fundamental transformation

The research reveals both unprecedented opportunity and profound challenge. While AI creates more jobs than it eliminates, WEF estimates roughly 44 per cent of workers’ skills will be disrupted in the next few years. This suggests transformation beyond retraining to fundamental questions about human adaptability and productive work.

Success stories from early adopters provide valuable insights. Companies implementing comprehensive AI training report significant productivity gains not because humans become more machine-like, but because they learn to leverage AI capabilities while providing uniquely human value.

Adaptation or transformation

The AI employment revolution represents more than technological change- it’s an opportunity to reconsider fundamental assumptions about human potential, work, and value creation. The 78 million net new jobs by 2030 will demand not just new skills but new ways of thinking about intelligence, creativity, and what makes humans irreplaceable.

The geographic and demographic dimensions add complexity that cannot be ignored. Advanced economies face higher AI exposure than emerging markets. In the U.S., 21 per cent of women versus 17 per cent of men work in jobs among the most exposed to AI. The transformation risks exacerbating existing inequalities unless approached with intentional focus on inclusive development and equitable access to AI-era opportunities.

Embracing the transformation thoughtfully

The AI employment revolution offers an unprecedented opportunity to elevate human work beyond routine tasks toward creativity, relationship building, and the kind of meaning-making that defines our species. The infrastructure investments, educational initiatives, and emerging job categories all point toward a future where humans and artificial intelligence collaborate rather than compete.

The choice before us extends beyond managing technological disruption to embracing human potential in an age of artificial minds. By recognizing that AI’s greatest gift may be forcing us to discover what makes us irreplaceably human, we can build a future where technology amplifies rather than diminishes human flourishing.

The 78 million jobs being created aren’t just employment opportunities – they’re invitations to discover new forms of human capability, creativity, and value creation. The workers who answer that invitation thoughtfully, organizations that embrace human-AI collaboration purposefully, and societies that ensure broad access to AI-era opportunities will shape a future where artificial intelligence serves to reveal rather than replace the irreplaceable nature of human intelligence.

That future requires action today – not just in retraining programs or policy frameworks, but in reimagining what it means to be human in an age of artificial minds. The opportunity is unprecedented, and the time for thoughtful transformation is now.

(Krishna Kumar is a Technology Explorer & Strategist based in Austin, Texas in the US. Rakshitha Reddy is AI Engineer based in Atlanta, US)

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