AI Assistants want to own the work we delegate

An AI assistant is becoming something you can give a job to. Increasingly, that job can involve gathering information, using applications, remembering previous decisions and following through over time. The ambition is to give more people access to the kind of support previously associated with a human personal or executive assistant.

The battle is heating up for general-purpose personal and work assistants: products that help an individual or team across multiple tasks and applications. An agent is the software that executes a task; an assistant is the continuing relationship through which users delegate those tasks. That distinguishes this race from narrower agents built exclusively for customer support, coding or another specific function.

The landscape includes personal and team assistants such as Instinct, Town, Lindy, Vellum, Poke and Jo; managed work agents such as Grok Bot, ChatGPT agent from OpenAI, Claude Cowork and Yutori Scouts; and open-source systems such as OpenClaw and NanoClaw. These categories overlap, but they help distinguish what users are buying and how they delegate work.

Why does this matter? Because the assistant could become the place where we decide what happens next. If it researches a purchase, chooses a service and completes a transaction, it can influence where money flows. If it coordinates work across business applications, it can influence which software people open, which subscriptions they value and which interfaces become less important.

That possibility helps explain the capital flowing into the category. Instinct reportedly raised a $250 million Series B at a $2.5 billion valuation, co-led by Index Ventures and Benchmark. But a valuable category does not guarantee that every assistant becomes a valuable company.

Harry Stebbings’ 20VC conversation with Town co-founder and CEO Jean-Denis Greze, and the accompanying takeaways, frame the central investment question: what can an independent assistant own as the underlying models and competing platforms improve?

Defining the competitive field

Comparing Gemini with Grok Bot is not quite apples to apples. One is a broad assistant product family; the other is a specific product designed to execute delegated work. A more useful comparison looks at the job each product takes over, how users interact with it and who operates the system.

The following landscape reflects documented positioning and capabilities, rather than a ranking based on hands-on performance testing.

The boundaries are porous. Town can execute tasks, Grok Bot can retain context, and an open-source system can support an ongoing personal relationship. The grouping describes their primary product approach, rather than exclusive capabilities.

Gemini supports recurring scheduled actions, while Meta AI already operates inside WhatsApp and other familiar interfaces. Both belong in the competitive picture. However, that presence should not automatically be equated with the execution capabilities of a dedicated work-agent product. Features also vary by plan, region and configuration.

Several bets on the same opportunity

Instinct’s bet is that personal delegation should feel as simple as contacting another person. Town places greater emphasis on professional routines and shared work: its site describes meeting briefings, inbox handling, recurring account updates and team integrations. Lindy similarly positions itself around connected tools and company context. Their potential advantage is learning how someone works and becoming useful without repeatedly asking them to explain it.

Vellum and Jo add other approaches to persistent personal assistance. Vellum now describes itself as personal intelligence, expanding beyond the enterprise AI development positioning described in its 2025 Series A announcement. Jo’s YC profile describes an agent spanning a user’s Mac and a private cloud machine. These products compete for the same underlying permission: becoming the assistant a person trusts with context and continuing work.

Poke illustrates both the opportunity and the consolidation already underway. General Catalyst led its $15 million seed round, backing an assistant delivered through familiar messaging channels. Its website now confirms it is joining Cognition. It remains relevant to the product landscape, but should no longer be presented as an independent startup.

Grok Bot takes a more explicit AI-worker approach. Its bots have persistent computers, use applications and can collaborate. ChatGPT agent and Claude Cowork bring delegated execution into products with existing users and subscriptions. Yutori Scouts approaches the opportunity through ongoing web tasks. These products put pressure on independent assistants to show why their particular experience is worth adopting.

Where OpenClaw and NanoClaw fit

OpenClaw and NanoClaw offer a different ownership model. Users can operate and customise the assistant system themselves, rather than relying entirely on a managed product. Neither is a foundation model. They organise how models use tools, maintain context and carry out work.

OpenClaw emphasises extensibility across tools and communication channels. NanoClaw emphasises a smaller, more inspectable system with container isolation. Its V2 announcement adds human approvals and persistent communication between agents.

The distinction matters because greater control comes with operational responsibility. Someone has to manage deployment, integrations, credentials and permissions. Self-hosting also does not automatically keep all processing local: external models and connected services can still receive data.

Container isolation limits what an agent can access; it does not guarantee that an authorised action is sensible. Sending the wrong email can still be damaging even if the software never escapes its sandbox. A dependable assistant needs both technical boundaries and good decisions about when to act, ask or stop.

These projects make the assistant layer easier to experiment with and reproduce. That expands the market while putting pressure on startups whose differentiation is largely a collection of integrations.

Why pay for another assistant?

This is the question every independent founder needs to answer. The major platforms already combine strong models with tools and increasingly proactive capabilities. Their users have existing subscriptions, familiar interfaces and accumulated context. An independent product must deliver a meaningful improvement over that baseline.

Consider a founder preparing for a customer meeting. Producing a briefing is useful. Consistently finding outstanding commitments, preparing the briefing, drafting the follow-up and updating the relevant systems after approval is a more valuable service. The differentiation lies in completing that process reliably, with less instruction each time.

For Instinct and Poke, the opportunity is making everyday administration easy enough to become habitual. For Town and Lindy, it is embedding assistance into professional and team routines. For Grok Bot and other managed agents, it is making delegated execution dependable. For OpenClaw and NanoClaw, control and customisation provide another reason to choose them.

The test across all of them is the same: how much work can I hand over without creating another job supervising it?

Distribution earns attention. Reliability earns delegation.

The giants have substantial advantages. Grok has a route to users through X. Google has existing productivity relationships. Meta already offers AI inside WhatsApp. Independent startups must persuade people to establish another relationship and connect another product to their working lives.

But access to users is different from permission to act for them. Someone may happily ask an assistant for restaurant suggestions while hesitating to let it contact a customer, make a purchase or change a booking. Each step towards autonomy requires the product to earn more trust.

The 20VC discussion raises doubts about whether assistants have achieved deep product-market fit beyond power users. I would frame this more narrowly: enthusiasm for AI is established, but habitual delegation remains a distinct product challenge. A successful demonstration does not tell us whether ordinary users return, pay and gradually need to intervene less.

A useful assistant should also reduce the burden of deciding what to delegate. If users must become expert prompt writers, integration managers and quality controllers, much of the promised productivity gain disappears.

Can assistants create network effects?

Greze’s emphasis on collaboration suggests a possible source of defensibility. An assistant could become more useful when it can coordinate with colleagues’ assistants, carrying context across departments and reducing the need to chase updates. Both Town’s team offering and NanoClaw’s agent-to-agent communication illustrate product development in this direction, although that alone does not establish network effects.

Imagine a salesperson’s assistant checking a customer’s commitments with the account team’s assistant before requesting a pricing exception from finance. More participating colleagues could make the system more valuable, provided it respects each person’s permissions.

But workflow lock-in is not automatically a network effect. Shared routines and organisational memory create switching costs. A genuine network effect requires each additional participant to improve the product for existing participants. Interoperability could also allow that value to accrue across competing assistant providers.

That is why I would not draw a permanent boundary between consumer and enterprise assistants. Instinct and Town may start with different users and buying decisions, but people’s personal and professional lives overlap. Their initial positioning explains their strategies; it does not guarantee they stay out of one another’s markets.

The investment case depends on completed work

The economics deserve as much attention as the product experience. A more active assistant can generate more inference, execution and support costs. Increased usage is encouraging only if the business can afford to serve it.

I would want to see cost per successfully completed workflow, including retries and human intervention, alongside paid retention and expansion. Task counts alone can conceal an expensive service. Equally, an assistant that appears cheap may deliver little value if the user repeatedly has to repair its work.

There may be several winners: a personal assistant, an assistant embedded in a productivity suite, a team-work platform and infrastructure supporting privately operated agents. The common requirement will be turning impressive capabilities into dependable delegation.

The company that earns the right to act repeatedly on our behalf could become one of the most valuable relationships in software.

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Eze Vidra

Co Founder and Managing Partner at Remagine Ventures

Eze Vidra is the founder of VC Cafe and the co-founder and managing partner of Remagine Ventures, a pre-seed fund investing in ambitious founders at the intersection of AI, technology, entertainment, gaming, and commerce with a spotlight on Israel.

He is a former General Partner at Google Ventures (GV) in Europe, former head of Google for Entrepreneurs in Europe, and founding head of Campus London, Google's first startup hub. Eze writes on Israeli tech, venture capital, artificial intelligence, and founder strategy.

He is also the founder of Techbikers, a nonprofit that brings together the startup ecosystem on cycling challenges in support of Room to Read.

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