monday.com、AI エージェントと人間の協働を中核としたプラットフォームへ再構築

More than 250,000 companies, from small and midsize businesses to Fortune 500 organizations, use monday.com to manage their work. When the company launched more than a decade ago, its core product was a visual interface that helped teams automate workflows and manage projects. Today, it has rearchitected its product from the ground up around a human-agent collaboration model where AI is woven into work at every level. With Claude at the core, monday’s new platform handles the technical complexity so customers can work at the AI frontier inside workflows they already know.

"The shift to an agent-first product was one of the most significant decisions we've made as a company," said Daniel Lereya, chief product and technology officer at monday.com. "It meant fundamentally reimagining what the platform should do, not just adding AI to existing workflows. Our vision is for monday to be the place where people and AI agents work together seamlessly and Anthropic and Claude have been trusted partners in helping us bring that vision to life."

Hitting the “AI dust” ceiling

monday’s rebuild unfolded in three phases. In the first phase, as frontier LLM technology matured and customer excitement grew, monday teams worked on embedding AI capabilities into its original platform. The effort culminated in May 2025 with an internal “AI month,” with four weeks dedicated to shipping AI features or products across the company.

Adoption was strong and generated excitement, but soon the team hit a ceiling. “We were building ‘AI dust’, sprinkling automations onto existing workflows without embedding them within or changing the product’s fundamental value proposition,” says Orly Stern Izhaki, VP of Product, AI Works Platform at monday.com. “Our features helped users summarize text and categorize information, but they weren’t creating sustained usage patterns.”

The company needed to shift focus from adding AI to product features to building it natively into the platform. "Adopting AI features is not the same as becoming an AI company," Izhaki says. "Once we understood that, everything changed."

That’s how Izhaki’s team set out to reimagine monday completely: from a work management tool to a place where people and agents get work done together. While the mandate to transform the product came from the top, it was up to each team and each employee to translate that north star into concrete product choices and build their own agents.

After months of intense work, the company announced the most significant change in its history, rebuilding its entire product experience around humans and agents working together, using already built-in context, workflows, boards, permissions, and governance. Since launching in May 2026, monday’s customers have had more than 5 million interactions with agents on its platform.

Agents as teammates

Along with access permissions and restrictions, each monday agent is given a name and an avatar, and colleagues can assign agents work through triggers and mentions in the monday platform.

This design was intentional, addressing a pattern monday noticed across its customer base: many enterprises want to put AI to work, but often stall at an AI chat that runs parallel to where they actually do the work. Embedding agents directly into workflows and enabling people to interact with them like they would with their colleagues turned agentic AI from an abstract concept to a concrete, actionable one.

The jobs monday has mapped for agents range from IT ticket triage and knowledge-base upkeep to candidate sourcing and interview scheduling, competitive-intelligence briefings for sales and marketing, and chief-of-staff work like meeting prep and converting decisions into tracked tasks.

*Agent teams and their jobs for four common workflows.*

Four ways to run Claude in monday

Customers use Claude inside the monday platform through four capabilities:

With monday Agents, teams can build custom agents using prompts, and choose Claude as its model. The platform gives the agent a name, a face, and a place on the board where anyone can assign it work.

Bring Your Own Agent (BYOA) makes it possible for Claude Managed Agents to join the platform. Once on the monday platform, an agent one person has built can become a teammate the whole team can mention and assign work to.

Pre-built Agents, available in the monday Agents Store, turn Claude plugins into specialized teammates: a legal team can run a legal plugin as an agent inside its own workflows, and finance teams can do the same with theirs.

The Claude Coding integration enables teams to connect Claude in the monday dashboard, then plan and assign agents tasks. Claude Managed Agents executes in the customer's own environment, and results and updates land back on the ticket before the task hands off to the next agent or to a human for review. The work runs from business need to working code and back to the business user.

From brief to landing page without leaving the board

One end-to-end example: a marketing team runs a campaign production line inside a single board item. The marketer and content lead shape the brief on the item, aligning on goal, audience, key message, and channels. A Strategist Agent built with monday Agents turns that raw input into a structured brief covering the campaign objective, messaging pillars, channel breakdown, and success metrics.

From there, a Landing Page Builder takes over. Running on Claude Managed Agents in the company's own environment, it pulls the approved brief and generates a new variant of an existing landing page, with copy, structure, and messaging adapted to the campaign. The output lands back on the monday item automatically. Before the page reaches approval, a Brand Reviewer, a Claude Managed Agent, checks it against brand guidelines and legal standards and flags anything that needs human attention. The marketing manager then makes one decision: publish or refine.

A family business at the AI frontier

Cooke, a family seafood business founded in 1985 in Blacks Harbour, New Brunswick, has grown from a single farm site with 5,000 salmon into the world's largest family-owned seafood company, operating in 16 countries. Today, Cooke runs project delivery, resource management, and contract management on Claude and monday together. Product managers use Claude to turn approved charters and requirements into initial project plans, generate status reports, and surface risks and issues that feed straight into their monday RAID logs, across roughly 200 active and proposed projects. Claude automates the reporting and data prep that keep lifecycle workflows accurate across 130 contracts—upkeep work that used to be tedious and manual.

“Together, monday and Claude help us read team capacity and make smarter allocation calls,” says Patti Stevens, director of strategy at Cooke. “Monday used to be a platform we had to update. Now we operate from it.”

What monday.com learned

For companies planning a similar rebuild, monday’s team shares five lessons they learned as they transformed their platform into an AI-first product:

• The mental model is harder to change than the technology. People naturally want to protect quality and keep improving what already works. Moving teams from "how do we responsibly improve the current product?" to "how do we responsibly rebuild it for a different future?" took longer than the technical work.
• Small teams move faster when everything is changing at the same time. Direction, UX, technology, pricing, the trust model, and the company's own definition of good were all in motion at the same time. Layers of stakeholders would lose that much detail, but small teams with clear ownership and fast decision rights stayed close to it.
• Adoption depends on trust as much as it does on capability. Product-market fit depends on user confidence and preparedness to let agents into how work actually gets done. Governance, permissions, transparency, and reliability determine whether agents move beyond pilot programs and into production.
• Capability needs infrastructure to match. Agents perform at a different level when they're grounded in live project data, team history, and structured workflows, and at enterprise scale the backend has to hold. Alongside the agent layer, monday invested in monday DB so the data infrastructure could support the volume, speed, and complexity of agents operating across an organization.
• Build on what already works. monday has always described itself as the place where people team up to drive business outcomes, and the agent-first rebuild extends that promise to a new kind of team member. People still come to monday to achieve their goals, the difference is that some of the team members working alongside them are now agents.