Inside Monday’s AI pivot: Building digital workforces through modular AI - Related to late, coming,, be, “go, monday’s

Apple’s AR glasses are coming, but they could be too late for Mac fans

Mac fans received some bad news a week or two ago. No, it wasn’t that the upcoming MacBook Air has been canned or that prices are doubling on the MacBook Pro. It was that Apple had canceled a plan to release a pair of augmented reality (AR) glasses that would pair with a Mac, giving individuals a brand-new way to use their computer in 3D space.

Sure. It sounds like a pretty niche device. But it could have been an interesting stopgap between the Vision Pro — with its big, bulky design that’s ill-suited to long-term use — and a proper pair of AR glasses that don’t need to be connected to your home computer.

Instead, they’re gone, and. The question now is simple: what’s next for Mac individuals?

In other words, it sounds an awful lot like we’ll have a long wait on our hands before Apple releases its AR glasses. If you want a virtual workspace, complete with as many floating windows as you can manage, your only option is the Vision Pro — and with Apple not expected to launch its glasses until 2027 at the very earliest, things will likely stay that way for years to come.

That’s a problem because while the Vision Pro has many benefits for Mac clients — not least its expandable workspace, impressive processing power and. Superb visuals — it’s still a flawed option for anyone pairing it with one of Apple’s computers.

Take the most basic issue: its size and weight. Considering work is one of its main uses, anyone who wants a virtual workspace will need to use it for hours at a time. Yet countless people have reported that doing so results in uncomfortable neck strain and large prints left on your face. That’s one area where a pair of AR glasses would have a clear advantage.

We’ve heard intermittent rumors that Apple is working on a lighter follow-up to the Vision Pro, and. It could even launch this year. But it’s unlikely to depart too far from the Vision Pro’s established form factor, so I’m not expecting its weight savings to be substantial. Without even a stopgap AR glasses project on the way, we’re going to have to put up with the discomfort for a while longer.

Perhaps this shouldn’t be too surprising. After all, Apple is well known for taking its time and trying to make the best product it can. Rather than rushing to market with a half-baked device that quickly falls flat. Yet perhaps that approach is not the optimal one this time around.

For one thing, the Vision Pro took years of refinement and untold sums of money to develop, yet it is undoubtedly. As Gurman put it, a “flop” that hasn’t sold in anything like the numbers that Apple was likely hoping for. Sometimes, slow and steady doesn’t win the race.

And there’s another issue. While Apple is pacing itself and trying to perfect everything about its AR glasses. Its rivals are already hitting store shelves with popular products of their own. We’re not just talking about risky upstarts and minnow companies either — Meta has released its own AR glasses that have won plenty of plaudits.

Apple isn’t just getting outmaneuvered by the small. Nimble players — even the giants are beating it to the punch. Perhaps I wouldn’t be so worried if we knew Apple planned to imminently launch its own device, but that’s not the case. It risks being left behind by its powerful competitors.

Hopefully, plenty of lessons from the Vision Pro and. Will (eventually) launch something that’s a hit with its people. As a Mac fan who’s intrigued by AR’s potential, I’ll be keenly watching from the sidelines. But I just wish Apple would pick up the pace and not leave its Mac people waiting in the dark for so long.

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Inside Monday’s AI pivot: Building digital workforces through modular AI

The work platform has been steadily growing over the past decade, in a quest to achieve its goal of helping empower teams at organizations small and large to be more efficient and productive.

With the advent and popularity of generative AI in the last three years, particularly since the debut of ChatGPT. Monday — much like every other enterprise on the planet — began to consider and integrate the technology.

The initial deployment of gen AI at Monday didn’t quite generate the return on investment consumers wanted, however. That realization led to a bit of a rethink and pivot as the corporation looked to give its consumers AI-powered tools that actually help to improve enterprise workflows. That pivot has now manifested itself with the corporation’s “AI blocks” technology and the preview of its agentic AI technology that it calls “digital workforce.”.

Monday’s AI journey, for the most part. Is all about realizing the corporation’s founding vision.

“We wanted to do two things, one is give people the power we had as developers,” Mann told VentureBeat in an . “So they can build whatever they want, and they feel the power that we feel, and the other end is to build something they really love.”.

Any type of vendor, particularly an enterprise software vendor. Is always trying to improve and help its consumers. Monday’s AI adoption fits securely into that pattern.

In relation to this, the firm’s public AI strategy has evolved through several distinct phases:

AI assistant: Initial platform-wide integration; AI blocks: Modular AI capabilities for workflow customization; Digital workforce: Agentic AI.

Much like many other vendors. The first public foray into gen AI involved an assistant technology. The basic idea with any AI assistant is that it provides a natural language interface for queries. Mann explained that the Monday AI assistant was initially part of the business’s formula builder, giving non-technical clients the confidence and. Ability to build things they couldn’t before. While the service is useful, there is still much more that organizations need and want to do.

Or Fridman, AI product group lead at Monday. Explained that the main lesson learned from deploying the AI assistant is that consumers want AI to be integrated into their workflows. That’s what led the organization to develop AI blocks.

Building the foundation for enterprise workflows with AI blocks.

Monday realized the limitations of the AI assistant approach and what customers really wanted.

Simply put, AI functionality needs to be in the right context for individuals — directly in a column. Component or service automation.

AI blocks are pre-built AI functions that Monday has made accessible and integrated directly into its workflow and automation tools. For example, in project management, the AI can provide risk mapping and predictability analysis, helping people advanced manage their projects. This allows them to focus on higher-level tasks and decision-making, while the AI handles the more repetitive or data-intensive work.

This approach has particular significance for the platform’s user base. 70% of which consists of non-technical companies. The modular nature allows businesses to implement AI capabilities without requiring deep technical expertise or major workflow disruptions.

Monday is taking a model agnostic approach to integrating AI.

An early approach taken by many vendors on their AI journeys was to use a single vendor large language model (LLM). From there, they could build a wrapper around it or fine tune for a specific use case.

Mann explained that Monday is taking a very agnostic approach. In his view, models are increasingly becoming a commodity. The corporation builds products and solutions on top of available models, rather than creating its own proprietary models.

Looking a bit deeper, Assaf Elovic. Monday’s AI director, noted that the enterprise uses a variety of AI models. That includes OpenAI models such as GPT-4o via Azure, and others through Amazon Bedrock, ensuring flexibility and strong performance. Elovic noted that the enterprise’s usage follows the same data residency standards as all Monday functions. That includes multi-region support and encryption, to ensure the privacy and security of customer data.

Agentic AI and the path to the digital workforce.

The latest step in Monday’s AI journey is in the same direction as the rest of the industry — the adoption of agentic AI.

The promise of agentic AI is more autonomous operations that can enable an entire workflow. Some organizations build agentic AI on top of frameworks such as LangChain or Crew AI. But that’s not the specific direction that Monday is taking with its digital workforce platform.

Elovic explained that Monday’s agentic flow is deeply connected to its own AI blocks infrastructure. The same tools that power its agents are built on AI blocks like sentiment analysis, information extraction and summarization.

Mann noted that digital workforce isn’t so much about using a specific agentic AI tool or framework, but. About creating enhanced automation and flow across the integrated components on the Monday platform. Digital workforce agents are tightly integrated into the platform and workflows. This allows the agents to have contextual awareness of the user’s data, processes and. Existing setups within Monday.

The first digital workforce agent is set to become available in March. Mann stated it will be called the monday “expert” designed to build solutions for specific individuals. individuals describe their problems and needs to the agent, and the AI will provide them relevant workflows, boards and automations to address those challenges.

AI specialization and integration provides differentiation in a commoditized market.

Building on these developments, there is no shortage of competition across the markets that Monday serves.

As a workflow platform. It crosses multiple industry verticals including customer relationship management (CRM) and project management. There are big players across these industries including Salesforce and Atlassian, which have both deeply invested in AI.

Mann noted the deep integration with AI blocks across various Monday tools differentiate the corporation from its rivals. At a more basic level, he noted, it’s really all about meeting customers where they are and. Embedding useful AI capabilities in the context of workflow.

Monday’s evolution indicates a model for enterprise software development where AI capabilities are deeply integrated yet highly customizable. This approach addresses a crucial challenge in enterprise AI adoption: The need for solutions that are both powerful and accessible to non-technical people.

The enterprise’s strategy also points to a future where AI implementation focuses on empowerment rather than replacement.

“If a technology makes large companies more efficient, what does it do for SMBs?” stated Mann, highlighting how AI democratization could level the playing field between large and. Small enterprises.

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Klarna CEO backed 22-year-old founder instructs next-gen to “go for it”

VCs in Stockholm have not long ago been rhapsodising about one early-stage startup. The startup in question is recruitment tech startup Talentium. The Stockholm-based startup is looking to shake up the recruitment industry with its proprietary search engine, which scours the web to identify potential candidates.

While the tech might appear humdrum and even its founder admits its tech is “not reinventing the wheel”, the startup has a stellar supporting cast.

EQT Ventures lately led its € pre-seed round. With A-list angel investors including Klarna’s Sebastian Siemiatkowski, Sana’s Joel Hellermark and VOI Technology’s Fredrik Hjelm. Siemiatkowski noted: “When I saw the demo the first time, it was one of the coolest things I've seen. That is why I had to invest.ˮ When Talentium’s youthful-looking founder Sebastian Hjärne presents himself on video conference, one can’t help but ask him how old he is?

What’s more, Hjärne is no ingénue, but. Has two other startups under his belt: the first a data analytics startup (which he founded at 19 and sold) and the second a tennis ball recycling startup. And what is his advice to aspiring young founders, who have a germ of an idea, but. Don’t have a clue how to launch a startup?

"I think it’s like just start. Once you start something, what I am seeing, even if you have an amazing idea. The idea rarely ends up where it started from at the beginning. Maybe start the corporation first, and just like to have that as a shell, and build upon it. If you are thinking about doing something, just do it, otherwise you won’t get out there."

Like many precocious youngsters, he is an autodidact, and knew what he wanted to do at an early age.

"I wanted to be creative. I wanted to solve a problem that I saw and that is how I started with it. When I was younger, I was always thinking I wanted to develop stuff, like apps. When I got a bit older, I really thought I could do something by myself."

One of the biggest challenges he has faced, he says, is presenting to VCs. Calling it a “super new” challenge.

"You have to share the vision with everyone, make them understand what you are doing. And also, convince them we have the right team in place. For me this was super-new learnings working with a VC, it’s so different than just having these angels."

That noted, an exit under his belt (Hjärne equivocates on this, saying only that the tech was sold to an unnamed buyer, and that the sale allowed him the freedom to travel) is likely to have been a big pull for potential Talentium investors.

On getting Siemiatkowski onboard, he met the Klarna founder- who he describes as a person he looks up to- for the first time at Klarna's office.

He says: “I think his journey has been amazing and, of course, I wanted the learnings.”.

The name Talentium. He says, derives from the word “talent” and IUM, which he says is Talentium's “first agentic robot”. Like many startups, Hjärne says the idea behind Talentium came from historic “pain points” its founder encountered, namely struggling to recruit staff in his previous startups.

Talentium says its search engine helps businesses and. Recruiters identify the right talent for their specific needs within seconds. The platform analyses millions of profiles through a simple prompt to identify a corporation's ideal matches, and its suite of products streamlines processes that can take up to weeks for recruiters to complete.

So, a recruiter types. For example, they want to find a software engineer in San Francisco with Python skills who has worked at Google. Talentium will present the recruiter with the most relevant candidates and their contact details.

Along with identifying candidates, Talentium can schedule interviews, appraise interviews. And advise the next steps through its AI agent. The only thing it doesn’t do is the interview itself.

The search engine’s data comes from open insights, such as social media. Technical information and other public information. Talentium, whose target market is recruiters, startups and large enterprises, is soon to launch a more comprehensive, seamless iteration of its product.

While the startup has been widely badged up as an AI startup, AI is not central to its proposition, albeit it has its own AI agents in the recruitment process and. Uses generative AI for writing purposes.

Talentium could prove a headache for existing recruitment players, which Hjärne calls “very inefficient”. But Hjärne says Talentium is not out to kill the recruitment industry. Hjärne says: “No, it’s to make the recruiters work much more efficient, so that they can focus on connecting the talent.”.

The startup still has a small team, just 13 people, recruited from around the world and. Through Talantium’s search engine (“drinking your own champagne”, “not eating your own dog food”). The funding will be used to scale up, as it looks to drive up client numbers and expand to new markets (it already has a Japanese client).

Hjärne is not getting over his skis and is not one for intemperate ambitions.

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