Marketing Hype vs. Reality

Those who sell real estate services have rarely let the truth get in the way of a good story. Even before the promise of AI, it wasn't difficult to find marketing narratives that tested the boundaries of truth. Now, as the entire world braces for significant changes in how stuff gets done, the real estate industry is, once again, drawing the attention of those with designs on upending a business that has functioned the same way for decades.

From our vantage point, we welcome change. We've embraced powerful AI resources, like Claude, to streamline workflows and build and improve tools that previously may have required 3rd party software and/or were difficult to stand up. But for now, the markets are not agentic. Those looking to secure longer-term office solutions must still navigate a complex labyrinth of variables. Only a highly experienced and skilled tenant advisor can provide the strategy and resources necessary for optimal results. The best advisors draw on scaled resources like market research and deep market engagement, and they employ proprietary strategies to create market leverage.

For our part, we continue to lean heavily into the belief that the best office solutions reflect an upfront understanding of the nuanced interplay between key drivers, from budget to design to employee experience. You can't just wander into the market, start looking at buildings, and expect the best result.

Some new market entrants are selling the promise of better search, faster service, and avoidance of those pesky brokers that make everything unnecessarily complicated. These companies purport to offer one place to see all available space, making the process of leasing an office feel more like renting an Airbnb or searching for a home on Zillow. It's a tempting idea. The problem? There are many.

First, the premise of easy search is a fallacy. The limited supply one can find online reflects a small segment of total available supply and is often fraught with inaccurate information on availability, rental economics, and more. When you casually search for office space online, you are not seeing the full picture. The only way to conduct a thorough search is to first define your target objectives and then filter the entire available supply against those objectives.

Next, there is the problem of information. Startup and small real estate firms lack experience and depth in the markets. They're missing vital data. Their deficiencies run from lacking basic comps, to knowing which tenants are actively negotiating, to being unable to ascertain market trends, to failing to understand the capital market dynamics that shape how investors negotiate. Offers submitted by these advisors are typically weak and poorly crafted.

These advisors aren't really advisors at all. They're more like the concierge desk at your favorite hotel. They may describe their service as "free to you, the tenant." This disingenuous misrepresentation has been made by weak service providers for decades. The tenant broker fee is the same regardless of whether you use a highly qualified advisor or a fast-talking concierge. The "don't worry, we're free" narrative exists to distract you from asking what services you're actually getting for the fee.

To be fair, companies seeking office space are at least partially to blame for the emergence of these service-light models. Startup companies want an office market that functions like Airbnb. They want "AirOffice." For seed or Series A startups, this is understandable. They obtain funding and the first thing they want to do is hire and bring people together. But the markets are increasingly littered with bad real estate decisions.

It pays to do a little research before securing office space: understand how the process works and the role brokers play before jumping straight to identifying space options. The complexity of the market has not changed. Good outcomes are about more than pretty pictures. The information you need to make great decisions remains largely opaque, known only by those who are now and have long been deeply engaged in the markets. Be wary of the chasm between marketing hype and market reality - - - it’s where your lease shifts from asset to liability.

Starting at What, Not Where

Deciding where to lease office space can be unexpectedly challenging. Every decision variable eventually translates into economic value, either as a cost or a benefit. But the real challenge is what we call the search problem: companies often begin with “where” when they should begin with “what.”

Starting with what means bringing the right stakeholders together before the search begins. It means building consensus around the factors that drive value and clarifying what the company needs its office to accomplish.

Markets present options. Those options are all different. An occupier that starts touring space without a clear vision of the desired outcome oftenends up chasing one imperfect solution after another. Each option is abandoned when the team discovers it fails to meet a need they had not fully considered. One common example is when the people leading the search are not closely aligned with the financial considerations that matter most to the executive team.

The quality of a lease solution ultimately reflects how well it addresses the full spectrum of variables that define value, with each variable weighted appropriately.

Before you think about where, spend time defining what.

Put the right team in place, including finance and human resources. Study location drivers like employee commute patterns. Discuss the budget, not only annual rent expense but also the capital required to transact. Evaluate the time needed to execute the project correctly. Consider how different space solutions and designs may affect employee engagement, recruiting, and brand.

Bring in a real estate advisor early. The best tenant advisors guide companies through a thoughtful process that produces a specific target outcome, matched to a realistic timeline.

A strong “what” should include the target market, the type of space, the type of building, the project timeline, and the project budget. It may also reveal that certain objectives need to be adjusted because they are not realistically actionable. That is something you want to learn before going to market, not after.

Once your what is fully defined and tested, you’re ready for where.

The "Gretzky Market"

Three forces have converged to create upward pressure on San Francisco office rents. Yes, you read that correctly: upward pressure.

First, solvent landlords with a reasonable cost basis and stable capital stack are ignoring the headline statistics. They know the market vacancy rate exceeds 30%. They don’t care.  They don’t have to. Vacancy is heavily concentrated in distressed and lower-quality assets, while leasing activity remains focused on a much narrower segment of available supply. Conditions in one segment of the market do not necessarily dictate outcomes in another.

Second, sophisticated data analytics are changing how landlords price space.  By segmenting demand and supply with far greater precision and providing real-time visibility into market activity, these tools allow landlords to make increasingly strategic pricing decisions. As discussed in last week's article on dynamic pricing, owners are no longer relying solely on historical lease comparables to establish value.

Third, and perhaps most important because it involves human behavior and compensation, we are hearing anecdotal reports that leasing and capital markets teams are entering a phase of the cycle where winning assignments increasingly depends on telling owners what they want to hear rather than applying conservative underwriting assumptions. Once this dynamic takes hold, it tends to reinforce itself as competitors begin marketing some version of "market-plus" pricing to secure new business.

When these three forces come together, landlord rent expectations can begin to detach from what can reasonably be viewed as current market value.

I call this a "Gretzky Market."

Wayne Gretzky famously said, "I skate to where the puck is going to be, not where it has been."

Today, landlords are beginning to ask occupiers to pay based on where they believe rents will be, not where they are now.

Dynamic Pricing Has Arrived in the Office Market

Landlords are increasingly using sophisticated, real-time data to determine how they price available office space. Historically, asking rents were established primarily through comparable lease transactions. The problem is that comparable lease data is inherently backward-looking. By the time a transaction becomes part of the market narrative, the economics were often negotiated months earlier. It was also difficult to precisely isolate the true competitive set for a particular space and understand the real-time dynamics within that subset of supply.

That is changing.

Today, institutional landlords can access highly detailed leasing intelligence through platforms like VTS, a software system widely used to track leasing activity across institutional office portfolios. Landlords require their leasing teams and brokers to report market activity into the platform, creating an expansive real-time dataset. Most major institutional owners now operate within this ecosystem.

More importantly, AI is beginning to transform that raw activity into strategic insight.

Landlords can now dissect the market at a micro level, segmenting supply by building quality, floor size, geography, tenant profile, availability timing, and competitive positioning. Instead of relying solely on completed lease transactions, they can analyze active negotiations and letter-of-intent pricing to understand where the market is moving in real time. In many cases, this provides a more accurate picture of current pricing pressure than signed leases.

The implications are significant.

We are beginning to see landlords make strategic pricing decisions based not simply on where the market was six months ago, but on where they believe it is heading. In some cases, owners may intentionally hold space off the market, allowing competing inventory to lease first so their remaining availability enters a tighter supply environment. Scarcity drives leverage, and leverage drives pricing.

This introduces a new level of complexity for occupiers.

Companies and their advisors must now understand the mechanics of dynamic pricing and the data influencing landlord behavior. Tenant advisors must possess the strategic capability to interpret the data and get ahead of how the landlord is using it to gain leverage in the negotiations.

Our long-held belief in  “selling our client’s tenancy,” as opposed to simply helping them “lease space”, has never been more relevant. Data may support a landlord’s pricing thesis, but not all demand carries equal value. The tenant willing to pay the highest rent is not always the tenant a landlord most wants over the long-term.

The Symmetry Problem

Markets reward those who possess superior information. In commercial real estate, landlords, lenders, brokers, contractors, and vendors operate with deep knowledge advantages that most tenants simply do not have. When companies lease office space, they enter an opaque market where bad information, incomplete information, or misunderstood information can cost millions of dollars. The companies that achieve the best outcomes are not necessarily the biggest or most sophisticated. They are the ones that close the information gap.

The first breakdown usually occurs in the hiring of a real estate advisor. When companies do not fully understand the leasing process, or the actual role of a tenant advisor, they evaluate brokers using the wrong criteria. They mistake access for strategy. They assume tenant representation begins and ends with showing available space. As a result, they often work with multiple brokers simultaneously, or worse, rely directly on the landlord’s broker to guide them through the process.

This creates immediate disadvantage.

Many companies believe more brokers means more options and therefore a better outcome. What they fail to understand is that finding “space” is easy. Finding the right space, aligned with business objectives, culture, growth plans, labor strategy, economics, operational efficiency, and negotiating leverage, is extraordinarily difficult.

Without a high-level tenant advisor, companies skip the most important part of the process: defining the optimal solution before entering the market. They begin touring space before they understand what they are actually trying to accomplish. Search becomes chaotic because the strategy never existed in the first place.

Compounding the problem is the compensation structure itself. Brokers are typically paid when transactions close, and in most cases, the fee is funded by the landlord. Many tenants never even ask how much their broker is being paid. They view the commission as a side arrangement between landlord and broker, something akin to a referral fee.

It is not.

The tenant pays for the fee through the rent stream. Every dollar originates from the economics of the lease. The moment companies begin thinking about brokerage compensation as though they are writing the check directly themselves, expectations change dramatically. They begin asking the right questions:

What strategic value is this advisor actually providing? What expertise are they bringing to the table?  How do the services correspond to the fee?  

Tenants suffer from asymmetrical information. Hiring the best tenant advisor is the single most important step a company can take to mitigate this issue.

More or Less?

Two truths are emerging in the San Francisco office market.

The first is surging demand for space from AI companies. It is increasingly clear that San Francisco is, and will remain, the epicenter of AI. The critical ecosystem has already been established. Talent, venture capital, strategic partnerships, M&A activity, research institutions, and universities are all concentrated here. And these companies are growing fast.

The nature of AI work, interdisciplinary, fast-paced, iterative, and highly confidential, tends to favor an in-office culture. Job growth in the AI sector has been robust. While difficult to measure precisely, estimates suggest AI-related employment in the San Francisco region has grown at an annual rate approaching 40% since 2022. AI demand has dominated the office market over the past two years and, at least for now, shows no signs of slowing.

The second truth is that AI is also causing layoffs.

We are already seeing an acceleration in workforce reductions tied directly to AI-driven productivity gains. Over the past year alone, the rapid development and deployment of agentic AI has begun reshaping how companies execute work, often reducing the need for human labor in the process.

How will this play out over time?

Our view is that the regional office market will increasingly divide into two distinct categories: high-performance assets and economically obsolete assets.

To be sure, this is already happening. Demand is concentrated in key clusters and focused heavily on higher-quality buildings. Companies, both AI firms and traditional occupiers, are competing for a much smaller pool of truly desirable space. As a result, premium rents are holding firm despite historically high overall vacancy.

In fact, today’s market often behaves less like a market with 30% vacancy and more like one with sub-10% vacancy, because so much of the inventory is effectively outside the competitive set.

Over time, if and as the desirable portion of the market fills, some demand will inevitably spill into secondary locations and lower-tier inventory. This has historically been part of the dynamic driving Oakland’s cyclical performance. San Francisco becomes too expensive, and some tenants move across the bay in search of value.

The question is not what happens if demand outpaces desirable supply. We know how that story ends.
The larger question is whether AI job creation will ultimately outpace AI-driven job loss.

Early indications are cause for caution.

We see potential disruption across a broad range of white-collar professions that currently fill San Francisco office buildings. Software engineering, legal services, finance, administrative support, consulting, and middle management all appear exposed to varying degrees of automation and workforce compression.

AI may prove to be the most significant economic change agent of modern times, perhaps unlike anything we have previously experienced.
For now, the answer remains uncertain.

Will AI ultimately create more jobs, or fewer?

Why I Read Every Word of the Lease

Leases are not a good read. They are long, often 60+ pages, and filled with sentences you have to read three times to fully understand. It is no surprise that many brokers pass the document straight to the attorney without comment. “I’m not a lawyer, I can’t give legal advice.” Fair enough.

But that misses something important.

While a lease contains legal concepts that absolutely require a strong attorney, its core purpose is to document the business deal. The terms negotiated in the letter of intent are not legal abstractions. They are business decisions. And ensuring those terms are carried through accurately is the broker’s responsibility.

No one is better positioned to do that.

Does it matter? It does. I routinely see lease language that subtly, and sometimes materially, erodes a tenant’s position.

I came across a good example this week.

My client is leasing second-generation space, previously built and largely usable as-is. The landlord is providing a tenant improvement allowance, but like most tenants in this situation, my client is not spending evenly across the entire premises. In their case, the bulk of the investment will be focused at the entrance of the space.

Spending tenant improvement funds on isolated areas of a second-generation space is common.

What was not normal is the language I found buried in Work Letter of the draft lease.   Here, I found a provision requiring the tenant improvement allowance to be spent evenly across the entire space. If the tenant concentrated improvements in only half the premises, for example, the landlord could reduce its contribution proportionally.

Same allowance. Very different outcome.

That kind of language rarely shows up in a letter of intent. It appears later, in the lease, where it is easy to miss if no one is looking for it.

This is why I read every word.

Tricky Markets

The trajectory of rental economics varies dramatically by market. In St. Louis, for example, historical rents show relatively little movement over time. The market is largely flat. In San Francisco, the opposite is true. Rental values have swung by 50% or more in both directions across cycles.

San Francisco is a boom-and-bust market. Tethered to the tech sector, it responds quickly and often violently to the cycles of the innovation economy. For owners, this demands a forward-looking mindset. Values that fall sharply have a tendency to rebound just as quickly. Locking into long-term economics at the bottom of a cycle can prove costly.

We are in that kind of moment now. Landlords are weighing whether to transact today at current market levels with a stable, long-term occupier or hold out for improved pricing in a recovery. Among higher-quality assets, there are early signs of hesitation, even regret, around deals struck at today’s terms.

This is when markets become difficult. The best landlords stay disciplined and honor their commitments. Others don’t. We are already seeing instances of owners attempting to re-trade previously agreed terms. Every landlord has the right to set pricing. But once a tenant commits at that level, the terms should hold. Moving the goal posts undermines trust and introduces unnecessary risk into the process.

Critical Steps in Managing the Cost of Designing and Constructing Office Space

Tenants who fail to rigorously assess design and construction costs before signing a lease expose themselves to budget overruns and difficult decisions under schedule pressure. These decisions are often reactive and suboptimal. This dynamic is the result of poor planning and is highly avoidable.

A great tenant advisor adds value in many ways, but one of the most important is assembling the right team at the right time. For tenants pursuing long-term leases with custom-built space, that team must include both an architect and a general contractor.

Experienced brokers can provide an early cost framework to help establish a realistic budget before a space is selected or designed. This is an essential first step, but it is only a starting point.

Architects and designers are creative by nature. Their initial designs often exceed budget. That is not a flaw, it is part of the process. The next step is cost engineering, where the design team and contractor work together to align the vision with the budget while preserving key elements of the design. This is a disciplined and highly collaborative exercise.

Having the right team is not enough. They must be engaged in a way that aligns with the tenant’s objectives. In most cases, this means bringing on a general contractor early under a “GC and Fee” structure. Under this approach, the contractor is retained for a fixed fee covering general conditions and overhead, rather than being selected later through a lump sum bid.

Early engagement creates accountability and improves cost visibility. It also reduces the risk of change orders, which are a primary driver of budget overruns. The goal is to enter the final bidding phase with a fully developed set of construction drawings and a well-vetted cost.

At that stage, the general contractor runs a competitive bid process across all sub-trades. With this level of preparation, tenants significantly increase the likelihood of delivering their space on budget and on schedule.

Making Room for What's Next

Here in the early days of 2026, information economy workers could be forgiven for abandoning their fight over remote work. After all, squabbling about where work is done when your job is not secure seems a bit like rearranging the deck chairs on the Titanic.

This got me thinking about how we sometimes don’t appreciate what we have until it’s gone. During and after the pandemic, information economy workers enjoyed a moment when it seemed they could demand more from their employers. Many seized the opportunity to redefine where (and sometimes when) they work. With a tight labor market, employers, nervous about losing staff, begrudgingly met such demands. But that’s no longer the case. Especially in the tech sector, where companies seem more focused on firing than hiring.

It seems clear that advancements in AI achieved over the past year have created the real possibility of significant changes in how work is done in the information economy. Indeed, recent layoffs seem to confirm that such changes are already underway. It’s time for affected workers to make room for what’s next. To do so requires an adaptive mindset, one that seeks a way to participate in, not run from, the increasing presence of AI in the workplace.

Why You Shouldn't Be Paying the AI Startup Rate

The San Francisco office market is white hot. Demand is at a record high. Huge AI companies like OpenAI and Anthropic grab headlines when they take down entire buildings. But it’s the steady surge of smaller startups that pushes demand to its current highs.  

38% of the leases completed in Q1 2026 were with AI companies. At the top end, these companies are competing for large blocks (such as Anthropic’s lease of all of 300 Howard Street), a market that is increasingly scarce.  At the low end, series A and B startups are scrambling to secure well-located, pre-built (even furnished) spaces they can lease immediately. Speed is a key driver. They will pay a premium for occupancy-ready space.

Both ends of the AI demand spectrum present risk to the landlord.  Many of these companies end up paying a risk premium.  The rents they pay define the market.  Beneath the surface, landlords are aware of the risk. Even OpenAI, the largest AI tenant in San Francisco, is high risk due to its massive compute spend, which requires it to continue raising large rounds of funding.

Your profitable, stable company presents a decidedly different risk profile to the landlord. You should not be paying the risk premium. We’re beginning to see landlords favor stability. After all, this is San Francisco. The market has a long history of boom-and-bust tied to tech demand. The key is to negotiate from a position of strength, aligning your occupancy with stability. Let the guys with 12 months of burn pay the premium.

Landlord as Bank: The Hidden Cost of "Convenient" TI Financing

The cost to build office space is at an all-time high, forcing companies to make deliberate decisions about how tenant improvements are funded. These decisions directly impact cash, balance sheet, and EBITDA—and should not be left solely to the real estate team.

For companies where valuation matters, structure matters. A business preparing for a sale, for example, may choose to fund all or a portion of the improvements with cash to preserve EBITDA, given valuation is often tied to an EBITDA multiple.

Sometimes when there is a shortfall between the tenant improvement allowance a landlord has offered as a concession to the lease and the total cost to build the space, the landlord will offer to finance the difference.

At first glance, this may appear to be an efficient solution. But the details matter.

If structured as a true loan—separate from the lease—the tenant can capitalize the improvements, record debt, and keep rent lower. This is typically more favorable from an EBITDA perspective.

But most landlords aren’t truly interested in acting as a lender. Their real motivation is to optimize for asset value.

They do so by embedding the additional funding into the lease as rent. This step makes the cost of the financing more expensive to the tenant while turbo-charging the value it creates for the landlord. How? By adding the loan value to rent, it becomes subject to the annual rent escalations common in most leases (typically 3%), further compounding the cost of the loan. Most importantly, the increased rent drives higher net operating income, which directly increases the landlord’s asset value upon sale.

Tenants must carefully assess the implications of landlord offers to finance additional tenant improvements, as the proposed structures often carry hidden costs.

Why Non-Tech Companies Need More Time to Lease Office Space in San Francisco

At roughly 86 million square feet, the San Francisco office market is not particularly large. When you break it down by submarkets, building class, or premium view space, it becomes even smaller. With approximately 8 million square feet of active demand, much of it concentrated in the best submarkets and best buildings, the leasing environment can become challenging for companies that want to make thoughtful, well-informed decisions.

Technology companies, especially AI firms, represent the largest share of that demand. But San Francisco is home to many companies outside the tech sector. These businesses must often operate in a market shaped by the behavior of fast-moving technology tenants.

That dynamic creates friction.

Tech companies frequently move faster and are often willing to pay more to secure the right space. Historically they have absorbed space quickly and sometimes with less sensitivity to deal terms. It is not that terms do not matter to them. Their priorities are simply different. In the technology economy, speed often determines the winners. Companies race to scale and investors continue to provide enormous capital to the firms they believe will get there first.

For more mature, non-tech businesses, this can make the leasing process difficult. Space they carefully evaluate can disappear overnight when a technology company decides to move faster or pay more.

So what should these companies do?

Allow more time for the leasing process.

Time creates flexibility. It allows companies to evaluate options thoroughly, negotiate with multiple landlords, and pivot when opportunities disappear. When tenants lose space to faster-moving competitors, the real problem is rarely the leasing strategy. The problem is usually a lack of time to recover and pursue alternatives.

Starting early does not mean starting blindly. Begin too early and the process can lose momentum. But if companies are going to make a mistake on timing, it is far better to err on the side of starting too early rather than too late.

Because in San Francisco’s office market, time is not just part of the leasing process.

It is often the single greatest source of negotiating leverage an occupier has.

Block’s Layoffs: Validating the Citrini Thesis, or Solving for Gross Mismanagement?

Last week, Jack Dorsey, CEO of Block, Inc., announced the company is laying off a whopping 40% of its workforce, more than 4,000 employees. Coming on the heels of the Citrini Memo, it is difficult not to at least consider the parallels between Block’s actions and the fictional scenarios portrayed therein. Indeed, Dorsey’s commentary on the matter reads as if taken directly from Citrini’s dystopian narrative:

“The core thesis is simple. Intelligence tools have changed what it means to build and run a company. I don’t think we’re early to this realization. I think most companies are late. Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes.”

In the aftermath of this announcement, a number of people, including former Block employees, have argued the layoffs are really about eliminating corporate bloat. AI, they suggest, is simply a convenient narrative that creates better optics by making the company appear to be getting ahead of a meaningful trend, rather than correcting for poor management decisions that resulted in massive overhiring.

I have questions.

If Dorsey’s stated case for the layoffs is valid, does this not align squarely (pun intended) with Citrini’s doomsday scenario? Alternatively, if this is really about correcting corporate bloat, how did Block management get so far off track as to add 40% more employees than necessary to run the company effectively?

To be sure, Dorsey makes clear that “gross profit more than doubled from the first quarter to the fourth quarter of 2025.” He goes on to write, “We believe this financial performance is just beginning to reflect the product development velocity improvements we drove this year.”

Is it possible Block generated $2.87 billion in profit while carrying $235 million in excess labor spend? Or is it more plausible that AI has already automated workflows that previously required large teams, making certain roles expendable?

The answer may lie somewhere in the middle. Yes, Block likely over hired. And yes, AI may now be enabling the company to automate work previously done by humans.

Either way, we will all be watching closely for signs that Dorsey’s prediction proves correct: that “the majority of companies will reach the same conclusion and make similar structural changes.”

One thing is certain. If AI-driven workforce reductions approach anything close to the scale of Block’s recent layoffs, and if similar levels of job elimination become commonplace, we should all be concerned.

A Wild Ride

Speculation about the economic impact of AI is everywhere. From economists to technologists to the barista at your local coffee shop, everyone has an opinion about what the future holds. Just this week we saw two sharply contrasting perspectives: one from Alap Shah and Citrini Research projecting widespread job loss and severe economic fallout, and another from Citadel pushing back on the logic behind the Citrini thesis.

Few technologies have generated this level of speculation and fear. Even Citrini’s admittedly fictional portrayal of the next two years had an immediate, very real impact on markets, sending stocks sharply lower. Forecasts about a future in which AI reaches its full potential swing wildly from dystopian to utopian. Investors do not know what to believe.

Take Nvidia. Imagine Jensen Huang huddled with his executive team before an earnings call: “Great work, everyone. With this historic performance, the stock should respond positively.” And then it drops 9 percent. The numbers are strong, yet the reaction is negative. That is not about earnings. It is about nerves. Investors want to believe in an AI-driven future, but the doomsday narrative is hard to ignore. What if the pessimists are right?

Uncertainty is the defining theme of this moment. That likely makes it one of the most opportunistic periods in modern economic history. It is a time when a bold bet could generate enormous gains or painful losses. There appears to be little middle ground. The stakes feel binary.

My view is that the future sits well above most of our pay grades, certainly mine. Most of us are too far removed from the underlying data and too unfamiliar with the technical architecture to see what the builders see. We experience AI through consumer outcomes, which are undeniably impressive and advancing quickly. More recently, we have begun hearing about agentic systems and breakthroughs from tools like Claude and Moltbot. Yet for all the progress, AI adoption in everyday life has not fully crossed into game-changing territory.

This is a wild ride. Buckle up. The future feels more uncertain than at any point I can remember.

Defining Work and Life

Companies have long sought to enhance employee productivity by reducing daily friction. This friction arises both in the execution of work itself and in the activities tangential to work such as commuting, eating, childcare, and laundry. Interestingly, medieval economies in Europe were organized around self-sufficient manors where life and work were inseparable. Similar models existed throughout the world, including in China and the Middle East. For most of human history, working was living.

That began to change in the nineteenth century. As new modes of transportation were adopted, including rail and later the automobile, white-collar workers gained the ability to live farther from where they worked. The expansion of highways accelerated this trend and gave rise to the modern commuter suburb. At the same time, advances in technology and economic systems raised living standards and created more discretionary time outside of work. Work and life began to evolve as distinct concepts. As that separation took hold, people increasingly perceived friction when work encroached on life.

In more recent decades, ambitious employers have sought to maximize employee engagement by reducing the tangential friction surrounding work. The technology sector has led this effort, developing campus environments where employees can address daily needs on site, from healthcare and childcare to meals and laundry.

The pandemic temporarily disrupted this trajectory, creating the largest separation between work and life ever experienced at scale. Today, however, the AI sector is once again redefining the relationship. With enormous stakes and a rapid pace of change, many AI companies are promoting an intense work culture, often embracing a 996 model in which employees work from 9 a.m. to 9 p.m., six days per week. Such a commitment leaves little room for life outside work and is incompatible with long commutes. It is therefore unsurprising to see some AI companies renting apartments to provide employees with housing close to the workplace.

These are unusual times. On one hand, many are experiencing a profound imbalance in which work dominates life. On the other, AI holds the promise of replacing labor at scale, potentially creating more free time than humanity has ever known. How this tension resolves is difficult to predict. For now, as we race toward an uncertain future, many are experiencing life as work once again, echoing patterns from long ago.

Rising Tide Not Lifting All Boats

AI companies are leasing office space in San Francisco at an accelerating pace. Demand spans the spectrum, from Series A startups to Anthropic, which recently signed a lease for just under 500,000 square feet. Yet the market remains deeply bifurcated. The best buildings are seeing real competition. Commodity assets are not.

This creates an existential question for owners of smaller buildings that lack views, scale, or high-end amenities: how do you stay relevant?

There are two viable paths.

The first is to lean into AI, but with discipline. Owners of commodity buildings should not expect to win mature AI tenants. That ship has sailed. The opportunity lies earlier. Early-stage startups struggle to find space that is move-in ready, flexible, and available on short terms. That segment is underserved. It carries more risk and higher churn, but it also delivers faster velocity and higher revenue per lease. Buildings that solve this problem can remain competitive by embracing flexibility rather than fighting it.

The second path is to zig while the market zags. Ignore AI entirely. Position the building as a refuge for tenants being priced out of a tech-dominated market. This strategy works best for Tier 3 assets with a low cost basis. The advantage is price. By leasing at a meaningful discount, these owners can capture demand from companies shut out of Tier 1 and Tier 2 buildings. The key is focus. Compete on affordability, not amenities you cannot credibly deliver.

The takeaway is simple. AI is not lifting all boats. It is widening the gap. Owners who understand which side of that divide they’re on, and act accordingly, can still differentiate their offering and achieve leasing success.

What Lies Ahead

It’s hard not to witness the rapid emergence of AI in the workplace without pondering our near future. Technology has long served as both catalyst and accelerant in shaping how we work. But the major catalysts of prior eras, things like the train, the telephone, and even the internet, took years to deliver change at scale.

With the recent introduction of Clawdbot, now Moltbot, people are beginning to experience the next iteration of AI beyond LLMs and vibe coding. We are starting to see how an AI agent can be deployed to do many of the things we do, only faster and better. While technologists have been working on AI for decades, advancements over the past several years have been swift. Indeed, the average information economy worker is barely keeping pace. Many still think AI is simply about better search. Frankly, search is AI’s least interesting and least impactful application.

I remember the many ways the internet crept into my life, both personal and professional. It did not feel like there was a single game-changing moment. Instead, there was a steady progression until one day it was everywhere. To be sure, it displaced workers and reshaped entire industries, think Amazon and bookstores. But I never recall thinking, “Wow, this is going to change everything.”

I think we could be in such a moment now. A moment when we can barely wrap our heads around what lies ahead. It is one thing to contemplate the next decade of my own career. But what about my young children? What will work look like for them? I have yet to hear anyone offer a coherent explanation. Instead, I read provocative comments from people like Elon Musk suggesting that people should forget about saving for retirement because it will not be necessary. Others suggest that large percentages of the work we do will soon be done by AI. And then what?

The LLMs felt like a meaningful advancement, but not a true game changer. While I have not yet been able to use Moltbot, I have read reports from those who have. Many are breathless and genuinely blown away by its effectiveness. Just this past week, publicly traded software companies saw their stocks hammered in reaction to agents like Moltbot. Maybe that response is reasonable. After all, why would we continue to buy one-size-fits-all software that is expensive and exposes us to variables outside our control, when an AI agent could build a custom solution that we own and control?

I do not know what lies ahead. But I do know one thing. It will not be boring.

San Francisco Office Is Hot (Again)

It can be confusing to understand the leasing dynamic in a city like San Francisco. The data suggests a market in which occupiers should enjoy outsized leverage. Vacancy remains north of 30%, after all. Yet many companies are surprised to encounter real competition for space and rental rates at or near all-time highs. How can both be true?

The answer lies in how that vacancy is distributed. Excess vacancy is concentrated in assets that are either fundamentally inferior or burdened by a distressed capital stack. Occupiers are largely bypassing inferior buildings as they focus on higher-quality environments to support a return to the office. At the same time, buildings with broken capital stacks often cannot transact at market terms, rendering them largely irrelevant to active tenants. As a result, effective vacancy for quality space is far lower than headline figures suggest. In the Class A premium segment, vacancy is closer to 5%.

As more companies work to bring employees back, a new narrative is emerging. The office must be well designed, well located, and rich in amenities. Employers recognize the friction inherent in return-to-office initiatives and want to get it right. Increasingly, they are willing to pay more for space that delivers a compelling experience. This same logic explains why several large-scale office developments are actively pursuing tenants with plans to build in the near term.

Leasing volume reached historic highs in 2025, and anecdotal evidence from early 2026 points to another year of strong demand.The “generational” leverage tenants enjoyed from 2022 through 2024 has largely evaporated. We expect tenant leverage to continue eroding in cases where occupiers are competing for high-quality space.

A New Product

Office space is a product. In the US, that product has been offered and consumed in largely the same way for decades. That is beginning to change.

Investors are exploring more creative ways to monetize office space. One example is the speculative construction and furnishing of space that can be leased on more flexible terms than those traditionally offered, including short-term leases of less than three years. Tenants like this approach and are often willing to pay a premium to avoid the friction inherent in the traditional leasing process. That friction includes the need to design, build, and furnish space, along with the long-term commitments required to support business needs that are constantly evolving.

Beyond changes to the physical product, landlords are also rethinking pricing. Historically, office leases have required tenants to pay a base rent plus their pro rata share of operating expenses. Those expenses are structured in different ways, such as full-service leases with a base year, NNN leases, or variations in between. Regardless of structure, the outcome is the same: fixed rent paired with variable costs, making total occupancy expense difficult to predict.

Some landlords are now simplifying this model by collapsing base rent and operating expenses into a single, fixed rent. While this rent typically increases annually by a defined measure, it is otherwise predictable and easy for tenants to understand and budget.

There is meaningful demand for office space that is occupancy-ready, offered on flexible terms, and priced with clarity. Thoughtful investors will begin carving out portions of their buildings for these offerings. While this space cannot be monetized in the same way as traditional long-term leases, over comparable time horizons it can generate significantly higher cash flow through premium rents and stronger residual value that reduces downtime between occupancies.