Value Is Not Disappearing, It Is Relocating

Anthropic’s recent release did not look like a turning point on the surface. There was no theatrical keynote, no dramatic benchmark chart, no single moment designed to dominate the news cycle. It was a quiet product update that most people outside a narrow circle barely noticed. And yet, within a day, public software companies lost hundreds of billions of dollars in market value.

That kind of reaction does not come from surprise. It comes from recognition. It is the same kind of recognition that hits an industry when it realizes a long standing assumption has quietly expired. Like film companies not noticing that digital cameras were good enough (see: Why Bold Companies Eat Their Own Lunch to Win Big), or taxi fleets not noticing that smartphones could coordinate drivers better than dispatch radios, the shock was not about novelty. It was about inevitability.

The Market Reaction Was About Replacement, Not Intelligence

For years, the question hanging over AI was whether it would ever be capable enough to matter in real work. Investors debated hallucinations, reliability, and edge cases. What changed this time was not a leap in intelligence, but a shift in responsibility.

Markets understand replacement better than they understand technology. When spreadsheets replaced ledgers, nobody worried about whether spreadsheets were elegant. They worried about what happened to bookkeeping jobs. The same logic applied here. Once software can take responsibility for outcomes rather than suggestions, entire categories of tools start to look redundant.

The sell off was not a vote against software demand. It was a vote against software whose only role was to stand between a human and an action.

The Interface Was the Product Until It Wasn’t

For most of the SaaS era, the interface was where value lived. The best products won not because they did more work, but because they made work easier to manage. They turned messy processes into clean screens and replaced tribal knowledge with repeatable flows.

Think about early CRM systems. Their breakthrough was not automation. It was visibility. Managers could finally see pipelines. Reps could finally remember follow ups. The interface did the coordinating, and humans did the executing. That division of labor worked for decades.

But it depended entirely on humans being the bottleneck. Once that bottleneck loosens, the interface loses its monopoly on value.

Execution Is Moving Out of Human Hands

What made Anthropic’s release different was not conversational quality. It was agency. Software that can log in, navigate systems, and complete tasks without waiting for instruction changes where work actually happens.

This is similar to what happened in manufacturing when machines stopped assisting workers and started running entire production lines. At first, control panels mattered more than machines. Over time, the machines became autonomous, and the panels faded into the background.

In many workflows, the same thing is now happening. The interface becomes something you check occasionally rather than something you live inside all day. Execution migrates away from people and into systems.

When Work Decouples From Headcount, Pricing Breaks

Most SaaS pricing models assume that output scales with people. More employees means more seats, which means more revenue. This logic worked when adding capacity required hiring.

Autonomous systems break that relationship. A small team equipped with agents can now do work that once required entire departments. The output increases, but the seat count does not.

This is not hypothetical. Teams already talk openly about reducing software licenses because fewer humans need direct access. The software is still critical, but the pricing model no longer maps to value. When that happens, revenue compression is unavoidable.

Value Is Not Disappearing, It Is Relocating

The enterprise stack used to be tall and layered. Data lived at the bottom, interfaces sat on top, and humans acted as the connective tissue in between. Every action flowed upward through screens and downward through forms.

As agents begin to act directly on systems of record, those layers collapse toward each other. The middle gets thinner because fewer interactions need translation.

This is similar to what happened in finance when electronic trading replaced phone based brokers. The market did not disappear. It became faster, flatter, and less tolerant of intermediaries who added no unique value.

It is tempting to see falling valuations and assume destruction. In reality, capital is moving to where leverage now lives. Spending on AI infrastructure, deployment, and operational tooling is accelerating, not slowing.

History shows this pattern repeatedly. When electricity replaced steam, money flowed away from mechanical expertise and toward distribution and control. When cloud computing replaced on premise servers, value moved from hardware ownership to platform orchestration.

The same relocation is happening now. The market is not shrinking. It is reweighting.

Data Becomes More Valuable When Software Can Act

When humans are the final decision makers, bad data is frustrating. When software acts autonomously, bad data is dangerous. Errors no longer stop at confusion. They turn into actions.

This is why systems of record gain importance rather than lose it. The database that everyone trusts becomes the foundation every agent depends on. If it is wrong, everything built on top of it is wrong faster. In this environment, owning clean and authoritative data is not just a technical advantage. It is a strategic one.

And, as autonomy increases, so does the need for oversight. Companies cannot deploy agents at scale without knowing what they did, when they did it, and whether they were allowed to.

This mirrors the evolution of financial systems. As transactions became automated, auditing, logging, and compliance became entire industries. Nobody brags about their accounting controls, but nobody operates without them.

The same pattern is emerging around AI. Governance becomes infrastructure, not decoration.

Software Starts Getting Priced Like Labor

When software replaces labor directly, customers naturally compare it to labor. They ask what it produces, not how many people touch it.

This changes how products need to be sold. Pricing tied to outcomes forces clarity. It rewards systems that can reliably deliver results and exposes those that rely on vague utility. The shift is uncomfortable for some companies, but it aligns incentives in a way that usage based pricing never fully did.

This also leads to the importance of Forward Deployed Engineers (see: Why Forward-Deployed Engineers Matter) as there is a persistent myth that better tools reduce the need for services. In practice, the opposite happens. When tools become more powerful, organizations attempt more ambitious changes.

Anyone who has lived through a major ERP or cloud migration understands this. The software is only part of the work. Integrating it into real processes, real data, and real incentives is where complexity lives.

As AI systems move into core operations, that complexity grows. Services expand to meet it.

The Real Risk Is Sitting in the Middle

The most fragile position today is not building software. It is building software that exists mainly to translate information for humans without owning execution or truth.  That middle layer is being squeezed by systems that act and systems that anchor reality. Products in between must either evolve or accept shrinking influence.

The irony is that many of the products driving this change are still sold as subscriptions. SaaS as a delivery mechanism remains intact. What is ending is the shortcut where a clean interface and a familiar workflow were enough to sustain long term value. That path is closing. What replaces it is harder but more durable. Software that executes outcomes. Software that owns data. Software that enforces trust.

The era of easy software is ending. The era of software that actually does the work is beginning.