The smartest, best-resourced people in the world hold completely incompatible views about where AI is going.

While we don’t know who is right, we are seeing signals that the investment world is growing impatient.

We break down the six camps, the four axes of disagreement, and what the pullback in AI capital means for where you should be focused right now.

There is something every transactional lawyer does when they read a contract that has never needed a name. They do not read it from start to finish. They navigate it — following cross-references, holding defined terms in memory, assembling the legal logic from its pieces. We call this unfurling.

The document looks like text, so the industry built systems for text. Nobody replicated the unfurling. The AI retrieves. The lawyer still has to read. This is causing Gen AI platforms to hit a ceiling.

The legal AI market is full of tools built on LLM inference. Syntheia has always done things differently — and we are making a change in February 2026.

This post explains what, why, and how we will be building going forward.

We are separating our offering into three clear product lines — SuperComparer.com, FundCurator.com, and Syntheia.io as the one data infrastructure layer underneath all of them.

Every generation of disruption has its comfort myth.

For AI and professional labour, that myth is Jevons' Paradox. We use this as a counter-argument to AI displacement — cheaper services will unlock more demand for lawyers!

The problem is that argument only holds if AI stays bad enough to need lawyers. It isn't going to.

A group of prominent mathematicians just tried to settle the debate: are LLMs intelligent, or just fancy autocomplete?

They presented AI with ten research problems that have never appeared on the internet, then asked AI to solve them.

The results reveal something about what AI can and can't do — and what that means for the 99% of legal work that doesn't involve inventing something novel.

Those who worked in legal tech and law firms would remember that before 2023, law firms held a strict line for procurement — no software can be purchased if it operated with anything less than 100% accuracy. Yet, in the last few years, every firm and their dog has been jumping onto the Gen AI bandwagon, a technology that is well known to perform at significantly less than 100% accuracy.

Why? What changed? Is this acceptance of risk by law firms permanent or temporary? And, what does the adoption of AI mean for the practice of law?

The vibe coding revolution is upon us!

We are seeing posts on LinkedIn every other day about lawyers who have vibe coded solutions.

The age of AI is changing everything!

But, is this really going to change everything? Maybe for some people, but unlikely for large firms and enterprise legal teams.

In the 90s, many law firms bought expensive PCs to decorate the desks of partners. These PCs sat idle, gathering dust as literal “shelf-ware”. Today, there are many firms who have bought enterprise wide licenses to generative AI tools that are also under-utilized. In this blog piece, we ask the question of how we can solve this, and what lessons we can learn from the PC experience in the 90s.

As the market continues to accelerate in the widespread adoption of generative AI tools, a gap is beginning to emerge. Legal work can be produced at great speed by AI, but AI slop is tainting otherwise accurate and correct legal advice. This it the gap we want to close.

How do we build tools that help human experts verifying legal work?

There is an elephant in every law firm’s board room right now. Very few people have any ideas about their “AI strategy”, because very few people are thinking about the strategy for their law firms. The spade of announcements about successful adoption and rollout of generalist AI tools is evidence supporting this lack of “AI strategy” at most firms.