It was a real honor to deliver the Opening Keynote at the Royal Society’s AI & Law Conference last week in London ! Thanks to all of the organizers and fellow speakers for this important dialogue regarding the future of our field. Link to Event Here:
https://t.co/JcfqrS866P
Most people, including really accomplished people, don't have an accurate mental model of how LLMs operate (and why would they?)
You see this in wide beliefs that AI is just copying from known sources, or that it only produces average answers, or that it can't generate new ideas
Different people will react differently to this, but I think it's great. If anyone can get high-quality answers to their individualized questions—as good as asking a professor of that subject—that can democratize learning in a really profound way.
Between 1985--2023, MIT's faculty grew 9%. Administrative staff grew 189%. 📈 Why? In new @PNASNews paper, we use dynamical system model to show administrative bloat can emerge without empire-building--just from well-intentioned problem-solving gone awry https://t.co/MZgGkxilZ2
One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.
The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.
The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.
However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.
Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.
What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.
[Original text: The Batch newsletter]
After many conversations over past year with friends, business associates & policymakers about the future of AI job disruption, I’ve tried to get my thoughts in order. With the caveat that I have no specific AI expertise, here they are. Comments and corrections encouraged.🧵
1/n
Ironclad Founder Jason Boehmig Joins @OpenAI
For Legal Vertical Launch
> #legaltech - on May 18 - Artificial Lawyer broke the news and got the scoop on the OpenAI legal launch.
> This site knew Jason was joining, but could not say so at the time.
https://t.co/u5fpRbb47d
People who don't follow cancer research often ask me why we haven't cured cancer. That perception masks a wonderful reality: We make amazing, stepwise progress every year, and the result is that many people live much longer today than they would have previously.
Right now we're in the thick of the annual meeting of the American Society of Clinical Oncology, the biggest research meeting on new cancer medicines, and this morning a bunch of really important studies dropped. I'm going to review them here.
This first image is the result for daraxonrasib, a treatment for pancreatic cancer that is generating consdirable excitement. The green line is the probability of living for patients who got the new drug; the gray one is the chemo control group.
If you follow cancer drugs, a chart like this will make your breath hitch a little. I'm going to review these and some other data here.
Anthropic now has a team dedicated to AI and the rule of law — and we've just opened our first role.
@AnthropicAI has studied what AI means for the economy. This team asks a different question: what will it mean for executive power, for courts and elections — and for the public deliberation that constitutional democracy ultimately rests on?
We're looking for someone with real depth in both AI and the law — a legal scholar, political scientist, or experienced government hand who can reason about frontier systems and the institutions they will affect.
If that's you, or someone you know: https://t.co/668HDz1lhf
This has quietly been a miracle month in medicine.
In the last 5 weeks we’ve got news on:
- retatrutide, the triple agonist GLP-1 from Lilly, basically melting fat and body-wide inflammation at record levels
- RevMed’s new pancreatic cancer drug showing unprecedented abilities to extend life
- small trial of a one-and-done PCSK9 gene editing therapy for slashing LDL cholesterol
- Mayo’s AI-assisted radiology showing vastly improved cancer detection
- this new therapy for metastatic solid tumors
This stuff is at varying levels of evidence. Retatrutide is ~100% on its way, other stuff needs more clinical trial data. But put it together and we’re maybe on the verge of majorly reducing the mortality of heart disease and cancer, the two leading causes of death in America.
Imagine replacing 90% of your employees with a team of geniuses who have no idea how your company operates.
Total chaos. Nothing works.
That’s what AI feels like today.
The missing piece is extracting all the domain knowledge from people’s heads and providing that as structured context to the models.
Davis Polk this week submitted $4.8 million in April-only billings to bankruptcy court overseeing Spirit Airlines case, including three 2nd yr associates charging $1,410/hr who together cost $725k:
https://t.co/YxyN9VN17A
You know what other tools know better than most instructors? Coursera and YouTube courses from top faculty, *the internet*, books from the library. How many students used those tools instead of formal ed? Very very few. How many will use Claude independently to learn the material? Probably the same amount.
I know it doesn’t sound glamorous, but the primary role of faculty is to get students in the seats and create incentives to actually absorb the information. This is your job. AI can help as a tool, I’ve seen some great harnesses of AI for education, but it will not do this.
Legal AI superempowers normal individuals with no legal background to fight big institutions in bureaucracies and in courts on a level knowledge/skill playing field, for the first time in human history. As such, it is one of the most inspiring applications of AI.
“AI is demoralizing.”
A Princeton Professor says he kept wondering this semester (while lecturing) if his students would be better off learning from Claude:
I had Opus 4.8 in Claude Code write a sophisticated, if minor, academic paper from a archive of hundreds of de-identified research files from years ago
I had to use GPT-5.5 Pro as a reviewer, it spotted one major error & some minor points. Opus corrected https://t.co/ELpzRJuXJ5
Fried Frank’s launch of a new AI-based fund formation tool is an example of an advantage law firms have over tech providers: decades of historical work product. https://t.co/GYcLggWhYG