Ross Hale

CEO @ Artium. Code/Surf/Dad

[Andrew Ng @AndrewYNg]

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]

[Ross Hale @rrrosss]

Ya know what’s great about TUIs? No ads. No popups. No surveys. No GDPR cookie tracker configuration. No cookies or tracking at all in fact.

[Aaron Levie @levie]

Whether it’s existing consulting firms, new ones that emerge, FDEs from agent vendors, or new internal agent engineering roles, the amount of work that is going to be created to implement agents in enterprises will exceed anything we imagine today.

The complexity of implementing agents in any existing organizations is very real. When I talk to large enterprises, as you move from a chat paradigm to agents that participate in meaningful workflows, there are a number of things they need to do.

First, you have to get agents to be able to talk to your data securely across your systems. In many cases, enterprises have decades of legacy infrastructure that contain the valuable context for AI agents. That’s going to take a ton of work to go modernize and move to systems that work well with agents.

Then, you need to ensure that you’ve implemented agents with the right access controls and entitlements, the right scopes to be safely used, and have ways of monitoring, logging, and securing the work that they do.

Next, you need to actually document the processes in the organization in a way that agents can utilize for doing the work. You also need to figure out what the new workflow looks like when agents and people are working together on a process, and who steps in where. Just replicating the old workflow will mute the gains. Oh and you likely need to create evals for your top new end-state processes.

Finally, you have to keep up with a rapidly changing set of best practices and architectural shifts happening in the agent space. While it’s fun for people to change their personal productivity tools on a dime, it’s 100X harder to do this in a business process. The speed of change is a blessing and a curse right now for anyone trying to keep a stable system design.

All of this means that individuals and companies that develop expertise on the above set of components (and more) are going to be needed to help organizations actually implement agents at scale. This is also the rationale for vertical AI agents right now that can go in deep on a business domain and help bring automation to it.

This is a huge opportunity right now whether you’re doing this internally or as an external business provider.

[Ross Hale @rrrosss]

@RichardSSutton Ironically I think a misunderstanding of The Bitter Lesson is why so many are pursuing pure scale of transformers instead of the meatier architecture you propose here.

[Ross Hale @rrrosss]

Feels so Cyberpunk to be running a purveyor of fine, custom AIs. Come, see our wares, the most delicately crafted AIs built with care to your exacting standards of quality 🎩

[Ross Hale @rrrosss]

It is trivial to have your cake and eat it too: simply acquire two cakes.

[Ross Hale @rrrosss]

The UX paradigm where I open an app, see something in the feed I’m interested in, then the feed refreshes and said interesting thing vanishes into oblivion… needs to die. Where have all the good designers gone?

[Ross Hale @rrrosss]

@swyx If chat were the ultimate interface, all videogames would be MUDs

[Ross Hale @rrrosss]

@dhh I’m right there with you. Our palisades home did burn down, unfortunately, so for now we’ve taken our 3 kids and moved to Santa Barbara. It feels like both relief and running away in defeat. Glad to hear you’re safe

[Naval @naval]

AI won’t replace programmers, but rather make it easier for programmers to replace everyone else.

[Ross Hale @rrrosss]

@farbood Farb! I’m into it — where do I find the instructions?

[Ross Hale @rrrosss]

I find myself suggesting these three Paul Graham essays on writing often these days. “Writing, Briefly”, “Write Simply”, and “Write Like You Talk”

https://t.co/JO3wVUoIFl
https://t.co/VWVo9M9e3B
https://t.co/Z5JpLMfJHR

[Ross Hale @rrrosss]

@farbood The ability to make much more progress on areas of specific research. Imagine 100s of years of continuous effort at the pinnacle vs the handful people get today (after onboarding all existing prior knowledge, making a few years of progress, then dying)

[Ross Hale @rrrosss]

Kubernetes is like yoga

[Drew McManus @drewmcmanus]

The end of hero culture: https://t.co/NdaAh5tdr1

[Ross Hale @rrrosss]

@awegro thanks man, happy new year!

[Ross Hale @rrrosss]

Building her first synth birthday morning! 👩🏻‍🔬👩🏻‍💻🎹 @mattetti @littleBits

[Ross Hale @rrrosss]

@littleidea we'll miss you here at the office. Got a new wetsuit for you when you visit!

[Ross Hale @rrrosss]

@dburkes @pivotal Lookin good Danny!

[John D. Cook @JohnDCook]

"No engineered structure is designed to be built and then neglected or ignored." -- Henry Petroski