Just finished north of 200 meetings in Europe with customers and technologists. The conversations were primarily around AI, common questions include:
1. Are there examples of organizations who have been able to demonstrate production level systems and do those developments show a return in lower cost, efficiency or better top line?
2. What do you think about agents? How will we discover, govern and stop agents if need be. Perhaps the biggest security concern ATM.
3. The frontier AI models are expensive, what's the business case at these token prices to embed AI in our customer facing products? Where will token prices be in the future.
4. What are the longer term implications of Mythos like models? Do we need to update cyber infrastructure or all IT infrastructure?
5. What do you think of Chinese opensource models? Are they secure and what is the downside of using them if they can be secured and they are cheaper?
The parts that surprised me were:
1. The pausing of Mythos and Fable 5 caused more consternation and concern in Europe both short term and raised longer term concerns on single model reliance or reliance or models not in ones control. I hadn't seen it from their POV.
2. Sovereignity which was always a topic and still is, is getting more nuanced - they want data residency, data localization and local resources, but there seems to be more willingness to accept global services on clouds. Classified systems continue to be an issue.
Net net - we need to ensure we continue to build trust both on our Frontier models and their consistent availability, we need to get the right economics in place and spend more time in Europe communicating and building presence if we want AI adoption to keep pace with the US.
Vakar dažās stundās Fable 5 man uzprogrammēja veselu datorspēli C++ valodā. Spēle darbojas Windows, macOS, Linux un tvOS operetājsistēmās un izmanto attiecīgi Direct3D12, Metal un Vulkan. Diezgan iespaidīgi.
Šodien šis modelis ārpus ASV jau vairs nav pieejams😭
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]
Two weeks without mobile internet improved mental health more than antidepressants and reversed roughly 10 years of attentional decline.
Screen time dropped 49% (314 to 161 min/day).
Introducing React Doctor
Scan your React codebase for anti-patterns:
- Unnecessary useEffects
- Fix accessibility issues
- Prop drilling instead of context / composition
Run as a CLI or agent skill. Repeat until passing. Fully open source
I think more and more companies/startups will implement a Code Factory system like this.
Just point your agent at this agent with the prompt
"Read this and create a .md plan for migrating our codebase to a Code Factory model"
Europe cannot afford to stay a loose club of vetoes and hesitations. In Leuven, Belgium, Mario Draghi put it clearly: coordinating national interests is not the same as acting as one power. Where Europe has chosen federation – trade, competition, the single market – it is respected and heard. Where it has not – defence, foreign policy, industrial strategy – it is divided and vulnerable. A Union strong on trade but weak on security will always see its strengths used against it. Europe must choose: fragmented nations, or a real European power.
Once again I am leaving the Munich Security Conference in a low mood. Amongst all the noise, the US signalled their plans for Europe, so things are becoming clearer. But things are clearly not good.
This is what we now know, and what we now have to do about it:🧵1/17
Is this really all the EU has to show for?
Here 25 tangible achievements, improvements and benefits that happened because we have the European Union 👇🇪🇺