Ben Lackey

SpaceX's anticipated IPO will be one of a kind, and not just for the valuation. There are a few unknowns which make this spectacle one to watch, and @WSJ just shined a big light on it using our data. 🧵 wsj.com/finance/invest…

Build Agentic GraphRAG on Vertex AI! This community article shows the construction of an agentic GraphRAG system. Unlike vector search, which finds semantically similar text, GraphRAG navigates structured relationships to solve complex queries → goo.gle/4cyNzab

This is a close second.

Winner for favorite comment today.

It is now 2026. github.com/neo4j-partners…

I rarely create EC2 machines by hand. I'm doing it right now and was pleasantly surprised to see it now defaults to the sane approach of allowing SSH.

Hey @sas, I work for Neo4j who has offices in Malmo. But I live in Seattle. I was really excited for you new SEA->CPH route. However it looks like it's not flying Oct 27-Oct 30 when I need it. One tiny data point of more demand... portseattle.org/news/nostalgic…

Read about the saga of the Bayside Trails in Tacoma, WA here! baysidetrails.org

@TreppWire I really enjoyed this. A lot of cycle ideas overlap with Dalios new book. I’d be curious your thoughts on it. Maybe you could even get him on someday… he’s doing a lot of media appearances.

🎙️ Episode 342 is out! We talk about Fed independence under fire, private credit stepping up as traditional lenders pull back, and the office special servicing rate hitting its all-time high at 16.38%. We explore office distress through Manhattan's 5 Bryant Park refinancing challenges and a Washington DC government building's value reduction, while highlighting green shoots with Nvidia's potential 100,000 square foot Austin lease. We also cover Starwood's $2.2 billion acquisition of Brookfield's net lease platform and close with multifamily transactions across Brooklyn, Washington DC, and Minneapolis. Tune in: hubs.li/Q03xMH8X0

It's been a while since I've coded against a well known API (rather than some obscure janky pre release thing). Chat GPT really helped here --

The language support for the Facebook API is not what I expected. Javascript it is, I guess? Writing PHP today doesn't feel like the way to go.

Seamlessly integrate @neo4j graph databases for advanced RAG and semantic search with the Neo4J plugin for Genkit 🚀 This plugin empowers devs to unlock deeper context to build smarter applications. Learn how to get started → goo.gle/42WPAGS

Check out this post on Nextdoor: nextdoor.com/p/SsGrYQQTMsK5…

Yes, we did shut down Salesforce a year ago, as we have many SaaS providers—an internal estimate is about 1,200 SaaS shut down. No, I don't think it is the end of Salesforce; might be the opposite. Here is what actually happened and how/why we originally intended to NOT share it publicly: At Klarna, we decided early to explore the potential of AI and LLMs—mostly ChatGPT—while being open to testing all things that seemed to be trending. We encouraged all employees to do so and allowed them to pursue ideas organically rather than following "management direction" on exactly what they should be building. In the early days of ChatGPT, we heard a lot: "this tool allows you to feed all your PDFs, all your data sources to a LLM!" However, the old universal truth of data scientists still holds true, even in AI: "shit in, shit out." Feeding an LLM the fractioned, fragmented, and dispersed world of corporate data will result in a very confused LLM. We started instead exploring a few key concepts: What of our data was actually valuable? What data was duplicative, incorrect, or contradicting? Why was it like that? While people nowadays can criticize things like Wikipedia, we also reflected on the fact that it is a remarkable achievement—having over 20,000 people collaborate on the largest graph of knowledge that is still fundamentally of high quality, accessibility, and accuracy. What could we learn from this? A Swedish company, @neo4j, and @emileifrem introduced us to the beautiful world of graphs. We further explored data modeling, ontology, and, of course, vectors, RAGs, and many things. Key to our explorations became the conclusion that the utilization of SaaS to store all forms of knowledge of what Klarna is, why it exists (docs), what it tries to accomplish (slides, tickets, kanban boards), how it is doing (sheets, analytics), who is it dealing with (CRM, supplier management), who works here (ERP, HR) and what it has learnt was fragmented over these SaaS—most of them having their own ideas and concepts and creating an unnavigable web of knowledge that required a tremendous amount of Klarna specific expertise to operate and utilize. We also recognized that enterprise software has a standard set of features that are vital for it to operate—features such as audit, versioning, access and edit management, and similar universal needs. We need them as well, but that fragmentation again adds friction, admin overhead, and more. So, we decided to start consolidating; to put things together, connect our knowledge, and remove the silos. The side consequence of this was the liquidation of SaaS—not all of them, but a lot of them. And not for the license fees, even though those savings have been nice, but for the unification and standardisation of our knowledge and data. So no, we did not replace SaaS with an LLM, and storing CRM data in an LLM would have its limitations. But we developed an internal tech stack, using Neo4j and other things, to start bringing data=knowledge together. Ultimately, we found this very interesting, but more importantly starting seeing serious productivity gains. We allowed our internal AI to use this knowledge, and we realised with the help of @cursor_ai we could quickly deploy new interfaces and interactions with it. So, I discussed with one of my board members: should we share this publicly? We decided not to. We hold no grudge against SaaS (not true—I hate some of it, but won't tell you which one). But we are a payments company and a neo bank, there is limited value for us to share this externally. However, Klarna, being a bank, holds quarterly calls with its investors, and in passing on of these calls, I mentioned that we had removed some SaaS software including Salesforce. It turns out that the recording was leaked to @SeekingAlpha, and they put out a news post about it. And from there, it went crazy. Suddenly, @Benioff was asked on stage why Klarna was leaving Salesforce. I was tremendously embarrassed. So, to summarise, what does this mean? Will all companies do what Klarna does? I doubt it. On the contrary, much more likely is that we will see fewer SaaS consolidate the market, and they will do what we do and offer it to others. Those are likely to be your next SaaS. And it is very likely that Salesforce will be one of those companies. As highlighted many times, they do so much more than CRM today and hence have the opportunity to become that hub of knowledge that modern companies will seek. But there are also risks for them and others; a lot of our large enterprise SaaS providers suffers from a fallacy. They started as companies with a clear opinion of how to do things, but over time, as they try to satisfy every whim of any random person working at any large enterprise, they become somewhat of a glorified database and lose their opinion. Opinionated software is worth something, as opinions represent an experience of what works, what produces results. And this is the ultimate value. So I hope with sharing this we can clarify a lot of speculation and misunderstandings and in the end same thing as is always true, just like when mobile came along, we talked about mobile first, now you need to be AI first. Of course all SaaS companies will need to learn adopt and evolve. But if they do there is tremendous opportunity ahead.

@DOGE @DOGE_USDA @DOGE_SSA Apparently the DOD operates a ski area. That seems pretty wild. westpoint.armymwr.com/programs/victo…

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I really don't get Google killing their domain and website builder business. There was so much value in a turn key solution with Workspace.

@aronchick I’m in the other camp… Where would you put a person on the frontier? My guess is on the other side. My calorie requirements are a bit lower than racks of hardware. If you believe that, then I’m running some more efficient algorithm. Am I missing something?

Wow, I called it. A year later they introduced the timed entry system because of overcrowding.

The sadness about not being able to get up to Paradise during the holiday weekdays just hit me. The park service is keeping the road closed this year, so there goes one ski/snowshoe spot... Then they're going to claim it's overcrowded...

What's really going on in machine learning? Just finished a deep dive using (new) minimal models. Seems like ML is basically about fitting together lumps of computational irreducibility ... with important potential implications for science of ML, and future tech... writings.stephenwolfram.com/2024/08/whats-…