News & Intel
LiveDaily AI-curated intelligence on Palantir Foundry, Ontology, AIP, Apollo, contracts, and community feedback. Updated automatically via GitHub Actions every day at 7 AM UTC.
Support for AI FDE to launch subagents with another model
At the moment, AI FDE doesn’t let you switch models when launching subagents. Concrete example: when building an OSDK React app, I’d like to do the research and design with Opus and produce a well-structured Epic with sprint notebooks — but I can’t then launch a subagent to implement Sprint 1 with Sonnet. Being able to choose the model per subagent would help a lot. It would keep token consumption (and cost) down for the implementation-heavy work, and it would remove the manual session switching that currently breaks the flow. 1 post - 1 participant Read full topic
Federation layer, Self-hosting of LLMs & Routing - More examples available?
Hello, I came across this interesting (but short) documentation regarding the implementation of a proxy or federation layer (I think mostly call model router outside the platform?). Bring your own model • Build a proxy or federation layer with AIP • Palantir While there is a tiny example mentioning the deployment of a container, additional documentation would be welcomed ? For example, we successfully deployed a 4B model asset as a container with vLLM engine but one thing we couldn’t do is to have the weights of the model loaded from a dataset ? Today, the weight are backed in the image. As no persistent storage is available, at every spin up we need to reload everything which takes around 5-10min while it would be better to have the model weights, CUDA graph etc.. stored in a dataset. This would allow: Lighter docker image Possibility of hot swap/sleep of model weights maybe GPU Release ? and more… Regarding the routing, where the router layer would be deployed
Elon Musk vs Michael Burry: World's richest man says AI internet traffic will outpace humans, market expert asks who is paying
Elon Musk says AI agentic traffic will eventually vastly exceed human internet usage, while Michael Burry questions who will pay for AI agents. The contrasting views highlight a broader debate over AI’s rapid expansion, massive infrastructure spending and whe…
On theCUBE Pod: Black Hat exposes agentic threat, theCUBE remembers David Floyer
Artificial intelligence systems are developing faster than cybersecurity experts — and the energy grid — can keep up with. At the recent Black Hat USA event, security analysts viewed the rise of AI-driven cyberattacks as a “sky is falling” threat, according t…
The Forrester Wave™: AI Platforms, Q3 2026 Is Live: Prepare To Recalibrate
The Forrester Wave™: AI Platforms, Q3 2026 has just published, and if you’ve read previous evaluations in this category, prepare to recalibrate. Agentic AI has redrawn the boundaries of what an AI platform is, what it must do, and what vendors compete to prov…
Palantir CEO drops 11-word bombshell for stock market investors
Software stocks have had a rough year. The fear driving them down is real: AI agents are getting good enough to automate tasks that enterprise software used to handle, and investors have been cutting valuations across the board. The debate has been running a…
Palantir CEO drops 11-word bombshell for stock market investors
Software stocks have had a rough year. The fear driving them down is real: AI agents are getting good enough to automate tasks that enterprise software used...
Palantir Surges 10%, UiPath Rises 7%, C3.ai Gains 5% as Agentic AI Stocks Rally Together
If you click 'Accept all', we and our partners, including 250 who are part of the IAB Transparency & Consent Framework, will also store and / or access information on a device (in other words, us… [+1046 chars]
Palantir Surges 10%, UiPath Rises 7%, C3.ai Gains 5% as Agentic AI Stocks Rally Together
The post Palantir Surges 10%, UiPath Rises 7%, C3.ai Gains 5% as Agentic AI Stocks Rally Together appeared first on 24/7 Wall St.. Agentic AI software names are moving together this Friday afternoon, and the leaderboard looks like a mirror image of Monday’s s…
Question about the layer between Ontology and action
Question about the layer between Ontology and action Palantir gives AI a governed representation of operational reality through the Ontology, then provides logic, models, agents, tools, actions, and Evals around that reality. What I’m trying to understand is whether Palantir has a general reasoning architecture that governs how the AI interprets that operational reality before deciding when and how to act , rather than leaving that reasoning largely to application-specific prompts, logic, tools, and evaluators. Put differently: is there a reusable layer that determines whether the system has identified the right problem, governing constraint, decision risk, and justified first move before intervention? I’m asking because I’ve developed a framework specifically for that layer and I’m trying to determine whether I’m identifying a genuine gap in the current architecture or simply missing something Palantir already has. Curious how people here would think about that.
Fractals documentation details request
In one of our internal demo meeting, Team walked through us the “Fractals” foundry capability , related to agents developments ( could sense it is more on agentic workflow development, agent configs, related ontology config, analysis on runs). Tried to see in documentation, but failed. Could anyone help me to route to the documentation. Would like to explore more on it. Thanks Attached the screen for reference: 1 post - 1 participant Read full topic
Palantir: I Am Raising My Price Target As AIP Momentum Accelerates
Summary - I reiterate my Buy on Palantir Technologies, raising the price target from $183 to $196 after robust Q2 2026 results. - PLTR's Q2 2026 revenue surged 93% y/y to $1.935 billion, with US revenue up 115% and management materially raising full-year guid…
Palantir Is Winning: Rapid AIP Adoption, Margin Expansion, Soaring FCF
Software analytics company Palantir (PLTR) had another record-breaking quarter in Q2'26, driven by accelerating adoption of its Foundry platforms and AIP, Palantir's Artificial Intelligence Platform. Because Palantir crushed top and bottom line estimates for …
Complete beginner looking for help getting started with the Ontology
Hi everyone, I’m brand new to Palantir Foundry and I’m starting from ground zero here. I’ve heard a lot about the Ontology and understand that it will help in some way to keep my data safe from models, but honestly I’m not sure where to begin. A few things I’m hoping you can help with: What exactly is the Ontology, in beginner-friendly terms? How does it help protect or govern my data when it comes to working with models/AIP? What’s the best first step or resource for someone learning this from scratch? I don’t have any prior experience, so any pointers, tutorials, docs, or advice on how to get oriented would be hugely appreciated. Thanks so much! 2 posts - 1 participant Read full topic
Presentation: Architecting AI Systems for the Messy Reality of Enterprises: Why Agentic Compute is the Missing Layer
Arun Joseph shares real-world insights on scaling enterprise agentic platforms like Deutsche Telekom’s LMOS. He discusses bridging organizational fault lines, replacing tool sprawl with core platform abstractions, and moving beyond basic chatbots to operation…
Show HN: Product analytics (and evals) for agent sessions on your MCP
HN Discussion — 2 comments · 40 points. Hi HN! We’re Theodore and Louis, founders of Armature (YC P26). We reconstruct the entire session behind the MCP tool calls you receive, including what the user asked their agent to do and what the agent thought.<p>You wrap your MCP in 3 lines of code (our SDK is available in Typescript, Python and
Enhance OSDK v2 Type Safety & Compile-Time Diagnostics for Ontology Property Mappings in Code Repositories
As a first-time poster in the Palantir Community, I would like to initiate a discussion around OSDK v2 TypeScript compilation and property binding experience in Code Repositories. While working on an AIP Chatbot Agent backed by TypeScript functions querying an Ontology Object Set ( UnnirInventoryBalance ), I encountered a subtle issue where an internal property mapping mismatch resulted in runtime zero-count/null returns rather than triggering compile-time diagnostics or highlighting errors in the Problems tab. Given Palantir Foundry’s unified “all-under-one-roof” architecture—where the Ontology, Code Repositories, and AIP Studio coexist within the same tenant—it would be immensely beneficial if the TypeScript compiler or static code analysis could flag display-name vs API-name mismatches or unmapped property keys directly during the build phase. Relying purely on runtime execution to uncover empty schema payloads can slow down debugging. I would love to hear how the community and pr
Issue: Pipeline Builder with LLM nodes — build fails but preview works
(topic deleted by author) 1 post - 1 participant Read full topic