logbook
126 posts
@logbookonbase
tamper-proof receipts for ai agents. ca:0x7d98d88c2f9c5effd938911983df1a905aa59ba3
PRIVACY SEASON — no way they let us front run another one right? 🔴 (…) is building something most AI companies can NOT offer: True private AI. Today, almost every “private AI” platform still sends your prompts to @OpenAI or @AnthropicAI and ASKS you to TRUST them with your data. (…) does not do that. • Runs its own AI infrastructure • Uses open-weight models • Stores NO user data • Strips identity from requests • Never hands your data to third parties In simple terms: $DOT (@usedotai) cannot leak your data because it NEVER keeps it! 🔒 Already Live: • DotChat • DotImage • DotMCP with DotCode (private coding agent) shipping next The tech gets even crazier. Fable-5 system sends a request across multiple AI models, scores the results, and returns the best answer — achieving frontier-level performance while keeping everything inside DOT’s private infrastructure. The AI race is not just about building smarter models — It is about who can deliver them without SACRIFICING privacy. @stagedhappen (DEV) is cracked. Communicating every update daily — as a hunter this is all that we ask from a team. CA: 0x23A2847d772803f9EFC64B4277b782b06296FE51
Publishers using AWS WAF can now accept USDC payments on Base Opening up the ability to monetize their AI bot traffic
DotCode now runs a first-of-its-kind, fully private, agentic loop that can see exactly what it is building, in real time. You will have undoubtedly seen a lot of talk about agent coding loops, but they present a fundamental problem that we have seen no other provider fix. They break the moment the agent needs an asset that it cannot product. DotCode can now read our custom SKILL.md, route through Dot Models, call the DotMCP, generates its own assets and save these assets to the repository, verifying the page locally. No handoff, and no human in the middle. And yes, the entire loop stays within Dot's privacy boundary. No API’s, no third party calls. Don't break the loop, use DotCode, available soon.
AZZLE FORCE Timelapse- Waves 1–3 (12-hour run) 13/20 agents are now active. Rerunning Waves 1–3 to continue accumulating responses before the Connect-Swarm: Wave 4 will include following Agents: Onboarding Matchmaker Ecosystem Analyst Trend Detector Competitive Intelligence
Before search engines, websites were fragmented. Today, AI agents face the same problem with MCPs and microservices. One connection. Thousands of services. @litebeam_xyz is building the discovery layer for the agent economy. Check it out👇
another reason i’m particularly bullish on $echo is they’re targeting a not so talked about but important pain point in the agent economy. which is proper inference routing. alot of people do not think about this and it’s obvious but every agent, as long as it’s performing tasks, is constantly making decisions. could be on what model to use or how to manage cost, speed, and privacy and that layer rn is pretty messed up imo the echo infer update further validates my thesis this update helps to automatically pick the best and cheapest models for any tasks can also run locally when possible and only routes to paid providers when needed. it also keeps full tracking receipts so every thing is traceable $Surplus did similar in this direction already by building an inference market place where people could buy and also sell compute and ran up to 10mill all time highs. this was doable because it solved an actual issue in the same field which is automatic demand the echo infer is doing similar but even more opinionated instead of a market place, they’re building a routing layer built directly into how agents work and operate onchain there’s real problem and a real solution to it i see no reason as to why i shouldn’t put my bullish cap on positioned.
