Jennifer's Tech World

Theres literally a site that Kalshi marketing uses to do nothing but make fake bet slips and markets. The only reason poly gets 'caught' is because you can actually verify Poly bets because of on chain transparency Kalshi lies and gets away with murer

Everyone crowning kalshi already is reading one wrong number Kalshi just printed a $22b valuation while polymarket sits near $9b, surface read says blowout, $17.9b may volume against $7.1b, 58% share versus 28%, clean knockout on paper Now look closer, polymarket pulled 678k real traders last month, kalshi managed roughly 85k, thats 8x the humans on a platform everyone keeps writing obituaries for Then the methodology trap, kalshi counts each contract by $1 face value, polymarket logs taker notional on price paid, swap rulers and that gap collapses fast And what flow chasers miss, kalshi rides world cup sports betting at 80% of its book, strip those ball games then the regulated event contract thesis thins out quick Kalshi won this volume headline, polymarket still holds its userbase, depth versus breadth is not one fight

inference is still so primitive every time we roll out a new model our providers go down (glm 5.2 right now) with the traffic gonna be a while before these things are as reliable as traditional infra

US becomes world’s top oil exporter as war on Iran disrupts rivals' supplies —— The US has emerged as the world's largest oil exporter, displacing long-time leaders Saudi Arabia and Russia and reshaping the global energy landscape. The development represents a remarkable turnaround for the US, which for decades relied heavily on West Asian crude. The US's energy transformation gained momentum after 2010, when production from shale oil and gas fields surged, first making the country the world's largest natural gas producer and later its biggest oil producer. Since February 2026, disruptions to Saudi oil exports caused by the UJS-Israeli war on Iran, combined with reduced Russian exports due to Ukrainian drone strikes and US sanctions, have helped propel the US to the top position among global oil exporters. According to ship-tracking data from Vortexa, US crude and fuel exports reached roughly 10.5 million barrels per day in May, supported by strong production and releases from strategic reserves. This marked the third consecutive month that the US ranked as the world's leading oil exporter.

$HOOD just did something no traditional brokerage has done. They shipped an MCP server that lets Claude, Cursor, or any AI agent execute real trades in an isolated account. Fidelity, Schwab, and Interactive Brokers are still making you click buttons. Robinhood built an API layer for AI agents and put it in production today. How it works: - Fund a dedicated isolated account - Connect your agent via Robinhood's MCP server - Agent builds portfolios, rebalances, spots opportunities - you get notifications and a kill switch The business model angle everyone's missing: this is a Gold feature. Agentic trading is a premium subscription driver, not a free tool. Every power user who wants this has to pay for Gold first. Vlad Tenev is turning AI into a monetization engine. The risk: "users bear full responsibility for any losses" is doing a lot of legal work in that press release. Autonomous AI trading at retail scale has never been tested in a real drawdown. The liability structure is untested. $HOOD up 208% over the past year. This launch is why the multiple holds - they keep shipping things incumbents aren't willing to build. Watch: whether agentic trading drives Gold subscriber growth in Q2. That's the revenue line to track.

Every AI agent today has the same problem. It forgets everything the moment the session ends. Your workflow. Your preferences. The fixes it learned yesterday. All gone. Hermes Agent is one of the first projects pushing in a completely different direction. Instead of treating AI like a temporary chat window, it treats it like a system that should: • remember • evolve • reuse experience • and improve over time That’s why developers are suddenly paying attention to it. The architecture behind it is genuinely interesting: • self-evolving skills • multi-layer memory • cross-session recall • autonomous agents running 24/7 • GEPA optimization loops • persistent personalities & workflows The result feels less like “using an AI tool” and more like building a long-term AI operator that compounds with usage. Made this infographic to simplify how the whole system actually works because this is easily one of the most interesting open-source AI agent projects right now.

I read Goldman Sachs’ AI report, and I was genuinely impressed. The core insight is as follows: Agentic AI could turn AI from a capex-heavy cost burden into a business where usage growth drives margin expansion. As token costs fall, more complex agents become economically viable. These agents then consume far more tokens through longer context windows, repeated reasoning loops, validation, tool use, and always-on background monitoring. This increase in token usage improves infrastructure utilization, strengthens unit economics, and gives hyperscalers and model providers more room to reinvest in model quality, distribution, and capacity. In other words, the bull case for AI capex is not simply that usage will grow. It is that this usage growth can increasingly flow through at attractive incremental margins. Goldman Sachs argues that this margin inflection is beginning to appear from 2026 onward.