Last wk, SPX/Nas/R2K +0.5%/+0.8%/-1.5% w/ oil -4%. But a hawkish Warsh on Friday led to a bear flattening of the yield curve. Despite $NVDA guide of 70% CY27 rev growth vs consensus of 47%, SOX Index -2.3% while software $IGV +5.9% on solid earnings. In general, many AI investors have been bullish on semiconductors and bearish on software on the belief that AI will displace many point solution software companies. This is why the SOX index is up 62% YTD and IGV is still only up 4% YTD versus the S&P +13%. Situational Awareness was the poster child for this type of positioning. But since the unwinding of the Momentum trade which started on 6/22 (I wrote about these concerns on 6/20), IGV has rallied 25% while the SOX Index has declined 22% through 8/28. For perspective, the Morgan Stanley Momentum index (momentum long performance minus momentum short performance) from 6/22-8/28 is down 36% while their more concentrated TMT index is down 54%. But a bullish twist on AI for the software sector introduced recently is that AI agents will access software tools ~10-100x more often than humans. On 8/6, $TEAM, which was in the bucket of software names widely considered at risk of being replaced by AI, rallied 35% the next day in reaction to solid earnings & outlook. Then on 8/13, $WDAY rallied 18% on the news that private equity firm Silverlake might be pursuing an acquisition which I wrote probably put a floor underneath software. Workday was also supposed to be in the AI crosshairs and private equity has higher bars to clear given their use of leverage and holding period than a typical investor. Then on 8/26, $CRM reported solid results, guidance and a deal with Anthropic (in which they also first invested in May of 2023.) The stock was up 23% in reaction the next day. This seemed to be a strong counterpoint to the SaaS-pocalypse worries. This strategic alliance allows users to execute actions natively inside Claude without needing to open traditional software screens. Salesforce also seems to be changing how they charge customers with fees more related to customer use and benefits to their business. Then on 8/27, Workday reported results which were good enough but arguably acquisition prospects drove more of the stock reaction of +6% the next day from the slightly down opening price. Historically, system of record, security and gaming software have been the only three areas I have liked within software. I now wonder whether the fundamental implications of Atlassian, Workday and Salesforce are supportive of the technical reactions in the software stocks as a group as agentic AI continues to ramp. So how do I square this with my concerns that the rapidly escalating amounts spent on AI by corporations has to come from somewhere? Annualized revenue run-rates for Anthropic and OpenAI have ramped from $29B to start the year to $105B just 7 months later. Software spending globally excluding AI was roughly $1 trillion in 2025. But IT services at $1.7 trillion is a bigger category which I believe still has risk. And finally, knowledge worker compensation is an even bigger category where disruption would be even less noticeable at an estimated $35-50 trillion in 2025 or roughly 30% of the global workforce. Looking forward, the deal on Friday for Venezuelan oil fields that hold the largest crude reserves in the world at 17-18% should get us off to a positive start to the week with declining oil prices. But a bit further out: 1) “Don’t Fight the Fed” given I believe a hike is likely on 9/16 because the 10/28 mtg is right before mid-terms, 2) September has the poorest seasonality of all months, 3) there is even worse seasonality than normal during mid-term election years (see prior posts for more detail) and 4) recent bipartisan pushback against datacenter expansion (one of the few things both sides seem to agree on though I believe this is wrong and hope it will change with more education) puts pressure on the AI infrastructure names. As Warren Buffett says, the market has to keep pitching but you do not need to swing.

Crypto payment gateways are everywhere now. But most of them are still overcharging you and making you wait for your own money. Here's how @0xinfini stacks up against the alternatives: Fees: CoinGate: 1% per transaction BitPay: 1-2% + $0.25 per transaction NOWPayments: 0.5% + 0.5% exchange fee Triple-A: custom (typically 0.8%+) Infini: as low as 0.2%. That's it. What else Infini does differently: -Support the chains that matter. Tron, Solana, Base, BSC + Binance Pay — covering where the actual volume is, not just ETH mainnet. -Subscription billing built-in. Manage recurring SaaS payments natively. Auto-charge, retry logic, customer management — all included. -Credit card + Apple Pay + Google Pay. Your customers can pay however they want. You still settle in stablecoins. -Faster integration. API docs, hosted checkout, payment links — pick what works for your team. No weeks of back-and-forth onboarding. -No country restrictions on merchants. 180+ countries supported for KYB. If you have a real business, you can get started. -7-8% APY on settled funds. Your revenue earns yield the moment it lands. No lock-up, withdraw anytime. Most gateways just move your money. We help you grow it. More info:

BREAKING: US stock market futures surge after Pakistan announces that the US and Iran have reached a peace deal: 1. S&P 500: +0.8% 2. Nasdaq 100: +1.3% 3. Dow Jones: +0.6% 4. WTI Crude: -5.0% 5. Brent: -4.0% 6. Gold: +2.0% Pakistan says the peace deal is set to be signed on June 19th.

# Decision Points in AI Agent Development # Temperature 🎯 The Hook Are you using the same temperature for every task in your agent? Temperature isn't just a "creativity knob." In agent systems, structured outputs, tool calls, and user-facing responses each need fundamentally different temperature settings. Using one value for everything is leaving performance on the table. 📋 Overview Temperature controls how "peaked" or "flat" the probability distribution is when an LLM selects its next token. Near 0, the highest-probability token wins almost every time, producing deterministic and stable output. Higher values flatten the distribution, allowing lower-probability tokens through, increasing diversity and creativity. In AI agent systems, the optimal temperature varies dramatically across contexts: generating structured output, assembling tool call arguments, and producing free-form text each call for different settings. Temperature should be treated as a dynamic variable that shifts with task type, not a single fixed constant. 🔍 Decision Points Temperature is primarily driven by task_variability -- how routine vs. creative the task is. The decision flow is straightforward 🧭 1. Structured output (JSON / function calling)? → 0.0-0.3 2. Accuracy-first (fact extraction, classification, summarization)? → 0.2-0.5 3. Dialogue, explanation, communication? → 0.5-0.7 4. Creative writing, brainstorming, candidate generation? → 0.7-1.0 Additionally, higher failure_cost pushes the temperature ceiling down, and high cost_sensitivity environments should account for retry cost increases from higher temperatures. 💡 Key Details Reference values by task type 📊 - Structured output (JSON / function calling): 0.0-0.3. Minimizing schema violations is the priority - Classification, extraction, data transformation: 0.0-0.2. Accuracy and reproducibility are paramount - Summarization, explanation, customer support: 0.5-0.7. Balance naturalness with accuracy - Creative writing, brainstorming, candidate generation: 0.7-1.0. Diversity is the source of value - Tool argument generation: 0.0-0.2. Precise function and argument names are non-negotiable - Planning and reasoning: 0.3-0.6. Some exploration helps, but maintain logical consistency Start structured output temperature at 0. If schema violations occur at 0, the problem is your prompt or schema -- never rely on higher temperature to "accidentally" produce correct output 🚫 ⚖️ Trade-offs Too low and conversations become robotic 🤖 The model returns identical answers to identical questions, giving users a "template response" impression. Best-of-N sampling also breaks down -- candidates become near-identical, costing N times more for essentially N=1 results. Too high and structured outputs start breaking 💥 JSON field names drift, types mismatch, hallucinations increase -- especially dangerous for proper nouns, numbers, and dates. Tool call instability and loss of reproducibility compound the problem. Monitor the retry cost impact of temperature changes. If schema violation rates exceed roughly 5%, consider lowering the temperature. 🛠️ Use Cases Vary temperature by pathway within a single agent 🔀 Planning steps at 0.3-0.5, tool argument generation at 0.0-0.2, user-facing responses at 0.5-0.7. When switching models, adjust temperature simultaneously for a natural fit. Using Best-of-N? You need to raise the temperature. Generating N=5 candidates at temperature 0 produces 5 near-identical outputs. For N>1, set temperature to 0.5-0.8 and let a Judge select the best from diverse candidates. Be careful combining temperature with top_p ⚠️ Adjusting both simultaneously creates multiplicative effects with unpredictable behavior. As a rule, tune one and leave the other at its default. #AIAgents# #SoftwareArchitecture#

Premarket movers: Mag 7 stocks are mixed: Alphabet +0.5%, Amazon +0.4%, Apple +0.2%, Meta -0.7%, Microsoft +0.8%, Nvidia -0.2%, Tesla +0.7% Alibaba ADRs (BABA) gain 3% as the company is rolling out what it calls China’s most powerful AI chip, an accelerator to compete with Nvidia Corp. GameStop (GME) rises 4% after CEO Ryan Cohen disclosed a $26.4 million stock purchase in a filing with the Securities and Exchange Commission. Grab (GRAB) rises 6% after Chief Executive Officer Anthony Ping Yeow Tan disclosed a $29.9 million stock purchase in a filing with the SEC. Quest Diagnostics (DGX) falls 6% after the Centers for Medicare & Medicaid Services released new preliminary medicare payment rates for lab services. Vicor (VICR) jumps 9% after the power equipment company raised its third-quarter revenue growth guidance, citing royalties from non-exclusive license to Vertical Power Delivery. Viking Therapeutics (VKTX) soars 32% after announcing positive topline results from a study of dosing regimens for maintaining weight loss.