u/ksraj1001

Over the last few months I built a few automations to remove the manual grind from my trading day. Sharing my morning routine in case it's useful, and I'd love to steal ideas from yours.

Before market open, my system auto-pulls:

• Overnight moves + gap scanners on my watchlist
• Key economic events for the day
• Yesterday's open positions + P&L carryforward
• Pre-set alerts on my key levels

On execution it logs entry/exit, size, and R automatically. At EOD it generates a one-page report — trades, P&L, mistakes tagged.

Two questions for the room:

1. What do you check every morning before the first trade that I might be missing?
2. What part of your day do you wish was automated but isn't?

EOD Report 02/07/2026 | Levels for 03/07/2026PCR 1.32 | VIX 12.29 (-7.21%)FII -311.82 Cr | DII +1,784.40 Cr

https://preview.redd.it/cro5ghipc7bh1.png?width=2168&format=png&auto=webp&s=53815928110e4115a7c73da766552d41fb710bb7

Daily summary

Lot dropped this week and there's a pretty clear through-line, so figured I'd pull it together.

Model releases:

- OpenAI launched GPT-5.6 (Sol/Terra/Luna). The bit worth noting isn't the flagship — it's Terra, reportedly matching GPT-5.5 quality at ~2x cheaper, with Luna aimed at the low-cost end.

- Google shipped Gemini 3.5 Flash (beats 3.1 Pro on several benchmarks), plus Nano Banana 2 Lite (images ~$0.034/1K-res) and Gemini Omni Flash (video ~$0.10/sec via API).

- xAI made Grok 3 GA and Grok 4.1 live for everyone. Grok 5 still hasn't shipped, which is its own story at this point.

Vertical / enterprise:

- Anthropic launched Claude Science for pharma and lab research. Separately, the US govt lifted the export restrictions on Fable 5 / Mythos 5 that it had imposed only weeks earlier.

- Mistral shipped OCR 4 (on-prem, structure-aware extraction) and is reportedly raising ~€3B at ~€20B.

Open source:

- Ollama crossed 52M monthly downloads, added `ollama launch` (one command to run coding agents on local or cloud models), and is now compatible with the Anthropic Messages API.

- Hugging Face: agents can train models via Hub skills now; Meta + HF also launched OpenEnv for agent environments.

Funding:

- Together AI raised $800M Series C (~$8.3B post). Crunchbase notes ~88% of 2026 AI funding went to US companies.

My take as someone building on top of these APIs:

The thing I keep noticing is that the price collapse is happening across every tier simultaneously, not just at the bottom. When the "balanced" model gets 2x cheaper each generation and the Flash tier beats last year's Pro, it gets really hard to build a business whose only edge is "we use the best model." That edge evaporates on someone else's release schedule.

The stuff that looked durable this week was all workflow-and-data — Claude Science, Mistral's on-prem OCR, Alibaba's agent ecosystem. Would genuinely like to hear how others here are handling multi-provider abstraction, because a surprise price or availability change shouldn't be able to wreck your margins overnight. And the frozen-then-unfrozen Anthropic thing means model availability is now a supply-chain risk, not a hypothetical.

Been algo trading on Indian markets for a while and got tired of the same problem everyone hits — your Pine Script fires a signal, and then you're glued to the screen waiting to actually place the order.

Built TraderOps to fix this. It's a Python/FastAPI server that:

1. Receives TradingView alerts as webhooks — you set the alert URL to your server endpoint, format the payload in Pine Script, and that's it. Signal fires → order goes out.
2. Connects to multiple Indian brokers — Zerodha (Kite), Zebu, AliceBlue, TradeJini, Kotak Neo, Motilal Oswal. Pick one or route across accounts.
3. Has an MCP server baked in — this is the part I'm most excited about. Using Claude's Model Context Protocol, I can literally type "buy 50 lots of NIFTY 24500 CE expiring Thursday" into Claude and it parses the intent, figures out the right broker API call, and executes. No JSON, no Swagger docs open in another tab.

The webhook path is the reliable production path. The MCP/Claude path is for when I want to manually intervene, adjust positions quickly, or just check "what's my open P&L on zebu right now" in plain English.

It's been running live with real money for a while now. Not paper trading.

A few things I learned building this:

• Every broker has a slightly different auth flow. Zerodha's TOTP + session token dance is well-documented. Some of the smaller ones... less so. Lots of reading SDK source code.
• TradingView's webhook body is just a plain text string by default — you have to structure your own JSON in the alert message using Pine variables like {{ticker}}, {{close}}, {{strategy.order.action}} etc.
• MCP is genuinely underrated for trading interfaces. I don't have to build a UI. Claude is the UI.

Happy to answer questions on the architecture or broker quirks. Anyone else doing multi-broker routing on Indian markets?

OpenAI's Custom Chip, Anthropic's Export Control, Chinese Models Going Global: What Actually Changed This Week in AI

Just parsed this week's AI news, and the narrative is clearer than anyone is saying: the industry is fragmenting into three geopolitical stacks, and the "global AI commons" is a myth.

Three Stories That Matter:

1. OpenAI's Jalapeño Chip (9-month ASIC development) — This signals vertical integration is now mandatory. If you only own one layer of the stack, you're vulnerable to someone integrating above or below you. Expect: Google, Meta, Anthropic to announce custom silicon within 12 months.
2. Anthropic $65B Private Valuation + Simultaneous Export Control — Anthropic overtook OpenAI in valuation (Series H; $47B run-rate revenue). Same week, US export-controlled Fable 5 and Mythos 5. Translation: frontier model access is now a geopolitical asset. Non-US enterprises are cut off. Alibaba simultaneously accused of stealing Claude. This is Cold War 2.0 for AI.
3. DeepSeek (Chinese) Now #1 Trending Model on Hugging Face — While Hugging Face IPO'd at $15B, Chinese models now dominate the trending charts. Open-source is no longer global; it's geopolitically split. US stack vs. China stack vs. EU stack.

My Take as Someone Building on Top of These APIs:

If you're building AI products in 2026, assume fragmentation. Don't build assuming a global open-source commons; it doesn't exist. Don't assume your favorite frontier model will remain accessible; export controls are real operational risks now.

The winners will be founders who:

• Build vertically (own multiple layers, not point solutions)
• Diversify model dependencies (don't bet everything on one geopolitical stack)
• Understand their ICP's geopolitical position (which government alignment helps them win?)
• Plan for regulatory overhead (export controls, data residency, compliance)

The industry didn't get more complex this week. It just stopped pretending to be global.

Sources:

• OpenAI + Broadcom Jalapeño announcement
• Anthropic's Series H valuation + US export control order
• Hugging Face IPO + Hugging Face trending models data
• Alibaba / Anthropic accusations

A few stories from the past week that, taken together, point to a real shift at the model layer rather than just incremental releases:

Meta and Llama. Multiple reports indicate Meta is stepping back from open-source Llama in favor of a proprietary program (internally referred to as "Muse Spark," with a new "Avocado" model) under Meta Superintelligence Labs. Llama crossed 650M+ downloads and was arguably the anchor of the open-weights ecosystem, so a pivot to closed development would be significant for anyone relying on that lineage.

Anthropic and export controls. Anthropic launched Claude Fable 5 on June 9 (Mythos-class, 1M-token context, always-on adaptive reasoning, notable security/vuln-finding capabilities). On June 12, a US export-control directive reportedly forced Anthropic to suspend access to Fable 5 and Mythos 5. Regardless of the specifics, it's a concrete example of frontier model availability being governed by policy, not just product decisions.

Apple and Google. At WWDC, Apple shipped its Siri overhaul with parts powered by a Gemini partnership. EU/China rollout is delayed on regulatory grounds.

Cost/commodity trend. Google cut Gemini Ultra from $250 to $200/mo and shipped 3.5 Flash; Alibaba's Qwen3.7-Plus is running at ~1/6 the per-token cost of its top tier; and open-weight models like Qwen 3.6 27B (reportedly 77.2% on SWE-bench, fits in 24GB) and Kimi K2.6 are increasingly viable for local/production use via Ollama (v0.30.8, June 12).

Platform agents. Google added Managed Agents to the Gemini API, Microsoft made Copilot Cowork GA plus "Autopilot" agents, and Anthropic shipped scheduled/cron agents in beta.

My take as someone building on top of these APIs: the two forces I'm watching are (1) frontier availability becoming a policy/geopolitics variable, and (2) the platforms absorbing the agent-orchestration layer that a lot of startups were building. Practically, that pushes me toward provider abstraction and keeping an open-weight fallback wired up, rather than hard-coupling to any single closed model. Curious whether others here are actually maintaining open-weight fallbacks in production, or if that's still mostly theoretical for most teams.

We're looking for a UX/UI design intern to join us full-time, in-person in Bengaluru.

What you'll actually work on:

• Live project — an HRMS platform (real product, real users, real deadlines)
• End-to-end design: UX research → wireframes → UI → prototype → dev handoff
• Brand and marketing design for our products
• Occasional events and founder-level work — you'll be in the room, not just making screens

Who I'm looking for:

• Strong Figma skills — if you don't know components and auto-layout, keep learning first
• Genuinely curious about AI tools — you don't need to know them all, just be excited to learn
• Creative with an opinion — show me a portfolio that has personality
• Based in Bengaluru, available full-time

What you get:

• ₹10,000–20,000/month based on skill
• Real product experience from week one
• Direct mentorship from a founder with 15+ years in tech
• Events, networking, actual business exposure
• Path to full-time if you're good

This week had a lot of signal buried under the noise. Here's a structured breakdown:

Anthropic IPO filing: Anthropic confidentially filed for an IPO this week at a reported $965B valuation with ~$47B in annualised revenue (Source: CBS News, TechCrunch). That's a higher valuation and higher revenue than OpenAI's last reported figures. They've been quietly scaling Claude Mythos for critical infrastructure security (Project Glasswing, 150+ orgs in 15+ countries). The enterprise/government GTM is clearly printing money.

Microsoft Build 2026: Microsoft introduced "Autopilot" agents — continuous background agents that act without being prompted. First one is Scout (inbox + Teams monitoring). Plus 7 new MAI models including MAI-Thinking-1 (35B params, 256K context window), Windows-local AI for NPU/Copilot+ PCs, and a Copilot Super App. They also released new models specifically to reduce OpenAI dependency for enterprise customers (CNBC).

Google I/O 26: Gemini 3.5 Flash released as GA — Google's best agentic/coding model yet. Gemini Omni adds true multimodal blending. Key pricing: Ultra drops $250→$200/mo, new Developer tier at $100/mo. Managed Agents (stateful, sandboxed) hit public preview. DeepMind also hired 20+ Contextual AI researchers for ~$85M.

Mistral: Le Chat renamed Vibe, now an autonomous work+code agent. Released Search Toolkit in public preview. Aggressive US market push from CEO Mensch.

xAI: SpaceX acquires xAI. Grok 4.3 ships Skills + enterprise Connectors. UK MP sues over deepfake content. Pause on specialized trainer hiring.

Alibaba: Qwen3.7-Plus — multimodal, agentic, deep reasoning + tool use. Commerce agent support (brands building native Qwen agents for e-commerce).

Hugging Face: IPO'd on NASDAQ at $42/share, $15B market cap, $2.1B raised. 30%+ of Fortune 500 with verified accounts.

Funding: DeepSeek reportedly close to $7.4B round (Tencent + founder). Anthropic's $65B Series H already closed. Q1 2026 global VC hit $300B, AI = 80%+.

My take as someone building on top of these APIs:

The Microsoft "Autopilot" announcement is the one I'm most interested in technically. The shift from "prompt → response" to "continuous observation → autonomous action" is architecturally significant — it's not just a product category, it changes how you think about memory, state management, and trust boundaries for agents in enterprise environments.

On pricing: Google's move is going to accelerate commoditization of the base model layer faster than anyone predicted 12 months ago. If you're building a product whose primary value is "access to a good LLM," you're in trouble. The differentiation has to be data, workflow depth, or vertical-specific trust.

The Anthropic revenue number ($47B annualised) is the most interesting data point of the week. That's not consumer subscription math — that's deep enterprise contracts in healthcare, security, and government. The "boring" verticals are where the real AI money is.

Happy to go deeper on any of these. What's the one story this week that most changes your roadmap?

Pulling together this week's major AI releases for anyone who didn't have time to track every blog post. Sticking to substantive changes, not hype.

Anthropic — Claude Opus 4.8 Released this week. Headline pricing unchanged, but Fast Mode dropped from $30 input / $150 output per million tokens to $10 / $50 — a 3x reduction on the premium tier. Reported improvements in "judgment" and longer autonomous runs. Also shipped 20+ legal MCP connectors and Microsoft 365 add-ins (Excel, PowerPoint, Word) in GA.

Alibaba — Qwen 3.7 Max Launched May 20 at Alibaba Cloud Summit. 1M-token context. Reported to top Claude Opus 4.6 Max on Terminal-Bench 2.0, SWE-Bench Pro, and MCP-Atlas. Pricing $2.50 / $7.50 per million tokens — roughly half of Opus 4.7. Alibaba claims autonomous operation up to 35 hours without performance degradation. Alibaba is now ranked #6 lab globally on Arena text leaderboard.

OpenAI — GPT-5.5 Instant Now default in ChatGPT. Reports 52.5% fewer hallucinated claims than GPT-5.3 Instant on high-stakes prompts (medicine, law, finance). OpenAI also shipped a ChatGPT sidebar inside Excel and Google Sheets, plus a personal finance dashboard for Pro users (US only).

Google — Gemini 3.5 Flash Reported to beat Gemini 3.1 Pro on coding and agentic benchmarks at ~4x faster output token rate. Ultra subscription cut from $250 to $200/month; new $100/month Developer tier introduced.

xAI — Grok Build 0.1 Coding agent moved to public API beta May 28. Custom Skills feature added for reusable user-defined tasks. Connectors for SharePoint, OneDrive, Notion, GitHub, Linear, plus bring-your-own MCP support.

Mistral Launched Vibe (unified work + code agent, replaces Le Chat). Acquired Emmi AI for physics-based simulation. Targeting €1B revenue in 2026; new 10MW inference DC announced.

Hugging Face Launched an app store for the Reachy Mini robot. ~10,000 units shipped. Also reported a malicious repo masquerading as an OpenAI release that accumulated 244K downloads before takedown — relevant for anyone pinning models from HF in production.

My take as someone building on top of these APIs:

The 3x Opus Fast Mode price cut and Qwen 3.7 Max's pricing + autonomous duration are the real signal this week. The cost floor on premium-tier inference is dropping faster than most app-layer products have repriced for. Anyone running multi-step agent workflows needs to recompute unit economics this week — either pass through the savings or reinvest the margin.

The other pattern worth noting: OpenAI and Anthropic are both pushing into Excel/M365 surfaces. Distribution is becoming the next battleground, not raw model capability. If you're building a productivity SaaS, the giants are now inside the same surface as you.