Sara Tech

focusing on data quality when benchmarks are broken left and right is so smart.

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Native RGBA with partial alpha support means the transparency is part of generation. Seedream 5.5: › generates the alpha channel directly › supports semi-transparent details › produces assets for further compositing Every strand of hair doesn’t need to become a manual selection exercise.

An Anthropic engineer literally stopped me at a coffee shop because of what was on my screen. I was sitting at Sightglass running my Polymarket bot. He looked over once. Then again. Then said: “That’s not a normal trading setup.” I told him the whole thing runs on: • Claude Code • 4 open-source repos • $25/month That’s it. He pulled up a chair instantly. “I work on the agent team at Anthropic,” he said. “We stress test Claude for workflows exactly like this.” Then I showed him what the bot was actually doing. 86 MILLION trades analyzed. Every wallet. Every entry. Every exit. Every profitable pattern. One prompt: “Find wallets with 100+ trades and 70%+ win rate. Rank by profit. Export the best ones.” Claude scanned 14,000 wallets in 4 minutes. Returned 47. The top 20 wallets made more money than the other 13,000 combined. He stared at the results and said: “That’s not data analysis. That’s a weapon.” And we were just getting started. Second repo: A Rust CLI scraping 500 live Polymarket markets in minutes. Claude filtered everything automatically: • spread gaps • liquidity depth • timing windows • whale behavior 500 markets became 35. Before I even looked at them. 93% rejected automatically. Then a trade closed live on my screen. +$84. He didn’t even blink. “How does it decide when to enter?” 3 independent AI agents: • arbitrage • convergence • whale-copying No shared memory. 2 agents agree = full position 1 agrees = half size Disagreement = no trade That consensus system alone cut 40% of losing trades. Then he asked the real question: “What about exits?” That’s where it gets stupid. The profitable whales rarely hold to settlement. 91% exit early. So my bot exits BEFORE they do. It takes profit at: • 85% expected move or • unusual volume spikes Basically: It copies smart money… then front-runs their exits. He just sat there staring at the terminal. “How much did you start with?” $200. 27 days ago. Current balance: $14,300. 271 trades. 74% win rate. Sharpe ratio: 2.47. Fully automated. I haven’t touched it in weeks. Before leaving he said: “This is almost identical to the internal scenarios our red team simulates.” Next morning I got an email from him. “Would you be open to speaking with our policy team?” I replied: “The article IS the meeting.” The craziest part? This stack costs less than Netflix. AI is no longer replacing workers. It’s replacing entire hedge funds. Comment “Claude” if you want the framework.

Once your visuals are ready, CapCut PC makes it easier to refine the details. With its AI Edit feature, you can select a specific area in your visual and describe the change you want — for example, changing a product's colorway. No need to redo the entire visual just to adjust one detail. #CapCutDidThat

Better search can lead to better decisions by AI coding agents. Jevlin combines eight search engines into one workflow, helping developers retrieve information from multiple sources without building separate integrations. Works with Claude Code and Codex, with one-line installation and $10 free credits. jevlin.ai

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