An AI-assisted coding practitioner reflects on how dramatically cheap coding models have improved since mid-2025, when only top-tier models like GPT-4 and Sonnet 3.5 were usable via early tooling harnesses like Brokk. Today, cheap models like DeepSeek Flash 4.1 reportedly beat larger models like 'Sol' on internal benchmarks despite being a fraction of the size. The author now favors DeepSeek Flash V4.1 for most tasks, plans to drop premium subscriptions to Anthropic, Z.ai, and OpenAI, and argues model choice should now hinge on vendor trust and data practices rather than raw capability, though top models remain useful for the hardest problems.
Nguồn: https://lostechies.com/ryansvihla/2026/09/22/why-not-use-deepseek-flash-for-everything. 8 Sync News chỉ tóm tắt và dẫn link; bản quyền nội dung thuộc tác giả và nguồn gốc.
Đọc tin ở đây, luyện code, học theo lộ trình và luyện IELTS trên các sản phẩm anh em — tất cả kết nối với nhau trong hệ sinh thái 8 Sync.
Cổng chính của hệ sinh thái: giới thiệu sản phẩm, blog và bảng giá trọn bộ.
Khám pháHọc theo lộ trình rõ từng chặng: video, quiz chấm tự động, certificate và mentor đang làm nghề.
Xem lộ trình1.000 bài DSA, đề tiếng Việt, chấm tự động 7 ngôn ngữ — nhiều bài FREE, chạy ngay trên trình duyệt.
Luyện miễn phíChấm bốn kỹ năng IELTS bằng AI, phản hồi chi tiết theo rubric.
Dùng thử miễn phíAI IDE 22 MB cho dev Việt.
Tải miễn phíBộ nhớ tổ chức cho AI agent.
Khám pháAI trực Fanpage, tự sàng lọc lead.
Dùng thửAn interactive guide to the Model Context Protocol: every JSON-RPC message on the wire, step by step. Transports, OAuth, tools, resources, sampling, elicitation, tasks, tool search and codemode.
I priced 30 days of my real Codex usage at API rates. A $100 plan covered $745 of API-equivalent work. Here's the math, the script to run on your own logs, and when the API still wins.
Choosing between AI pentesting vendors requires looking past marketing labels like 'autonomous' or 'agentic' because the underlying systems vary widely. A Stanford-led study ran different AI agent frameworks against a live 8,000-host network and found that between 55% and 82% of reported findings were confirmed as real vulnerabilities. Swapping only the underlying model moved one framework's valid finding rate from 57% to 80%, yet that same framework still scored lowest overall since its findings stayed shallow. On a CTF-style benchmark two frameworks scored near-identically (48.6% vs 45.9%), but on the live network one scored nearly three times higher on severity and complexity. Buyers should demand proof of exploitation, real-network results, clear safety controls, data handling answers and clarity on what 'continuous' actually means.
+ a practical learning checklist to learn AI engineering.
...explained visually (with tradeoffs in production).
How DeepSeek Harness's Super-agent works: a Router, isolated Workers, event triggers and a Watchdog let one AI agent run many tasks. Diagrams inside.
Claudemy turns Claude into a personal tutor that builds audio lessons on any topic.
It really looks the part now.
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