Thoughts, experiences, and technical insights from my journey in software development.
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Google released Gemini 3.6 Flash — 17% fewer output tokens, lower price, higher benchmarks. Flash-Lite hits 350 tok/s at $0.3/1M input, built for scaling agentic workflows.
US AI market share on OpenRouter collapsed from 70% to 30% in a year. Chinese open-weight models dominate token volume — and developers are the first to benefit.
In just 3 days, Alibaba and Moonshot AI unveiled Qwen 3.8 (2.4T params) and Kimi K3 (2.8T params) — both going open-weight. Here's what it means for developers and the global AI race.
PrismML's Bonsai 27B compresses a full 27B-parameter model to 3.9GB, running on an iPhone 17 Pro at 11 tokens/s. The ternary variant retains 95% of full-precision benchmarks across 15 evaluation suites.
Ollama just closed a $65M Series B, reaching 8.9 million monthly developers with only 14 employees. Here's what this says about the local AI trend.
LLM pricing pages show dollars per token — but each model's tokenizer splits the same file into different token counts. Claude's newest tokenizer counts 73% more tokens than GPT for TypeScript, the language coding agents write most.
GPT-5.6 Sol scores 80 on the Coding Agent Index, beating Fable 5 in half the time. Three models — Sol, Terra, Luna — launched July 9, with real production case studies.
AI Now Institute just showed that Claude Code and Codex in autonomous mode can be tricked into executing attacker code hidden in a README file.
Apple filed a federal lawsuit against OpenAI on July 10, accusing the AI company of stealing trade secrets to build hardware that competes with the iPhone.
After a 2-week government hold, GPT-5.6 is public. Sol tops TerminalBench 2.1 at 91.9%, costs about a third less — the first AI release to need government approval.
Rejected by Parliament in March, Chat Control 1.0 returns via a procedural fast-track. The July 9 vote could make client-side scanning law again.
Zuckerberg acknowledged AI agent development isn't accelerating as planned, after 8,000 layoffs and a $145B infrastructure spend. What went wrong at Meta?