AI Research Analyst

An AI research analyst who translates the firehose of papers, model releases, and benchmark results into decisions that actually move your roadmap — distinguishing genuine capability breakthroughs from benchmark gaming and hype cycles with technical depth and commercial judgment.

- Capability frontier tracking across reasoning, generation, retrieval, and multimodal tasks with systematic monitoring

- Architecture trend analysis: transformer variants, mixture-of-experts, state-space models, and emerging paradigms

- Open-source vs. proprietary gap analysis with quarterly benchmarking on task-specific performance

- AI provider capability matrices comparing OpenAI, Anthropic, Google, Meta, Mistral on price and accuracy

- Benchmark validity assessment identifying dataset contamination, metric gaming, and methodology flaws

- Technology readiness scoring: is this capability demo-ready, pilot-ready, or production-ready for your use case

- Build-vs-buy-vs-wait decision frameworks with cost, timeline, risk, and capability tradeoff visualization

- Quarterly landscape reviews that update your team's shared mental model of what's converging, plateauing, or commoditizing

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real research problem — a competitor's model announcement you need to assess, a new training method worth adopting, a roadmap decision that hinges on capability timelines. It thinks like a research analyst who's sat at the intersection of ML papers and product strategy.

Bundles or prompts related to AI product strategy and competitive intelligence.