Notes from the
edge of the model.
Field notes on what actually breaks in production — agents, retrieval, evaluation, MLOps, and the career decisions nobody writes down. Longer arguments become papers; these are the rest.
353 posts
COVID exposed how fragile global supply chains are.
AI supply chain applications: demand forecasting with ML (predicting what people will buy before they know). Real-time disruption detection using NLP on news and social media. Route…
By Pranay Mahendrakar Read postThe most common pitch I hear from non-technical founders in 2026: "I have a great AI idea.
If you're an AI engineer with even moderate skills, you are the scarce resource in the startup ecosystem right now. Non-technical founders with ideas are abundant. Technical cofounders…
By Pranay Mahendrakar Read postThe fastest growing AI job category right now isn't LLM engineering. It's multimodal AI engineering.
Why: every major model is going multimodal. GPT-4o sees and hears. Claude processes images and documents. Gemini handles video. The text-only era is ending. Multimodal AI roles…
By Pranay Mahendrakar Read postIn 2025-2026, big tech acquired AI startups at a rate not seen since the social media era.
The pattern: large company acquires AI startup primarily for the TEAM, not just the product. The talent acquisition premium in AI is 2-5x the company's actual revenue. What this means…
By Pranay Mahendrakar Read postThe gap between AI research and AI products is the most expensive gap in the tech industry.
The problem: research teams produce papers with impressive results on benchmarks. Product teams need systems that work reliably, at scale, within budget, on real data. The translation…
By Pranay Mahendrakar Read postThe most impactful AI companies of the next decade won't be built in Silicon Valley.
Why: these markets have massive populations, rapidly growing internet access, unique problems that Western AI products don't solve, and local language and cultural requirements that…
By Pranay Mahendrakar Read postI've been in AI for over a decade.
The engineers who survive these transitions share common traits. The ones who don't share different ones. What makes an AI career last: Strong fundamentals. Math, statistics, algorithms…
By Pranay Mahendrakar Read postForget bigger GPUs. The future of AI compute might be chiplets — tiny specialized processors…
AMD is already doing this. Intel is investing heavily. And for AI specifically, the idea is powerful: instead of one massive chip that does everything, combine specialized chiplets — one…
By Pranay Mahendrakar Read postA new job title appeared on my LinkedIn feed 47 times last month: "AI Trust Engineer."
This role sits at the intersection of AI engineering, security, ethics, and user experience. The AI Trust Engineer ensures that AI systems are trustworthy enough for users to rely on…
By Pranay Mahendrakar Read postAI developer tools are a $50B+ market by 2028.
The landscape: GitHub Copilot (code generation). Cursor (AI-native IDE). Replit (AI-powered development environment). Codeium (free AI code completion). Sourcegraph Cody (codebase-aware…
By Pranay Mahendrakar Read postEdTech powered by AI is the largest untapped market I can identify. And it's about to break open.
The market: $400B+ in global education spending. Less than 5% uses AI in any meaningful way. The opportunity is staggering. What's working in 2026: Khan Academy's Khanmigo (AI tutor…
By Pranay Mahendrakar Read postI'll stake my reputation on these AI market predictions for 2030. Bookmark this and check back.
The AI market will exceed $1 trillion annually by 2030. Not speculation — the growth trajectory from current $200B+ makes this almost certain. Job predictions: 5 million new AI-related…
By Pranay Mahendrakar Read post