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Rohit Nair
Rohit Nair is an applied AI systems engineer at Ford in Detroit, specializing in agentic systems, code intelligence, retrieval, LLM evaluation, observability...
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84 % |
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Hong Phuc - AI engineer and systems builder
A personal operating system for serious AI engineering, developer tooling, local automation, and product-grade systems.
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84 % |
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Oron Culzac — Support Systems & AI Engineering
Support systems and AI engineering: turning repeated queue pressure, fragmented knowledge, and brittle manual processes into tooling a team can actually oper...
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84 % |
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Memory Engine for Engineering Teams - Shared Memory for Engineers and Agents
Turn decisions, runbooks, implementation facts, and team instructions into shared memory every engineer and coding agent can retrieve. Preserve engineering k...
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83 % |
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soren paetau | ai solution architect | llm systems, data architecture, workflow automation
I build LLM-powered products end-to-end — RAG pipelines, evaluation harnesses, and production deployments. Currently shipping AI analytics systems at Simplic...
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83 % |
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Farshad Pasbani
Engineer building ML systems, agentic-AI tooling, and the infrastructure that runs them.
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83 % |
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Tanmay Dogra · Portfolio
Full-stack ML/AI engineer building models, agentic workflows, and production systems that turn research into real products.
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83 % |
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Claude Code from Source — Architecture, Patterns & Internals
A technical book analyzing the architecture of Anthropic's AI coding agent. 18 chapters, 400 pages, reverse-engineered from source maps. No source code — onl...
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83 % |
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Datt Goswami — Staff AI infrastructure engineer
End-to-end systems for autonomous coding agents. Staff-level AI infrastructure engineer building Rust + Python LLM systems, agent memory, evals, and continua...
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83 % |
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Loop Engineering Guide: Build Safe Autonomous Agent Loops
A practical loop engineering guide for building autonomous coding-agent loops with discovery, handoff, verification, state, scheduling, worktrees, skills, MC...
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83 % |
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Kaushal Prajapati · Production AI Systems & Research
Kaushal Prajapati writes about production AI engineering, agentic systems, software engineering, deep-learning papers, evals, retrieval, and LLM platforms.
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83 % |
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Sebastián Orrego — @saitama
Platform & AI infrastructure engineer. I build the layer underneath other people's work: the platform that lets engineers ship without touching cluster state...
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83 % |
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Altan Çetin Çelik — AI/ML Systems
AI/ML systems engineer focused on adaptive inference, agent architecture, backend systems, and edge AI.
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83 % |
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Eli Maine | Practical AI Tools and Full-Stack Engineering
Eli Maine is a full-stack engineer building practical AI tools, agent memory experiments, and production web systems.
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82 % |
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Ryan Curtis - Resume
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82 % |
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Karimulla Naik — AI Systems & Code Intelligence
Karim Saheb — independent AI systems researcher building tools for code intelligence, inference optimization, and experimental ML architectures.
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82 % |
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Gotchacode - AI Engineering Systems
Gotchacode helps software teams adopt AI coding agents with stronger repo context, tests, CI, PR review, and engineering guardrails.
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82 % |
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Krzysztof Lempka | Systems Architect and Engineering Executive
Systems architect and engineering executive with sixteen years of software development experience. Scaling engineering teams, cloud architecture, and verifie...
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82 % |
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GAGCoders — Build smarter. Automate the repetitive.
Practical, responsible engineering guides for AI coding, agents, RAG, MCP and automation.
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82 % |
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Ryan Kilroy // Agents. Systems. People.
Ryan Kilroy — agentic systems designer and engineering lead. Production agentic AI systems end-to-end, plus the teams and operating models that ship them.
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82 % |
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