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tanguy decourson
Staff Software Engineer specializing in AI agents and full-stack platforms
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Built a production LLM-powered crypto trading platform in PHP/Laravel that combined RAG, market data, sentiment signals, and operator review workflows to generate buy/sell recommendations. Stands out for a disciplined approach to agentic systems: the application owns orchestration, risk controls, audit trails, and approvals, while the LLM is treated as a bounded advisory component rather than the control plane.
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Key Strengths
- shipped a production LLM-powered crypto trading feature end-to-end
- strong orchestration-first approach with deterministic application control
- builds safety-critical AI systems with bounded LLM roles
- deep focus on reliability through risk limits, kill switches, and manual approval
- designs explainable operator-facing AI workflows and admin UIs
- separates planning, execution, and commit actions for safer agent design
- practical understanding of latency, cost, reliability, and safety tradeoffs
- strong observability mindset for non-deterministic systems
- proactive handling of prompt injection and hallucinated tool results
- maintainable architecture with clear separation of prompts, tools, business rules, and UI
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