Redis as an agent’s working memory and rate limiter
Building autonomous, multi-agent execution systems for quantitative trading workflows sounds great until you put them into production.
Read entryBuilding autonomous, multi-agent execution systems for quantitative trading workflows sounds great until you put them into production.
Read entryWhen you build and manage high-traffic analytics systems, your worst enemy isn't raw volume—it is dirty data.
Read entryI recently built an automated monitoring agent to parse order-book heatmaps, trading execution logs, and live liquidity charts. The goal was simple: run a…
Read entryBuilding complex LLM agents with LangGraph is incredibly intuitive until you run them in production on workloads that take minutes or hours to complete.
Read entryEvery second added to a feedback loop is a tax on engineering velocity. For my algorithmic trading platform, our deployment pipeline was suffering under a…
Read entryIn algorithmic trading, "maintenance windows" are a luxury we cannot afford. When your systems route orders to global financial exchanges operating across…
Read entryThree quarters ago, my team deployed an automated news-sentiment and event-driven futures trading system. We hooked up a raw, unfiltered firehose of real-…
Read entryIt was 10:14 PM on a Tuesday when the pager went off. Our primary execution router, which processes high-throughput routing signals for our algorithmic tr…
Read entryDeploying a 70-billion parameter model like Meta-Llama-3-70B on a local workstation is the holy grail for trading desks and quantitative shops looking to…
Read entryOur production algorithmic trading infrastructure processes thousands of order executions and millions of real-time market data ticks daily. For years, ou…
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