WRITING

Notes from the lab

Benchmarks, build notes and research on agents, retrieval and reinforcement learning, from Trilogy's AI Center of Excellence.

Subscribe on Substack ↗
  1. Skip the $600 Mac mini. Run OpenClaw securely on a remote box.

    The setup, the gotchas, and three Claude Code skills that do the install for you.

    “An assistant that does not stop when you close your laptop lid.”

    ↗
  2. Building the AI COE Chatbot

    Willfully over-engineering a simple RAG bot to explore agentic workflows.

    “Latency is the king of chat.”

    ↗
  3. Reinforcement Learning for Agents, Part II

    Agent Lightning, Handit.ai, and a homegrown tool, AgentEvolve.

    “There’s a glaring gap in this space.”

    ↗
  4. Reinforcement Learning Techniques to Optimize Agents

    Can RL loops continuously refine prompts, tools, and agentic pipelines?

    “You’re not merely tuning weights. You’re actually trying to improve the source code.”

    ↗
  5. Auto-Improve Bitcoin Algo Trading Strategies with LLMs

    Building and auto-refining algorithms with multi-model LLM loops.

    “From a negative -2.06 sharpe to a +3.99 sharpe.”

    ↗
  6. Agentic Automation for Social Content

    Content creation, approval and scheduling with n8n and Airtable.

    “Tool sprawl is killing productivity.”

    ↗
  7. Analyzing Large Datasets with LLMs

    Taming context limits and building reasoning agents for enterprise-scale insight.

    “LLMs are great with words, but weak with math and worse with scale.”

    ↗
  8. The Hidden Cost of Scattered AI Tooling

    And a four-layer framework for scalable enterprise adoption.

    “The rush toward AI everywhere often swaps one kind of debt for another.”

    ↗
  9. Claude Code: Triumphs, Trials and Trade-Offs

    Its architecture, standout features, and where it still falls short.

    “Incredibly smart and inexplicably dumb at the same time.”

    ↗
  10. Agentic Retrieval Deepdive

    A benchmarking study of off-the-shelf and custom agentic retrieval pipelines.

    “None of the advanced setups outperformed a strong dense baseline.”

    ↗
  11. Retrieval Benchmarking: Agentic vs. Vanilla

    Which datastores and embeddings actually win on retrieval accuracy.

    “Out-of-the-box agentic solutions consistently underperform vanilla retrieval.”

    ↗