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Office Hours

Series

June 2026

  1. Office Hours — What deterministic guarantees do you need from an LLM system for compliance-heavy enterprise use cases?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  2. Office Hours — How do you structure your LLM training infrastructure to avoid getting locked into a single provider or model?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  3. Office Hours — When should you use prompt engineering and when do you actually need fine-tuning or retrieval-augmented generation?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  4. Office Hours — What concrete guardrails and constraints do you need to put on LLM agents before deploying them to production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  5. Office Hours — How is AI-assisted coding actually changing your development workflow and productivity in a real codebase?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  6. Office Hours — What's the practical difference between using an AI agent for backend automation versus building traditional scheduled jobs or APIs?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  7. Office Hours — How do you know what data your AI coding agent is sending to the cloud, and what should you audit for?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  8. Office Hours — When should you use traditional ML (tabular models, gradient boosting) instead of jumping straight to LLMs for a new feature?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  9. Office Hours — How do you architect systems where AI agents can safely execute code or access tools without human review on every action?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  10. Office Hours — What are the actual best practices for learning to build effective multi-step AI agents beyond toy examples?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  11. Office Hours — When building AI agents, how do you decide between deterministic state machines and freeform LLM reasoning?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  12. Office Hours — What's a concrete pattern for adding governance and determinism to AI pipelines that need compliance or audit trails?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  13. Office Hours — How do you structure LLM applications to prevent hallucinations when the model is confident but factually wrong?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  14. Office Hours — What's the practical difference between building with Claude, ChatGPT, and open-source models when you need production reliability?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.

May 2026

  1. Office Hours — How do you reliably evaluate AI agent behavior in production when testing in development doesn't catch all failure modes?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  2. Office Hours — What's your strategy for sourcing and licensing data for training custom AI models?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  3. Office Hours — What common issues are you hitting with LLM gateways and API management in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  4. Office Hours — How do you give local LLMs persistent context without bloating prompts or losing information?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  5. Office Hours — Should you use regex or other methods to enforce security constraints on LLM agent outputs?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  6. Office Hours — What patterns work best for aggregating results when retrieval-augmented generation approaches fail in agentic systems?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  7. Office Hours — How do you handle data isolation and prevent information leakage in RAG systems serving multiple tenants?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  8. Office Hours — What's the best approach for real-time, local text-to-speech when building live voice interaction features?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  9. Office Hours — How do you prevent AI agents from taking unintended actions when they have access to external tools and APIs?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  10. Office Hours — What are developers actually building with AI coding agents right now?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  11. Office Hours — Why does Codex work better than Claude Code for production monoliths?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  12. Office Hours — What practical tips do power users have for working effectively with AI agents?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  13. Office Hours — Are there any AI agent sandboxes worth evaluating right now?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  14. Office Hours — How much are you actually spending on AI coding at work?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  15. Office Hours — What's the best way to replace RAG pipelines with a filesystem interface for AI agents?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  16. Office Hours — Why don't AI coding tools like REST?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  17. Office Hours — How do you prevent retry cascades in LLM systems?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  18. Office Hours — Why should you add relationships and structure to your AI context instead of using naive RAG?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  19. Office Hours — What's the best approach for handling OCR and document parsing in a RAG pipeline?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  20. Office Hours — How are you using multi-agent AI systems effectively in your daily workflow?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  21. Office Hours — Should you use agentic search or RAG for retrieval, and what's the tradeoff in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  22. Office Hours — How are you preventing runaway LLM workflows and token costs in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  23. Office Hours — How are you structuring context and prompts for AI coding agents to get reliable results?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  24. Office Hours — What breaks when you run AI agents unsupervised in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  25. Office Hours — How are you using LLMs in production and what unexpected issues have you hit?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  26. Office Hours — Are you using finetuning for LLM agents in production, and if so, what trade-offs did you encounter versus using base models with prompt engineering?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  27. Office Hours — How should you structure memory and context for AI agents so they can learn from past tasks without growing unbounded token usage?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  28. Office Hours — What monitoring and safeguards do you need in place to control AI agents that take real actions in production systems?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  29. Office Hours — How do you keep AI coding agents aligned with your team's codebase standards, style guides, and architectural decisions?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  30. Office Hours — Should you give AI agents access to API keys and private credentials, and if so, what isolation strategies actually work?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.

April 2026

  1. Office Hours — What's the best way to set cost limits and prevent AI agents from burning through your API budget on failed or inefficient tasks?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  2. Office Hours — How do you prevent AI agents from accidentally introducing vulnerable dependencies or malicious code when they autonomously modify your codebase?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  3. Office Hours — What's your strategy for testing and evaluating LLM outputs in production now that Promptfoo was acquired?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  4. Office Hours — Has anyone successfully fine-tuned LLMs for production use and what was the ROI?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  5. Office Hours — Is operational memory a missing layer in AI agent architecture?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  6. Office Hours — What hiring criteria should you use when your team is heavily using AI-assisted coding?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  7. Office Hours — Who is actually getting measurable value from AI agents in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  8. Office Hours — How do you know if AI agents will choose your tool?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  9. Office Hours — Has anyone deployed LLMs to production and what were the biggest operational challenges?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  10. Office Hours — How are you extracting the best performance out of your RAG pipeline?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  11. Office Hours — Is anyone using function calling with LLMs in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  12. Office Hours — Best LLM stack for Q&A over internal PDFs?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  13. Office Hours — What tools are you using for AI evals, and why does everything feel half-baked?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  14. Office Hours — Is synthetic data generation practical outside academia?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  15. Office Hours — Are we pretending RAG is ready, when it's barely out of demo phase?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  16. Office Hours — Why don't we have a functional DSL for data+embedding+API pipelines?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  17. Office Hours — Why are so many companies rolling out their own AI/LLM agent sandboxing solution?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  18. Office Hours — What are some actual use cases of AI Agents right now?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  19. Office Hours — Can you personalize an LLM by fine-tuning it on conversation history, or is that the wrong approach?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  20. Office Hours — Who is actually getting real business value from AI agents right now, and how?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  21. Office Hours — Is fine-tuning LLMs actually worth it, or is prompt engineering and RAG always the better path?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  22. Office Hours — Is fine-tuning the right approach when you want a model to reliably remember your codebase or company-specific data?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  23. Office Hours — What kinds of tasks are AI agents actually reliable at in production today?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  24. Office Hours — Is RAG an antipattern for AI agents, or is it still the right default approach?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  25. Office Hours — How do you actually monitor AI agents in production when there's no standard playbook yet?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  26. Office Hours — We're using an LLM to extract structured data from messy PDFs. Sometimes it works perfectly, sometimes it misses fields or invents data. How do I know if the problem is the model, my prompt, or the PDF quality itself?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  27. Office Hours — We're getting inconsistent outputs from the same prompt with GPT-5.4. Temperature is locked at 0. What's actually going on?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  28. Office Hours — I'm using Claude Opus 4.6 for a customer-facing summarization task. Should I batch requests during off-peak hours to save money, or just call the API in real-time?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.

March 2026

  1. Office Hours — How do I know when to stop prompt engineering and just upgrade my model?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  2. Office Hours — Is it better to improve the harness around the LLM or wait for a better model?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  3. Office Hours — Should I A/B test my LLM prompts in production or is that overkill?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  4. Office Hours — What's the hardest part of building AI agents that actually work?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  5. Office Hours — How do you actually test LLM apps beyond vibe checks?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  6. Office Hours — Why is AI agent reliability barely improving despite 18 months of model upgrades?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  7. Office Hours — How are people safely reusing cached LLM answers in production RAG systems?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  8. Office Hours — Do structured outputs from LLMs create false confidence that the response is actually correct?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  9. Office Hours — How are you handling LLM API costs in production without sacrificing quality?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.
  10. Office Hours — How do I actually know if my LLM is hallucinating in production?

    A daily developer question about AI/LLMs, answered with a direct, opinionated take.