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Learning guides

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Learning guides

18 articles

  1. Instant agent steering and recoverable tool calls

    A close reading of Codex instant_interrupt: ending model output, continuing background tools, and preserving state when users change requirements mid-run.

    Learning guides Agent engineering Runtime & infrastructure Memory & context
    English

  2. Keep review evidence separate from compacted agent context

    Independent Codex Guardian history shows why generation context and review evidence need separate records, with provenance through resume and rollback.

    Learning guides Agent engineering Memory & context Evaluation Security & privacy
    English

  3. Why old CLAUDE.md rules can hinder a model upgrade

    Use prompt audits, instruction layers, and migration evals to retain real requirements, reassess model workarounds, and enforce hard limits in code.

    Learning guides Agent engineering Evaluation Developer tools
    English

  4. Why agent network permissions need ongoing checks

    Codex network policy changes explain revocable permits for redirects, long responses, and WebSockets, and why tool and network permissions need separate layers.

    Learning guides Security & privacy Runtime & infrastructure Agent engineering
    English

  5. Financial markets from zero: stocks, Bitcoin, and risk

    A beginner learning path through stocks, ETFs, indexes, Bitcoin, candlesticks, position sizing, paper trading, backtesting, and tax basics.

    Learning guides Finance
    English

  6. Debugging agents with traces, spans, and OpenTelemetry

    The GitHub Copilot OpenTelemetry update explains agent traces, spans, metrics, events, content capture boundaries, and a telemetry adapter for Lora PI Kit.

    Learning guides Agent engineering Developer tools Runtime & infrastructure
    English

  7. Why pinning a Git SHA can still run different code

    Plugin4Shell exposes a supply-chain gap: a pinned SHA records the expected version, but installers must also verify the actual HEAD after checkout.

    Learning guides Security & privacy Developer tools MCP & skills
    English

  8. When to split a task across agents: check dependencies

    How task dependencies shape multi-agent results, with SAIGE experiments, ablations, and OpenAI guidance for deciding when to delegate.

    Learning guides Multi-agent systems Agent engineering Evaluation AI research
    English

  9. Why you cannot just rerun an agent after a crash

    WorkflowAgent, step boundaries, and idempotency keys explain safe recovery after crashes, timeouts, and human pauses, with a proposed Lora PI Kit adaptation.

    Learning guides Agent engineering Runtime & infrastructure
    English

  10. Where agent credentials belong: host, vault, and broker

    Where keys belong when coding agents call GitHub, databases, and cloud APIs, and how vaults and credential brokers define access boundaries.

    Learning guides Security & privacy Agent engineering Runtime & infrastructure
    English

  11. Why more agent tools can mean worse tool selection

    How Tool Search loads definitions on demand, affects prompt caching, and differs from MCP connections and ARD resource discovery.

    Learning guides MCP & skills Memory & context Agent engineering
    English

  12. Should an agent keep going or start a fresh attempt?

    Use When Agents Slow Down, Reflexion, Hyperband, and agent evaluation to compare continued revision with independent attempts under reproducible budgets.

    Learning guides Evaluation Memory & context AI research
    English

  13. Turn production agent failures into regression tests

    Use Kitaru Replay, Evaluator, and Regression Suite to preserve production failures as repeatable agent tests, with tool policies and CI gates.

    Learning guides Evaluation Agent engineering Developer tools
    English

  14. Why long tasks need more than one growing conversation

    How OpenAI Agents API and Anthropic Managed Agents use sessions, context windows, compaction, and persistent state for long-running agents.

    Learning guides Memory & context Agent engineering Runtime & infrastructure
    English

  15. What Tau solves by splitting an AI agent into three layers

    Tau separates model adapters, the agent core, and the application so tools and frontends can work together without depending on each other.

    Learning guides Agents Agent engineering Developer tools
    English

  16. Connecting an agent loop to a frontend with events

    Follow tool execution and repeated model calls, separate streamed deltas from final messages, and explore frontend state with a model-free Python demo.

    Learning guides Agents Agent engineering Web development
    English

  17. Loop Engineering Harness: controlling agent iterations

    Break down planning, execution, evaluation, state management, and stopping rules to keep multi-step agent tasks controlled and traceable.

    Learning guides Agent engineering Memory & context Evaluation
    English

  18. Sandbox isolation: boundaries, implementations, and practice

    How sandboxes limit untrusted code access to files, processes, networks, and resources, comparing VMs, containers, user-space kernels, and syscall filters.

    Learning guides Security & privacy Runtime & infrastructure
    English

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