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@algodojo.xyz

@algodojo.xyz

Posts

7

Publications

1

AlgoDojo BlogAug 25, 2026

Dynamic LLM API Key Rotation: Securing Agent Infrastructures with Infisical and GitHub Actions

As AI agents evolve from experimental chat interfaces into autonomous systems executing multi-step workflows across databases, cloud platforms, and third-party SaaS tools, an imperative challenge has

workflow automationdynamic-llm-api-key-rotation--securing-agent-infrastructures

AlgoDojo BlogAug 21, 2026

Defensive Tool Orchestration: Implementing Idempotency and Exponential Retries for LLM-Based Activities in Temporal

Large Language Models (LLMs) have transformed software architecture from deterministic state machines into dynamic, reasoning-driven ecosystems. Where software engineers once wrote explicit `if-else`

workflow automationdefensive-tool-orchestration--implementing-idempotency-and-e

AlgoDojo BlogAug 14, 2026

Compensating Saga Transactions: Managing Distributed Tool Side-Effects in Long-Running Temporal Workflows

When autonomous AI agents and distributed microservices execute multi-step workflows, managing un-doable side-effects across external tools becomes a primary engineering hurdle. By leveraging the Saga

Temporalcompensating-saga-transactions--managing-distributed-tool-si

AlgoDojo BlogAug 14, 2026

Human-in-the-Loop Signals: Handling Async Approval Timeouts for Long-Running Agent Workflows in Temporal

Autonomous AI agents are capable of remarkable multi-step reasoning, but high-stakes decisions demand human oversight. Here is how to build resilient, long-running human-in-the-loop workflows in Tempo

Temporalhuman-in-the-loop-signals--handling-async-approval-timeouts-

AlgoDojo BlogAug 13, 2026

Context Compression Strategies: Hierarchical Summarization of Archival Memories in Letta Agents

As stateful AI agents transition from brief session interactions to multi-month operational horizons, managing context efficiency becomes an urgent engineering priority. Discover how Letta utilizes hi

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@algodojo.xyzAug 13, 2026

Long-Poll Signaling in Temporal: Synchronizing Asynchronous Human Approvals with LLM Execution Trees

As autonomous AI agents navigate complex multi-step execution trees, introducing human approvals creates a fundamental timing mismatch between millisecond LLM calls and multi-hour human response times

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AlgoDojo BlogJul 3, 2026

Pattern: Self-Correcting Agent Loops with Guardrail Prompts

Self-correcting agent loops use guardrail prompts to catch errors before

AI agentspattern--self-correcting-agent-loops-with-guardrail-prompts