How I built an AI Kanban platform with FastAPI, RAG and agents
Architecture notes from Lavc Systems: FastAPI backend, React UI, local LLMs, RAG, vector memory, agents, WebSocket observability, and task orchestration.
Backend engineering, AI systems, automation, API integrations, cloud architecture, security, and software delivery notes by Patrick Araujo.
Architecture notes from Lavc Systems: FastAPI backend, React UI, local LLMs, RAG, vector memory, agents, WebSocket observability, and task orchestration.
A concise pattern for API integrations: credential boundary, raw ingestion, idempotent identifiers, scheduled jobs, SQL modeling, and operational reporting.
FastAPI backends become easier to operate when requests, jobs, queues, task state, and logs are designed as one traceable workflow.
LLMs can summarize, retrieve, draft, and suggest, but critical actions need policy, permissions, audit trails, and deterministic execution paths.
A practical reporting pipeline starts with reliable API collection, keeps raw data auditable, and moves business logic into SQL models that can evolve.
How to build biodiversity monitoring pipelines with camera traps, acoustic and environmental sensors, edge filtering, cloud storage, AI labels, human review, dashboards, and conservation alerts.
How regional fintech teams can model accounts, devices, documents, phone numbers, payment keys, beneficiaries, transfers, and temporal links as an explainable anti-fraud graph.
How to choose cloud regions in Latin America by measuring user latency, service availability, data location, international transfers, resilience, egress, and operational complexity.
How to design digital public services around identity, forms, evidence, payments, status, notifications, interoperability, accessibility, and auditable APIs.
How to translate the EU AI Act into a software control plane for system inventory, role classification, data governance, technical documentation, logging, human oversight, release gates, monitoring, and incidents.
How to automate connectivity field service with network incidents, trouble tickets, work orders, resource inventory, technician routing, SLA clocks, offline mobile forms, evidence, and closure verification.
How to translate NIS2 into backend requirements for asset inventory, risk management, incident reporting, continuity, supply-chain security, vulnerability handling, access control, evidence, and management accountability.
How to build APIs for unstable mobile and remote networks with deadlines, retries, exponential backoff, jitter, idempotency, caching, compression, pagination, resumable transfer, and graceful degradation.
How to design smart-mining telemetry in Latin America with vibration, temperature, pressure, safety events, edge buffering, OPC UA, MQTT Sparkplug, predictive maintenance, industrial cybersecurity, and integrated operations.
How to build agricultural IoT with ESP32 nodes, calibrated soil-moisture sensors, offline irrigation control, flow and pressure feedback, MQTT or LoRaWAN telemetry, evapotranspiration models, dashboards, predictive alerts, OTA, and safety interlocks.
How telecom operators can turn calls, chats, tickets, network events, billing data, and customer history into an AI-assisted resolution pipeline with diagnosis, safe tools, human handoff, verification, and auditability.
What developers can build around Brazilian operators by combining Open Gateway APIs, 5G, IoT, edge processing, customer-care AI, service automation, OSS/BSS integration, observability, consent, and multi-operator architecture.
How to design reliable Latin American ERP integration across Omie, SIGE Cloud, Zoho Creator, Google Sheets, and SQL using raw ingestion, canonical models, identity mapping, incremental sync, idempotent writes, reconciliation, and observability.
A practical low-cost observability architecture for Latin American SMEs using structured logs, Prometheus metrics, cron monitoring, synthetic checks, sampled traces, actionable alerts, retention tiers, and cost controls.
How to design multilingual AI support bots for Latin America with language and locale detection, market-aware RAG, contextual localization, code-switching, grounded answers, tool controls, human handoff, and per-language evaluation.
How US and Latin American nearshore teams can design and deliver APIs with timezone overlap, contract-first specifications, localization rules, async reviews, CI gates, clear ownership, incident handoffs, and outcome-based delivery metrics.
How to build offline-first mobile and web systems with local databases, sync queues, idempotent operations, explicit conflict resolution, low-bandwidth UX, bounded retries, secure local storage, and observable synchronization.
How to design event-driven Pix and Open Finance payment pipelines with idempotency, consent, settlement evidence, double-entry ledgers, refunds, fraud controls, multi-layer reconciliation, and operational observability.
How to design resilient backends for satellite direct-to-device and non-terrestrial networks with connectivity fallback, store-and-forward queues, message expiry, idempotency, delayed events, local buffering, degraded modes, and secure commands.
How to design WhatsApp commerce automation with Cloud API webhooks, consent, CRM identity, order state, payment confirmation, logistics events, AI assistance, human handoff, idempotency, and observability.
A backend architecture for AI agents acting safely on SaaS accounts, invoices, support tickets, and reports through delegated authorization, approvals, durable workflows, and audit evidence.
How to design AI-assisted incident response runbooks that preserve evidence, summarize telemetry, propose containment, open remediation pull requests, require approvals, and verify recovery.
How gateways evolve for agent traffic with protocol-aware discovery, tool registries, delegated authorization, semantic policy, token and action budgets, event logs, and result verification.
How multi-tenant SaaS platforms can use trusted execution environments, remote attestation, policy-bound key release, and controlled outputs to protect sensitive analytics and AI data in use.
How power capacity, energy efficiency, carbon intensity, water, accelerator availability, latency, and data residency should shape AI infrastructure, caching, scheduling, and workload placement.
How RAG systems should preserve document source, creator, version, license, ACL, parser, chunk, embedding, index, retrieval, prompt, claim, and citation lineage.
How Latin American enterprises can turn 5G coverage into operational systems by combining public or private mobile networks, local breakout, edge computing, event pipelines, cloud services, network APIs, dashboards, and measurable outcomes.
How to design real-time digital trust systems for Latin America by combining identity proofing, passkeys, device and telco signals, behavioral data, payment context, FAPI-secured APIs, fraud decisions, human review, and recovery.
How product teams can build continuous model and AI system evaluation pipelines with versioned datasets, deterministic tests, calibrated judges, human review, release gates, and production feedback.
How to run local LLMs for sensitive source code with explicit trust boundaries, controlled egress, verified model artifacts, ACL-aware RAG, sandboxed tools, secret protection, and hybrid routing.
How NIST's AI Agent Standards Initiative, MCP, A2A, OpenAPI, identity, delegation, and auditability are reshaping the backend boundary for interoperable agents.
How to engineer AI systems around request budgets, token costs, GPU utilization, prefix caches, dynamic batching, bounded queues, backpressure, and graceful degradation.
How CI/CD platforms must evolve when coding agents generate changes: executable specs, tests, security gates, provenance, attestations, review, and controlled delivery.
How an AI security control plane joins model inventory, prompts, data flows, identities, permissions, evaluations, runtime logs, vendor risk, incidents, and governance.
How to allocate and observe AI workload costs across inference, embeddings, vector databases, storage, egress, scheduled jobs, tenants, features, and business outcomes.
How to choose and govern API keys, OAuth clients, service accounts, workload identities, bots, and AI agent identities with reconstructable audit trails.
How backend systems coordinate physical AI in warehouses through missions, fleet adapters, traffic, telemetry, recovery, safety boundaries, interoperability, and simulation.
A practical post-quantum readiness guide for backend engineers covering cryptographic inventory, TLS dependencies, token lifetimes, signatures, vendors, testing, and migration.
How predictive signals, CISA KEV, EPSS, threat intelligence, anomaly detection, attack-path context, and bounded automated containment create preemptive security pipelines.
Why prompt injection becomes a confused-deputy authorization failure when AI agents can use tools, access data, and act with delegated authority.
How AI-generated pull requests should preserve task, agent, model, tool, diff, review, commit, SBOM, build provenance, signatures, artifact, and deployment traceability.
A practical architecture for AI-generated systems: TypeScript for contracts and application boundaries, Python for AI and automation, SQL for facts, and CI for independent verification.
How to design identity, OAuth scopes, policy gateways, audit logs, and least-privilege authorization for AI agents that act across APIs and internal tools.
How to design AI SOC automation with SIEM normalization, detection-as-code, alert triage, MITRE ATT&CK context, human approval gates, SOAR actions, and incident evidence.
Why APAC AI infrastructure is a chip-to-cloud engineering problem: semiconductors, HBM, advanced packaging, data center power, cooling, GPU scheduling, sovereign AI, and software supply chains.