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Dev.to

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05:12
2026-10-07
dev.to
ai-agents

AI agent security risks: 4 controls for 2026

OWASP's Q1 2026 exploit round-up documents eight real-world AI agent security incidents, including a three-hour PyPI backdoor of the LiteLLM gateway that pulled an autonomous attack bot into roughly 4…

05:10
2026-10-07
dev.to
large-language-models

Structured outputs as application contracts

An AI engineer at a fintech startup replaced regex parsing of LLM chat output with JSON Schema-constrained structured outputs, treating the schema as an application contract that the model must satisf…

05:08
2026-10-07
dev.to
ai-agents

For an agent that runs on a schedule, silence has to mean no

Developer Maaz Kazi launched Locus, an Apache-2.0 system of persistent, named AI teammates ("Operatives") that run in their own container with a browser, filesystem and terminal, using the user's own …

05:07
2026-10-07
dev.to
ai-policy

UAE AI regulation for businesses: what you must do

A compliance guide outlines what UAE businesses must do to prepare for AI regulation, noting that the country has no single AI law and instead relies on a stack of data protection rules including the …

04:38
2026-10-07
dev.to
ai-agents

I let my AI agents merge to production. Once.

A developer who automated their entire CI/CD pipeline — including the final merge step — with AI agents describes how a fully closed-loop agent pipeline auto-merged and auto-deployed a write-path bug …

04:37
2026-10-07
dev.to
large-language-models

Why I put one thin layer between my app and every LLM provider

A developer described building a thin abstraction layer between their application and multiple LLM providers after finding API keys scattered across three places, duplicated retry logic, and no visibi…

04:06
2026-10-07
dev.to
ai-agents

Don't verify the agent. Verify the state.

A developer building StareBrain, a pre-launch Android AI agent that requires user confirmation before executing actions, argues that verifying an agent's own success reports creates a recursive trust …

04:05
2026-10-07
dev.to
ai-agents

I route Claude Code steps by decision type, not difficulty

A developer built a Claude Code plugin called maddog that routes each step of a task to a subagent on a model chosen by the kind of decision the step requires rather than by task difficulty. In 49 adv…

03:47
2026-10-07
dev.to
ai-infrastructure

Why the Outbox Pattern, Queue, and Embedding Worker?

A developer building the Second-Memory semantic search system decoupled memory creation from embedding generation using a transactional outbox pattern, a queue, and a dedicated embedding worker writin…

03:44
2026-10-07
dev.to
agent-protocols

MCP in Agentic AI vs Function Calling: MCP Wins

A developer argues that the Model Context Protocol (MCP) beats plain function calling for agentic AI teams whose agents must outlive a single model, framework or application, since one MCP server inte…

03:43
2026-10-07
dev.to
ai-infrastructure

LLM API Cost Monitoring in .NET: Best Practices for Production

A developer outlined a production pattern for LLM API cost monitoring in .NET, using a DelegatingHandler to capture usage.total_tokens and push metrics to Prometheus with a background reconciliation j…

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