AgentForge: LLM Workflow Reliability Platform
18 Signals

AgentForge: LLM Workflow Reliability Platform

A development and observability platform for building, testing, and hardening LLM-powered agent workflows against real-world data failures.

Added May 24, 2026

Developer Tools
AI Infrastructure
LLMOps

Opportunity score

60

/ 100

Medium opportunity

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The Problem

Engineering teams are increasingly building LLM-powered agents and multi-agent workflows, but these systems consistently break when they encounter messy, real-world data and production edge cases. Developers lack robust tooling to identify where LLMs fail against real data, debug agent decision paths, and reliably orchestrate tool-using workflows in production.

Potential Solution

AgentForge provides a unified platform for designing, testing, and monitoring LLM agent workflows with built-in failure detection against real data inputs. It includes agent orchestration primitives, RAG pipeline testing, support for agent-to-agent (A2A) protocols, and observability dashboards that surface where LLMs break so engineers can harden workflows before deployment.

Why Now?

Major enterprises across data, security, fintech, and observability are simultaneously hiring engineers to build production agent workflows, but tooling for reliability and debugging at the agent layer remains immature relative to demand.

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Showing 1-20 of 20 signals

Job adsSep 23, 2026
micron-semiconductor-asia-operations-pte-ltd-201815216z
Member of Technical Staff - Agentic AI Architect

Implement Agentic frameworks to orchestrate LLM interactions with internal APIs, databases, and software tools. Build and maintain agent evaluation harnesses to benchmark agent accuracy, reliability, and task success across complex, multi-step workflows.

Job adsSep 2, 2026
bytedance
AIOps R&D Engineer Graduate (Video and Edge) - 2027 Start

- Build and continuously improve intelligent Agents powered by Large Language Models (LLMs). Apply Prompt Engineering, RAG, MCP, Skills, multi-Agent orchestration, tool calling, and related techniques to intelligent fault diagnosis, root cause analysis, automated remediation, and intelligent customer service.

Job adsSep 2, 2026
amazon
Software Development Engineer, Benefits Technology

• Build generative-AI in production, not beside it: LLM-backed evaluation, multi-agent workflows where specialized agents reason from different perspectives and assemble the evidence, retrieval over claims and reference data, and the test harnesses that keep model behavior predictable.

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