Camunda announces ProcessOS, an agentic operating system for AI-first enterprise transformation
Agentic orchestration platform provider has announced ProcessOS, a new intelligence layer that the company says leads into “the great re-engineering” of processes and concurrent workflows.
According to the company, to move past mere AI task assistance, companies will need to rethink about which tasks should be done, and whether agents or humans should perform them. “Just bolting AI onto legacy processes compounds technical and organizational debt, adding complexity, fragility, and cost. AI-first process transformation must work backwards from outcomes, not forward from current reality,” Camunda wrote in its announcement.
Built for enterprise deployment, ProcessOS ensures full governance and control:
- Verification by design: visual process models clearly show which steps are performed by AI, under which conditions, and which steps involve humans
- Human in the loop for any change: every process modification is reviewed and approved by humans before it reaches production
- Re-use and learning built in: ProcessOS prioritizes approved process patterns and connectors, improving with each human feedback loop
ProcessOS runs natively on AWS, with deep integration into Amazon Bedrock and Amazon Bedrock AgentCore for foundation models, agent memory, identity, and gateway services. Camunda is available on AWS Marketplace with production-ready reference architectures for Amazon EKS, ECS, and EC2.
ProcessOS is available in closed beta for selected enterprises beginning today. Organizations can register their interest to participate at camunda.com/process-os.
Hadrian Releases OpenHack, Democratizing AI Vulnerability Discovery
Hadrian has released OpenHack, an open-source tool for AI-powered source code review that works within Claude Code, Codex, and Cursor.
The temptation when you give a strong LLM a codebase is to let it improvise. “Read this repo and tell me what’s vulnerable.” It will produce something. The output will be a mixture of plausible bugs, hallucinated bugs, real bugs explained wrongly, and the occasional sharp insight. Triage takes longer than just reading the code yourself.
We’ve found two failure modes drive most of that noise:
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Unscoped prompts. The agent doesn’t know what question it’s answering, so it answers all of them at low confidence.
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Self-graded findings. The same agent that proposed the bug decides whether the bug is real. There’s no independent check.
The workflow of OpenHack is designed around fixing those two things. Reviews are scenario-first: every unit of agent work is exactly one routing unit, one expert, and one proof question. And the agent that proposes a finding is not the agent that admits it.
How OpenHack works:
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Scenario-based scoping. Every unit of work is one routing unit, one expert, and one specific proof question. No unscored prompts asking the model to find anything wrong.
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Independent triage. The agent that proposes a finding is not the agent that admits it. A separate triage agent reviews each candidate against the original evidence before it becomes a recorded finding.
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Inspectable artifact trail. Recon output, scenario backlogs, expert results, triage decisions, and findings all live as plain files on disk. The full review is auditable end to end.
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Harness-agnostic, model-agnostic. Runs inside Claude Code, Codex, or Cursor, with any model the harness supports.
OpenHack is available immediately at github.com/hadriansecurity/
Devart releases dbForge 2026.1
The AI-powered capabilities of dbForge
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Conversion of natural language to SQL
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Context-aware SQL query generation
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Optimization of pre-written SQL queries
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Detection of redundant or missing indexes
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Detailed SQL explanations
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Error analysis and troubleshooting
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Integrated AI chat for questions related to databases and SQL.
dbForge 2026.1 is available today for dbForge Edge, dbForge
