Ideas for building
better software.

Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 Super

Autonomous vehicle (AV) development often relies on separate models for trajectory generation, high-level intent prediction, scene understanding, and data... Autonomous vehicle (AV) development often relies on separate models for trajectory generation, high-level intent prediction, scene understanding, and data labeling. This separation makes it hard to compare related outputs, investigate model behavior, and reuse the same representations across the development workflow. NVIDIA Alpamayo 2 Super

Oligo Raises $60 Million for Runtime Security

The company will use the investment to accelerate product innovation and expand go-to-market operations. The post Oligo Raises $60 Million for Runtime Security appeared first on SecurityWeek.

Accelerate CloudFormation development with the IaC MCP Server

Walk through a complete CloudFormation development cycle - authoring, validation, deployment, and troubleshooting - without leaving your AI assistant, using the AWS IaC MCP Server.

2027 Chevrolet Corvette Grand Sport X proves code is as important as hardware

Chevy's 721-hp hybrid ups the ante with few compromises, but at a steep cost.

CISO Conversations: Russ Kirby – Passion Is the Antidote to Burnout

Russ Kirby, CISO at Ping Identity, shares how passion, courage, and “good enough” thinking shaped his path from HP to the C-suite—and what keeps him up at night. The post CISO Conversations: Russ Kirby – Passion Is the Antidote to Burnout appeared first on SecurityWeek.

Varonis Agent IBAC keeps AI agents within their intended boundaries

AI agents need broad access to be useful, but traditional access controls cannot determine whether an action aligns with a user's intent. Varonis explains how Agent IBAC detects intent drift and enforces real-time guardrails to keep agents within their intended boundaries. [...]

Understanding Agentic SDLC: The Future of Software Engineering

Agentic SDLC, or agentic software development life cycle, is the next major shift in how I think about building and shipping software. It is not simply AI writing a few lines of code inside an IDE. It is an end-to-end approach where specialized AI agents participate across planning, implementation, testing, review, deployment, monitoring, documentation, and continuous improvement. The core idea is straightforward: I set the goal, the priorities, guardrails, and approval points. Agents do the ope

Deploy local agents everywhere with LFM2.5-2.6B