Leah Adds Natural Language Harness to AI Software Factory

Leah has added Harness Builder to its Maestro platform, enabling professional developers and business users to create applications through natural language prompts. By combining AI agents, software factory workflows and governance controls, the company aims to simplify application development while helping organizations maintain security, consistency and oversight…

Mike Vizard Nov 6, 2026

Blitzy Partners with Microsoft Frontier Company to Bring AI to Azure Workload Migrations

Blitzy, a provider of an artificial intelligence model that establishes the relationship between all the software artifacts in an IT environment, today announced it has allied with the Microsoft Frontier Company to help DevOps teams refactor existing applications in a way that makes it simpler to move them to the Microsoft Azure cloud service. As…

Mike Vizard Nov 5, 2026

Meta Acquires Conductor to Support Multi-Agent AI Coding

Meta has acquired AI coding startup Conductor, a deal that extends the social media giant’s developer tools portfolio as it competes with OpenAI and other leading AI vendors. Conductor’s platform enables software developers to manage multiple AI coding agents working on different tasks within a single project. While individual AI coding assistants can generate and…

James Maguire Nov 5, 2026

Blogs

OpenAI Acquires Pierre Computer to Expand Codex, Challenge GitHub

OpenAI has announced plans to acquire developer tools startup Pierre Computer, a deal that will expand the capabilities of its Codex AI coding platform and position the company as a more direct competitor to Microsoft’s GitHub. The acquisition will bring Pierre’s Code Storage technology into Codex, enabling OpenAI to offer more of the infrastructure needed…

James Maguire Nov 4, 2026

Featured Reports

DevOps.com Research

The State of Observability 2026: Bigger Budgets, Higher Stakes and the Rise of the Agent

Observability budgets are climbing fast: a Futurum Group survey of 628 enterprise IT leaders reported by DevOps.com found 36% plan to spend more than $1 million on observability in 2026, with 7% planning to spend more than $5 million. This report draws on Futurum Group research, Enterprise Technology Research (ETR) spending-intention data, practitioner reporting from DevOps.com, Cloud Native Now and PlatformEngineering.com, and executive interviews and webinars from Techstrong TV and Techstrong Learning. Five findings stand out: spending is moving up-market; cost control is the central operational problem; no enterprise has a truly unified platform; AI observability has become a buying priority before agents are widely deployed; and platform engineering is becoming the delivery vehicle for observability.

Techstrong EditorialUpdated November 5, 202616 min read

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DevOps.com Research

The State of AI Coding in DevOps Workflows

Coding using artificial intelligence (AI) tools is no longer an experiment for DevOps teams. It is the new operational reality. Futurum Research, for example, finds that 76.6% of organizations actively use AI in development workflows and another 20.4% are evaluating it. The ETR arm of the Futurum Group, meanwhile, is reporting that 93% of AI coding tool users report measurable productivity gains, which ETR calls the strongest signal of tangible return from investments in AI. This report draws on Futurum Group research, Enterprise Technology Research (ETR) data, practitioner reporting from DevOps.com, Cloud Native Now and PlatformEngineering.com, and executive interviews and webinars from Techstrong TV and Techstrong Learning. Four findings stand out: AI coding adoption has reached critical mass; the bottleneck has moved from writing code to reviewing and verifying it; coding agents are privileged software that widen the supply chain; and platform engineering is becoming the control plane for AI-generated code.

Techstrong EditorialUpdated November 5, 202616 min read

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Mayank JainNov 9, 2026

I Don’t Just Manage Engineers Anymore. I Manage Agents Like a Team

AI coding agents are no longer just productivity tools. They’re becoming active members of engineering teams, opening pull requests, triaging tickets and handling operational tasks. But managing them requires more than better prompting. Engineering leaders must establish clear assignments, standing orders, automated verification and feedback loops that turn autonomous agents into reliable contributors without sacrificing human judgment.

Agent OrchestrationAgentic AI

Mike VizardNov 6, 2026