HeyJaredIsaac Sacolick
- Indexed articles, last 90 days
- 7
- Latest publication
- Sep 30, 2026
- Outlet visibility, for InfoWorld
- Top 500K sites
- Earliest in this view
- Jul 7, 2026
Latest articles
Validating AI models and agents with property-based testing (opens the original)
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Testing deterministic systems is relatively straightforward. Create an assertion that the system should pass, and automate validating it against a series of input-to-output data patterns. When new test patterns are needed, use observability sources to extract them from actual usage data or to create synthetic test data. But testing AI models and agents with nondeterministic outputs doesn’t align with this form of unit testing. For example, say you are using a language model to categorize a strin
Seven critical vibe coding mistakes — and how to avoid them (opens the original)
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Vibe coding an application or an AI agent sounds too good to be true. A single developer prompts their way through a plan and has the code for a working prototype in minutes instead of days. Fixes and improvements come through iteration until the developer is satisfied with the results. According to the State of Code Developer Survey, 48% of respondents have adopted vibe coding for new projects, and 62% say it’s effective. But 96% don’t fully trust that AI-generated code is functionally correct.
AI inference: Five best practices for successful AI applications (opens the original)
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While some organizations are still getting started with their AI strategies, others are in pilot purgatory, with few experiments or proofs of concept (POCs) reaching production. Only 25% of organizations have moved 40% or more of their AI experiments into production, according to The State of AI in the Enterprise. We discussed delivering AI proofs of concept that matter at a recent Coffee With Digital Trailblazers on LinkedIn Live. One key reason POCs stumble is when they don’t align well with t
Five ways to evaluate AI agent orchestration platforms (opens the original)
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AI agent orchestration platforms coordinate role-based and task-based AI agents, along with the tools, data, and people they depend on, into multistep workflows. These platforms are highly important for organizations scaling from handfuls to thousands of AI agents running in production. Two open standards do the connective work: MCP (Model Context Protocol) gives agents governed access to tools and data, while A2A (Agent2Agent) lets agents discover and delegate to one another, including agents b
How AI impacts site reliability engineering (opens the original)
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Site reliability engineers (SREs) have the tough assignment of resolving thorny performance and reliability issues. But their primary mission is to provide devops teams with operational insights and to suggest implementation improvements on business system performance, security, and overall robustness. Google introduced its SRE playbook in 2003, but it took some time for the role’s definition, tools, and techniques to become mainstream. Startups were the first to adopt observability for cloud-na
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Top 500K sites
For InfoWorld, the outlet · Measured Aug 1, 2026
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