AI agents - Peter Jonathan Wilcheck

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Values-Based Marketing in the Age of AI Agents: Earning Verifiable Trust

October 16, 2026Category : Business and AI Agents

Tags : Agent Discovery Agent Shoppers agentic commerce AI agents Brand Authenticity Brand Transparency Brand Trust Brand Values Consumer Trust Greenwashing Machine-Readable Marketing Structured Data Trust Marketing Values-Based Marketing Verified Claims

When a shopping agent, not a person, first meets your brand, values-based marketing becomes machine-readable: agents rank products on availability, price, and quality, so a values claim that lives only in a manifesto never appears. A practical look at brand trust in the agent era.

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How AI Agents Learn to Reason

July 27, 2026Category : AI Agent Development

Tags : Agent Training AI agent development AI agents DeepSeek R1 GRPO LLM Training Machine Learning Model Alignment Process Reward Models Reasoning Models Reinforcement Learning Reward Functions RLHF RLVR Verifiable Rewards

The trustworthiness of AI agents deployed in production depends on the rigor of their training methodologies. Traditionally, reinforcement learning from human feedback (RLHF) has been used, where human evaluators rank model responses to guide preferred behaviors. However, human preference is slow, costly, subjective, and does not guarantee correctness. Reinforcement learning from verifiable rewards (RLVR) offers.. Read more

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Non-Human Identity AI Agents: Why Every AI Agent Needs Its Own Verifiable Credential

July 24, 2026Category : Agentic AI

Tags : Access Control Agent Security agentic AI AI agents API Keys Credential Management Cybersecurity.Identity Governance Least Privilege Machine Identity NHI Non-Human Identity OAuth Tokens OWASP Service Accounts

AI agents that interact with calendars, databases, or support ticketing systems do so using credentials such as API keys, service accounts, OAuth tokens, or certificates. Security teams refer to these as non-human identities (NHIs), which have become the largest identity population within most enterprises. Recent industry research indicates that the ratio of machine identities to.. Read more

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Scaling Agentic AI: Turning Successful Pilots Into Production Systems

July 24, 2026Category : Business and AI Agents

Tags : agentic AI AI Adoption AI agents AI Cost Management AI Governance AI Observability AI Operations AI Pilot to Production AI Reliability AI Scaling AI Strategy AI Studio enterprise AI LLMOps production AI

Most companies have now deployed an AI agent that delivers impressive demonstrations. For example, a procurement agent can draft a request for quote in seconds, a support agent can resolve a tier-one ticket autonomously, and a finance agent can reconcile accounts overnight. The challenge is not the demo itself, but what follows: after the pilot.. Read more

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Self-Healing Automation: How AI Agents Adapt When Interfaces Change

July 24, 2026Category : Agentic AI Technology

Tags : agentic AI AI agents automation reliability Continuous Testing locator healing Machine Learning natural language testing QA Automation self-healing automation semantic matching software testing Test Automation test maintenance UI testing visual testing

Self-healing automation lets AI agents notice when a UI element moves or changes, find it again on their own, and keep working. A practical look at the healing loop, three generations from locators to semantics, where agentic reasoning goes further, and what it still cannot fix.

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Vertical AI Agents: Why Domain-Specific Models Beat Generalists for Business ROI

July 24, 2026Category : Business and AI Agents

Tags : AI Adoption AI agents AI Compliance AI ROI AI Strategy Business AI Domain-Specific Models enterprise AI Fine-Tuning Generative AI Industry AI LLMs Machine Learning small language models Vertical AI

For most business work, a smaller model tuned to one domain now beats a general-purpose giant. A practical look at why vertical AI agents win on accuracy, cost, and compliance — and how to adopt them without overbuilding.

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Edge AI Hosting: On-Device and Hybrid Deployment for AI Agents

July 24, 2026Category : Hosting Services for AI Agents

Tags : AI agents AI hosting AI latency edge AI edge cloud edge computing edge hosting edge inference hybrid AI local AI inference model deployment NPU on-device AI on-prem AI small language models

Most AI agents still live in the cloud, but a growing class of work is moving to the device and the network edge. A practical look at why edge AI hosting wins on latency, cost, privacy, and resilience — the three edge layers, what a hosting platform provides, and when to keep an agent local.

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Autonomous Decision Execution: How AI Agents Take Action Without Waiting

July 20, 2026Category : Agentic AI

Tags : Agent Autonomy agentic AI AI agents AI Automation AI Compliance AI Governance AI Infrastructure AI security Autonomous AI Business Automation Decision Automation enterprise AI Human in the Loop Machine Learning Risk Management

Most AI deployments through 2025 followed a simple pattern: the model recommends, a person decides, and someone else clicks the button. That pattern is breaking down. A growing share of production agents now skip the last two steps entirely for low-stakes work, evaluating a situation and executing the resulting action — sending the email, updating.. Read more

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FinOps for AI Agents: How to Control Token and Hosting Costs

July 20, 2026Category : Hosting Services for AI Agents

Tags : AI agent observability AI agents AI cost optimization AI Governance AI inference cost AI Infrastructure AI ROI cloud cost management cost per inference FinOps for AI GPU Infrastructure Inference Hosting model routing token budget token economics

The economics of an AI agent look nothing like the economics of the software it replaces. A traditional web service scales roughly with users; an agent scales with steps. Each retrieval, tool call, and reasoning loop burns tokens, and a single user request can quietly trigger dozens of model calls. Add always-on GPU capacity, shared..

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Continuous AI Playtesting: How Cloud Bots Catch Bugs Before Launch

July 20, 2026Category : Game Hosting

Tags : AI agents AI in Gaming AI Playtesting Automated Testing Bug Detection Cloud Gaming Cloud QA Continuous Testing Game Bots Game Development Game Hosting Game Quality Assurance Game Server Testing Game Testing Machine Learning QA Overnight Testing QA Automation Regression Testing Reinforcement Learning Test Automation

Continuous AI playtesting runs reinforcement-learning bots against game builds around the clock in the cloud, catching crash bugs and state errors before players ever see them. A practical look at how it works, the GPU infrastructure behind it, and what it still can’t replace.

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Values-Based Marketing in the Age of AI Agents: Earning Verifiable Trust

How AI Agents Learn to Reason

Non-Human Identity AI Agents: Why Every AI Agent Needs Its Own Verifiable Credential

Scaling Agentic AI: Turning Successful Pilots Into Production Systems

Self-Healing Automation: How AI Agents Adapt When Interfaces Change

Vertical AI Agents: Why Domain-Specific Models Beat Generalists for Business ROI

Edge AI Hosting: On-Device and Hybrid Deployment for AI Agents

Autonomous Decision Execution: How AI Agents Take Action Without Waiting

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