<?xml version="1.0" encoding="UTF-8" ?><feed xmlns="http://www.w3.org/2005/Atom"><title>N-Gram House</title><link href="https://ingramhaus.com/"/><updated>2026-06-28T06:29:17+00:00</updated><id>https://ingramhaus.com/</id><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author><entry><title>Safety Policies for Legal Use of Generative AI: Lessons from Mata v. Avianca</title><link href="https://ingramhaus.com/safety-policies-for-legal-use-of-generative-ai-lessons-from-mata-v.-avianca"/><summary>Learn how to build robust safety policies for generative AI in legal settings using lessons from Mata v. Avianca. Discover why hallucinations happen, compare tools, and get a step-by-step verification guide.</summary><updated>2026-06-28T06:29:17+00:00</updated><published>2026-06-28T06:29:17+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Vibe Coding for Product Managers: How to Cut Time-to-Feedback in Half</title><link href="https://ingramhaus.com/vibe-coding-for-product-managers-how-to-cut-time-to-feedback-in-half"/><summary>Learn how product managers use vibe coding to cut time-to-feedback from weeks to hours. Explore tools, workflows, and best practices for AI-assisted prototyping in 2026.</summary><updated>2026-06-27T06:30:34+00:00</updated><published>2026-06-27T06:30:34+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Prompt Injection Risks in Large Language Models: Attacks and Defenses</title><link href="https://ingramhaus.com/prompt-injection-risks-in-large-language-models-attacks-and-defenses"/><summary>Prompt injection poses severe risks to LLM applications. Learn about attack types like DAN and HouYi, defense strategies including context partitioning, and industry trends shaping AI security in 2026.</summary><updated>2026-06-26T05:56:00+00:00</updated><published>2026-06-26T05:56:00+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Instruction Tuning for Large Language Models: Building Better Followers</title><link href="https://ingramhaus.com/instruction-tuning-for-large-language-models-building-better-followers"/><summary>Learn how instruction tuning transforms base LLMs into reliable assistants. We cover LoRA efficiency, data curation strategies, and the trade-offs between flexibility and accuracy.</summary><updated>2026-06-25T06:23:25+00:00</updated><published>2026-06-25T06:23:25+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Infrastructure as Code for Vibe-Coded Deployments: Repeatability by Design</title><link href="https://ingramhaus.com/infrastructure-as-code-for-vibe-coded-deployments-repeatability-by-design"/><summary>Learn how to combine vibe coding with Infrastructure as Code for secure, repeatable deployments. Discover best practices for AI-generated IaC, risk mitigation, and workflow automation.</summary><updated>2026-06-23T06:07:22+00:00</updated><published>2026-06-23T06:07:22+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Measuring and Reporting LLM Spend: Dashboards and KPIs That Matter</title><link href="https://ingramhaus.com/measuring-and-reporting-llm-spend-dashboards-and-kpis-that-matter"/><summary>Learn how to track and optimize LLM costs with essential KPIs like cost per completion and anomaly detection. Build dashboards that prevent budget overruns and prove AI ROI.</summary><updated>2026-06-22T07:05:42+00:00</updated><published>2026-06-22T07:05:42+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Grammar-Constrained LLM Outputs: A Guide for Enterprise Applications</title><link href="https://ingramhaus.com/grammar-constrained-llm-outputs-a-guide-for-enterprise-applications"/><summary>Explore Grammar-Constrained Decoding (GCD) for enterprise LLMs. Learn how enforcing syntax rules boosts accuracy in data extraction and logical reasoning without heavy fine-tuning.</summary><updated>2026-06-21T06:03:56+00:00</updated><published>2026-06-21T06:03:56+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Monolith or Microservices in Vibe Coding: How to Pick the Right Architecture</title><link href="https://ingramhaus.com/monolith-or-microservices-in-vibe-coding-how-to-pick-the-right-architecture"/><summary>Explore the trade-offs between monolithic and microservices architectures in the era of vibe coding. Learn how AI-assisted development influences your choice, when to scale, and how to optimize context windows for better code generation.</summary><updated>2026-06-20T06:00:17+00:00</updated><published>2026-06-20T06:00:17+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Retrieval-Augmented Generation (RAG) for LLMs: The Complete End-to-End Guide</title><link href="https://ingramhaus.com/retrieval-augmented-generation-rag-for-llms-the-complete-end-to-end-guide"/><summary>Learn how Retrieval-Augmented Generation (RAG) boosts LLM accuracy with real-time data. This end-to-end guide covers architecture, implementation steps, and best practices.</summary><updated>2026-06-19T06:26:00+00:00</updated><published>2026-06-19T06:26:00+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Fairness Testing for Generative AI: Metrics, Audits, and Remediation Plans</title><link href="https://ingramhaus.com/fairness-testing-for-generative-ai-metrics-audits-and-remediation-plans"/><summary>Learn how to test generative AI for bias using metrics like demographic parity, intersectional audits, and remediation strategies to ensure fair and compliant AI systems.</summary><updated>2026-06-18T06:00:01+00:00</updated><published>2026-06-18T06:00:01+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How Training Duration and Token Counts Affect LLM Generalization</title><link href="https://ingramhaus.com/how-training-duration-and-token-counts-affect-llm-generalization"/><summary>Explore how training duration and token counts impact LLM generalization. Learn why variable sequence lengths beat raw scale and avoid the generalization valley.</summary><updated>2026-06-17T05:59:03+00:00</updated><published>2026-06-17T05:59:03+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Safety and Harms Evaluation for Large Language Models in Production: A Practical Guide</title><link href="https://ingramhaus.com/safety-and-harms-evaluation-for-large-language-models-in-production-a-practical-guide"/><summary>A practical guide to LLM safety evaluation in production. Learn about key frameworks like CASE-Bench and HELM, regulatory compliance with the EU AI Act, and how to mitigate bias and toxicity risks.</summary><updated>2026-06-16T06:03:57+00:00</updated><published>2026-06-16T06:03:57+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>HumanEval and Code Benchmarks: How to Test LLM Programming Ability in 2026</title><link href="https://ingramhaus.com/humaneval-and-code-benchmarks-how-to-test-llm-programming-ability-in"/><summary>Discover how HumanEval and other code benchmarks test LLM programming ability. Learn about pass@k metrics, EvalPlus, and why execution-based evaluation matters for real-world AI coding tools.</summary><updated>2026-06-15T05:59:40+00:00</updated><published>2026-06-15T05:59:40+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Responsible AI Development for Generative Systems: Ethics, Bias, and Transparency</title><link href="https://ingramhaus.com/responsible-ai-development-for-generative-systems-ethics-bias-and-transparency"/><summary>Learn how to implement responsible AI development for generative systems. Cover ethics, bias mitigation, transparency frameworks, and compliance with 2026 regulations like the EU AI Act.</summary><updated>2026-06-14T05:53:18+00:00</updated><published>2026-06-14T05:53:18+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>The Hidden Cost of Generative AI: Training and Process Redesign</title><link href="https://ingramhaus.com/the-hidden-cost-of-generative-ai-training-and-process-redesign"/><summary>Discover the hidden costs of generative AI adoption. Learn how training and process redesign impact your budget, with data-driven insights on change management expenses.</summary><updated>2026-06-13T06:08:55+00:00</updated><published>2026-06-13T06:08:55+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Managed APIs vs Self-Hosted Models: Choosing the Right LLM Strategy for 2026</title><link href="https://ingramhaus.com/managed-apis-vs-self-hosted-models-choosing-the-right-llm-strategy-for"/><summary>Decide between managed APIs and self-hosted LLMs. We compare costs, privacy, performance, and control to help you choose the right AI strategy for 2026.</summary><updated>2026-06-12T05:52:27+00:00</updated><published>2026-06-12T05:52:27+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Self-Attention in Transformers: The Engine Behind Large Language Model Understanding</title><link href="https://ingramhaus.com/self-attention-in-transformers-the-engine-behind-large-language-model-understanding"/><summary>Discover how self-attention powers large language models. Learn the query-key-value mechanism, multi-head attention, and why transformers outperform RNNs in understanding context.</summary><updated>2026-06-11T05:55:47+00:00</updated><published>2026-06-11T05:55:47+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Generative AI in Logistics: Route Optimization, Exception Handling &amp; Status Updates</title><link href="https://ingramhaus.com/generative-ai-in-logistics-route-optimization-exception-handling-status-updates"/><summary>Discover how generative AI transforms logistics through dynamic route planning, intelligent exception handling, and automated customer status updates. Learn real-world impacts on cost, efficiency, and service.</summary><updated>2026-06-10T06:01:25+00:00</updated><published>2026-06-10T06:01:25+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How to Use Agent Plugins and Tools to Extend Vibe Coding Capabilities</title><link href="https://ingramhaus.com/how-to-use-agent-plugins-and-tools-to-extend-vibe-coding-capabilities"/><summary>Learn how to extend vibe coding with agent plugins and tools like Cursor, Cline, and Chrome extensions. Discover workflows, security tips, and best practices for 2026.</summary><updated>2026-06-09T06:05:12+00:00</updated><published>2026-06-09T06:05:12+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Compute Budgets and Roadmaps for Scaling Large Language Model Programs</title><link href="https://ingramhaus.com/compute-budgets-and-roadmaps-for-scaling-large-language-model-programs"/><summary>Learn how to build effective compute budgets and scaling roadmaps for LLM programs. Explore cost trends, hardware strategies, and inference optimization techniques to manage AI expenses in 2026.</summary><updated>2026-06-08T05:57:09+00:00</updated><published>2026-06-08T05:57:09+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How to Communicate Governance Without Killing Developer Velocity: Dos and Don'ts</title><link href="https://ingramhaus.com/how-to-communicate-governance-without-killing-developer-velocity-dos-and-don-ts"/><summary>Learn how to communicate software governance effectively without slowing down development. Discover dos and don'ts for balancing compliance, security, and developer velocity using platform engineering best practices.</summary><updated>2026-06-07T06:00:46+00:00</updated><published>2026-06-07T06:00:46+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Cut Generative AI Costs: How to Reduce Tokens Without Losing Context</title><link href="https://ingramhaus.com/cut-generative-ai-costs-how-to-reduce-tokens-without-losing-context"/><summary>Learn how to cut generative AI costs by 50% without losing context. Discover practical prompt optimization techniques, token pricing secrets, and model routing strategies to maximize ROI.</summary><updated>2026-06-06T05:58:30+00:00</updated><published>2026-06-06T05:58:30+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Public Sector Generative AI Policies: Procurement, Transparency, and Accountability in 2026</title><link href="https://ingramhaus.com/public-sector-generative-ai-policies-procurement-transparency-and-accountability-in"/><summary>Explore how public sector generative AI policies shape procurement, transparency, and accountability in 2026. Learn about federal mandates, state-level risks, and practical compliance steps.</summary><updated>2026-06-05T06:07:34+00:00</updated><published>2026-06-05T06:07:34+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Governance ROI for Generative AI: How to Cut Incidents and Pass Audits Faster</title><link href="https://ingramhaus.com/governance-roi-for-generative-ai-how-to-cut-incidents-and-pass-audits-faster"/><summary>Discover how Generative AI governance drives ROI by reducing incidents and accelerating audit readiness. Learn to transform compliance from a cost center into a strategic asset with policy-as-code and automated evidence.</summary><updated>2026-06-04T05:58:22+00:00</updated><published>2026-06-04T05:58:22+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Incident Response for AI-Introduced Defects and Vulnerabilities: A Practical Guide</title><link href="https://ingramhaus.com/incident-response-for-ai-introduced-defects-and-vulnerabilities-a-practical-guide"/><summary>A practical guide to incident response for AI-introduced defects and vulnerabilities, covering CoSAI frameworks, prompt injection, and data poisoning prevention.</summary><updated>2026-06-03T06:04:12+00:00</updated><published>2026-06-03T06:04:12+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How to Deploy Vibe-Coded Apps to Production Clouds in 2026</title><link href="https://ingramhaus.com/how-to-deploy-vibe-coded-apps-to-production-clouds-in"/><summary>Learn how to deploy AI-generated 'vibe coded' apps to production clouds securely. Compare Vercel, Netlify, and Cloudflare, and discover best practices for security and speed in 2026.</summary><updated>2026-06-02T05:55:29+00:00</updated><published>2026-06-02T05:55:29+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>E-Commerce Product Discovery with LLMs: Semantic Matching and Recommendations</title><link href="https://ingramhaus.com/e-commerce-product-discovery-with-llms-semantic-matching-and-recommendations"/><summary>Explore how LLMs transform e-commerce product discovery through semantic matching. Learn about vector databases, implementation strategies, and real-world impact on conversion rates.</summary><updated>2026-06-01T05:55:18+00:00</updated><published>2026-06-01T05:55:18+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>GDPR and CCPA in Vibe-Coded Systems: Data Mapping and Consent Flows</title><link href="https://ingramhaus.com/gdpr-and-ccpa-in-vibe-coded-systems-data-mapping-and-consent-flows"/><summary>Navigate GDPR and CCPA compliance in vibe-coded systems. Learn how to automate data mapping, design robust consent flows, and mitigate privacy risks in AI-generated code.</summary><updated>2026-05-31T06:04:19+00:00</updated><published>2026-05-31T06:04:19+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Error-Forward Debugging: How to Use LLMs and Stack Traces for Faster Fixes</title><link href="https://ingramhaus.com/error-forward-debugging-how-to-use-llms-and-stack-traces-for-faster-fixes"/><summary>Learn how Error-Forward Debugging uses LLMs to analyze stack traces for faster bug fixes. Discover tools, benefits, and risks of this emerging AI development technique.</summary><updated>2026-05-30T06:49:47+00:00</updated><published>2026-05-30T06:49:47+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Legal Basics for Vibe-Coded Apps: Copyright, Licensing, and IP Ownership</title><link href="https://ingramhaus.com/legal-basics-for-vibe-coded-apps-copyright-licensing-and-ip-ownership"/><summary>Navigate the legal complexities of vibe coding in 2026. Learn about copyright ownership, open-source license risks, and IP protection strategies for AI-generated apps.</summary><updated>2026-05-29T06:06:53+00:00</updated><published>2026-05-29T06:06:53+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How to Reduce Bias in LLMs: Data Cleaning and Training Strategies</title><link href="https://ingramhaus.com/how-to-reduce-bias-in-llms-data-cleaning-and-training-strategies"/><summary>Learn practical techniques to reduce bias in Large Language Models. From data augmentation to adversarial training, discover how to balance fairness and accuracy in your AI applications.</summary><updated>2026-05-28T06:07:14+00:00</updated><published>2026-05-28T06:07:14+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Why Startups, Agencies, and E-Commerce Lead Tech Adoption in 2026</title><link href="https://ingramhaus.com/why-startups-agencies-and-e-commerce-lead-tech-adoption-in"/><summary>Explore why startups, agencies, and e-commerce businesses are leading technology adoption in 2026. Discover how agility, low-code tools, and AI drive innovation faster than large enterprises.</summary><updated>2026-05-27T07:47:02+00:00</updated><published>2026-05-27T07:47:02+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Colorado SB24-205 Guide: Impact Assessments and AI Risk Management</title><link href="https://ingramhaus.com/colorado-sb24-205-guide-impact-assessments-and-ai-risk-management"/><summary>Colorado SB24-205 mandates strict AI governance for high-risk systems. Learn about impact assessments, risk management, and compliance deadlines for developers and deployers.</summary><updated>2026-05-25T06:10:33+00:00</updated><published>2026-05-25T06:10:33+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Evaluating Reasoning Models: Think Tokens, Steps, and Accuracy Tradeoffs</title><link href="https://ingramhaus.com/evaluating-reasoning-models-think-tokens-steps-and-accuracy-tradeoffs"/><summary>Explore the tradeoffs of reasoning models: how think tokens boost accuracy but skyrocket costs. Learn when to use LRMs, the limits of logical steps, and efficiency strategies like CTS.</summary><updated>2026-05-24T05:50:03+00:00</updated><published>2026-05-24T05:50:03+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Continuous Batching and KV Caching: Maximizing Throughput for LLMs</title><link href="https://ingramhaus.com/continuous-batching-and-kv-caching-maximizing-throughput-for-llms"/><summary>Learn how continuous batching and KV caching maximize LLM throughput. We explain the mechanics, compare static vs. dynamic batching, and highlight tools like vLLM and PagedAttention for efficient deployment.</summary><updated>2026-05-23T05:56:09+00:00</updated><published>2026-05-23T05:56:09+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Data Residency vs LLM Deployment: API vs Open-Source in 2026</title><link href="https://ingramhaus.com/data-residency-vs-llm-deployment-api-vs-open-source-in"/><summary>Navigate 2026 data residency laws for LLMs. Compare API vs open-source deployment choices under the EU AI Act and global regulations. Learn architectural strategies for compliance.</summary><updated>2026-05-22T06:21:38+00:00</updated><published>2026-05-22T06:21:38+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Pattern Libraries for AI: Mastering Vibe Coding with Reusable Templates</title><link href="https://ingramhaus.com/pattern-libraries-for-ai-mastering-vibe-coding-with-reusable-templates"/><summary>Learn how pattern libraries and rules files transform vibe coding into reliable software architecture. Discover how to configure AI assistants like Cursor and Copilot for secure, consistent code.</summary><updated>2026-05-21T05:58:05+00:00</updated><published>2026-05-21T05:58:05+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Legal Services and Generative AI: Document Automation, Contract Review, and Knowledge Management</title><link href="https://ingramhaus.com/legal-services-and-generative-ai-document-automation-contract-review-and-knowledge-management"/><summary>Explore how generative AI transforms legal services through document automation, contract review, and knowledge management. Learn about top platforms, efficiency gains, and implementation best practices for 2026.</summary><updated>2026-05-20T06:00:49+00:00</updated><published>2026-05-20T06:00:49+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Documentation Architecture: Using ADRs and Decision Logs for AI-Generated Systems</title><link href="https://ingramhaus.com/documentation-architecture-using-adrs-and-decision-logs-for-ai-generated-systems"/><summary>Learn how to use Architecture Decision Records (ADRs) with AI assistance to document software choices. Discover workflows that reduce documentation time by 73% and avoid common pitfalls in AI-generated decision logs.</summary><updated>2026-05-19T05:59:08+00:00</updated><published>2026-05-19T05:59:08+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How Vibe Coding Redefines the Role of Software Engineers in 2025</title><link href="https://ingramhaus.com/how-vibe-coding-redefines-the-role-of-software-engineers-in"/><summary>Vibe coding transforms software engineering from manual coding to AI orchestration. Learn how developers adapt, top tools compare, and strategies to avoid technical debt in 2025.</summary><updated>2026-05-18T06:14:57+00:00</updated><published>2026-05-18T06:14:57+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Mathematical Reasoning Benchmarks for Next-Gen Large Language Models: Beyond Accuracy</title><link href="https://ingramhaus.com/mathematical-reasoning-benchmarks-for-next-gen-large-language-models-beyond-accuracy"/><summary>Explore how next-gen LLMs perform on mathematical reasoning benchmarks. While scores on GSM8k and MATH are high, perturbation tests reveal deep flaws in generalization and proof generation.</summary><updated>2026-05-17T05:54:58+00:00</updated><published>2026-05-17T05:54:58+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Setting Expectations Responsibly: A Guide to User Education on LLM Limitations</title><link href="https://ingramhaus.com/setting-expectations-responsibly-a-guide-to-user-education-on-llm-limitations"/><summary>Explore essential strategies for educating users on LLM limitations, including mitigating hallucinations, addressing algorithmic bias, and preventing overreliance through transparent, practical training methods.</summary><updated>2026-05-16T06:38:55+00:00</updated><published>2026-05-16T06:38:55+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Task Decomposition Strategies for Planning in Large Language Model Agents</title><link href="https://ingramhaus.com/task-decomposition-strategies-for-planning-in-large-language-model-agents"/><summary>Explore task decomposition strategies for LLM agents, including ACONIC, Chain-of-Code, and Task Navigator. Learn how breaking down complex tasks improves accuracy by up to 40% and reduces costs.</summary><updated>2026-05-15T06:00:04+00:00</updated><published>2026-05-15T06:00:04+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How Generative AI Drives Revenue: Cross-Sell, Upsell, and Conversion Lifts in 2026</title><link href="https://ingramhaus.com/how-generative-ai-drives-revenue-cross-sell-upsell-and-conversion-lifts-in"/><summary>Discover how generative AI drives revenue through personalized cross-sell and upsell strategies. Learn about conversion lifts, implementation costs, and real-world ROI stats for 2026.</summary><updated>2026-05-14T06:25:37+00:00</updated><published>2026-05-14T06:25:37+00:00</published><category>Business AI Strategy</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Hardware Constraints That Limit Scaling for Large Language Models: The Physical Wall</title><link href="https://ingramhaus.com/hardware-constraints-that-limit-scaling-for-large-language-models-the-physical-wall"/><summary>Explore the physical hardware limits stopping Large Language Models from growing infinitely. From GPU memory walls to data center power caps, discover why scaling AI is harder than it looks.</summary><updated>2026-05-13T06:02:27+00:00</updated><published>2026-05-13T06:02:27+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Evaluating Vibe Coding Tools: The Essential Buyer's Checklist for 2025 and Beyond</title><link href="https://ingramhaus.com/evaluating-vibe-coding-tools-the-essential-buyer-s-checklist-for-2025-and-beyond"/><summary>A comprehensive buyer's checklist for evaluating vibe coding tools in 2025 and 2026. Compare top AI assistants like Cursor, Windsurf, and GitHub Copilot based on security, context, and agentic capabilities.</summary><updated>2026-05-12T06:03:03+00:00</updated><published>2026-05-12T06:03:03+00:00</published><category>Software Development</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Temperature Tuning for LLMs: How to Balance Creativity and Precision</title><link href="https://ingramhaus.com/temperature-tuning-for-llms-how-to-balance-creativity-and-precision"/><summary>Master LLM temperature tuning to balance creativity and precision. Learn how temperature, top-p, and top-k work together to control AI output for code, writing, and data tasks.</summary><updated>2026-05-11T06:00:26+00:00</updated><published>2026-05-11T06:00:26+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Secure Vibe Coding: Security Basics for Non-Technical Builders</title><link href="https://ingramhaus.com/secure-vibe-coding-security-basics-for-non-technical-builders"/><summary>Learn essential security basics for non-technical builders using vibe coding platforms. Protect your AI-generated apps from secret exposure, XSS, and other vulnerabilities with practical tips.</summary><updated>2026-05-10T05:56:26+00:00</updated><published>2026-05-10T05:56:26+00:00</published><category>AI Security</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>Stochastic Depth in LLMs: How Random Layer Dropping Boosts Performance</title><link href="https://ingramhaus.com/stochastic-depth-in-llms-how-random-layer-dropping-boosts-performance"/><summary>Explore how stochastic depth improves LLM training by randomly dropping transformer layers. Learn about neural collapse, regularization synergies, and practical implementation tips for building robust, efficient models.</summary><updated>2026-05-09T05:58:50+00:00</updated><published>2026-05-09T05:58:50+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry><entry><title>How Quantization-Friendly Transformers Enable Edge LLMs in 2026</title><link href="https://ingramhaus.com/how-quantization-friendly-transformers-enable-edge-llms-in"/><summary>Explore how quantization-friendly transformer designs enable Large Language Models to run efficiently on edge devices. Learn about PTQ, QAT, and latest precision formats like NVFP4.</summary><updated>2026-05-08T06:01:19+00:00</updated><published>2026-05-08T06:01:19+00:00</published><category>Machine Learning</category><author><name>Nicholas Barasa</name><uri>https://ingramhaus.com/author/nicholas-barasa/</uri></author></entry></feed>