Notes from production AI.
No vendor takes. Practical engineering writing on what actually works when you ship AI to real users — and what we've broken along the way.
33 articles · Updated Sep 8, 2026 · Subscribe via info@aiinfox.com
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AI Trends 2026: Six Development Trends Businesses Should Watch
The 2026 shift is from experiments to deployment. Six trends that decide what businesses build next: agents, multimodal, smaller models, RAG and security.
RAG AI Explained: How Retrieval-Augmented Generation Grounds Answers in Your Data
RAG retrieves from your documents before the model answers. How the two stages work, why it beats retraining, and what it does not fix on its own.
How AI Is Changing Customer Support: What to Automate and What to Keep Human
AI support handles the repeat questions and the out-of-hours tickets. The cases that need judgment still go to people, with the context already gathered.
AI Software Development: Building Custom Solutions That Fit the Business
AI software learns from data instead of following fixed rules. What it covers, when custom beats off-the-shelf and how to run the project so it delivers.
Conversational AI for Business: What It Is and Where It Pays Off
Conversational AI is not a scripted chatbot. Where it works in support, sales and internal operations, and how to design the hand-off to human agents.
AI Automation for Business Operations: What It Is and Where It Pays Off
AI automation handles the work rule-based systems cannot: variable input, judgment calls and prediction. Where it fits, where it does not and how to start.
Custom AI Development vs Off-the-Shelf: When Building Is the Right Call
Packaged AI tools fit typical problems. Custom AI development fits yours. How to tell which you need, and what to settle before you engage a partner.
AI Chatbot Development for Customer Support: What to Build and How
AI chatbots take the repeat questions off your support team. What goes into building one, where it helps and the design choices that decide whether it works.
AI Agent Development for Business Automation: What It Takes to Ship
AI agents automate whole workflows, not single steps. Here is how they are built, where they pay off and what a successful deployment needs.
Machine Learning Services: What They Cover and How to Buy Them Well
Machine learning services cover the whole model lifecycle, not just training. What they include, where they pay off, and how to start without overcommitting.
Voice AI for Business: What Replaces the IVR Menu
Voice AI replaces press-1 menus with agents that understand intent and take action. Where it works, where it fails, and what a build involves.
Generative AI vs Traditional AI: Which One Your Problem Needs
Traditional AI predicts and classifies. Generative AI produces new text, code and images. Where each fits, the risks, and how to choose for your problem.
AI Agent Observability in Production: What to Instrument Before Launch
Agents you cannot trace are agents you cannot debug. The 10-point observability checklist we instrument on every production agent engagement.
AI Development RFP Template: 12 Questions Every Vendor Should Answer in Writing
Most AI RFPs ask the wrong questions. The 12 that separate vendors who ship from vendors who pitch, with the answers that should disqualify.
AI Vendor Takeover Audit: 7 Signs Your Current Vendor Isn't Shipping
Most stuck AI engagements share the same seven symptoms. The checklist we run before a takeover, and the recovery that gets a system shipping in 4-8 weeks.
Australian Privacy Act and APPs for AI Development in 2026
The Privacy Act is the federal floor, APRA CPS 234 and CPS 230 the financial-services overlay, and the NDB clock is unforgiving. The checklist we run.
How to Evaluate Offshore Senior AI Engineers (Without Falling for Resume Theater)
Offshore AI hiring rounds optimize for the wrong signals. The interview pattern that surfaces who has shipped production LLM systems, and why take-homes fail.
Hiring an AI Development Company in the USA in 2026: What to Ask, What to Verify
Most AI vendors will not survive a real verification call. What US CTOs and VPs of Engineering should ask before signing, and what evidence to insist on.
LLM Evaluation Harness 101: How to Test an LLM Before Your Users Do
Most failed LLM engagements share one missing artifact: the eval set. How to build one, score against it and gate every prompt change in CI.
Offshore AI Development in 2026: What Actually Works and What Doesn't
Offshore AI in 2026 is not what offshore meant in 2014. Senior-only delivery, eval-first discipline and handoff-ready deliverables made the pyramid obsolete.
PIPEDA and Quebec Law 25 for AI in Canada: 2026 Compliance Checklist
PIPEDA is the federal floor. Quebec Law 25 is the strictest provincial overlay. OSFI E-23 sits on top for banks. Here is the checklist that ties them together.
RAG vs Fine-Tuning in 2026: Cost, Latency, and When to Pick Which
RAG is the default for most production AI in 2026. Fine-tuning is the right call in four narrow scenarios. Here is the cost math we run on discovery calls.
UK GDPR for AI Development: A Practical 2026 Guide
Most UK GDPR posts read like a legal essay. This is the engineering version: DPIAs, lawful bases, Article 22, transfers and erasure through embeddings.
Voice Agent ROI: The Real Cost Math Behind 4,000 Calls a Day
Voice agents run at 10-30 cents a call when built right and over a dollar when built wrong. The cost model behind a deployment doing 4,000 calls a day.
HIPAA-Compliant AI Deployment: A 12-Point Checklist
Every healthcare AI we have shipped passes the same 12 controls before a clinician sees it. BAAs, VPC isolation, audit logs, refusal layers, eval gating.
RAG Hallucination Rates: What Actually Moves the Needle
Most RAG hallucination guides mistake model choice for the lever. The ranked list of what actually drops hallucination rate in production RAG systems.
AI Development Companies in Mohali: The 2026 Ecosystem
A look at the Mohali AI ecosystem: what is being built, who is hiring, and where the next wave of production AI work is coming from.
When LLM Fine-Tuning Actually Pays Off
A cost, quality and data-residency decision tree. We have fine-tuned 12 models across healthcare, legal and EdTech. Here is what we learned.
Building an LLM Eval Harness from Scratch
What to evaluate, how to score it without humans in the loop on every change, and how to keep evals trustworthy as your prompts evolve.
Shipping RAG in Production: What Nobody Tells You
Vector search is the easy part. The hard parts are chunking, re-ranking, citations, refusals, and the eval suite that gates every prompt change.
Voice Agents Under One Second: The Latency Playbook
Latency budgets, streaming STT, speculative LLM responses, and TTS chunking. A practical playbook from production voice deployments holding 700-950ms p95.
Build Bounded Agents, Not Autonomous Ones
Open-ended agent loops are a debugging nightmare. Bounded recursion, explicit tool whitelists, and approval gates make agentic systems shippable.
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