Your First 30 Days with an AI Consultant: A Step-by-Step Process
The AI consulting process is set in the first 30 days: discovery, data analysis, roadmap, and the first pilot. A clear, week-by-week answer to what to expect.
30 min
Blog archive
Showing 25–48 of 540 articles, newest first.
AI Consulting Contract: Scope, Intellectual Property, Data and SLA Clauses
How to write an AI consulting contract? A clause-by-clause template and checklist for scope, intellectual property, data/KVKK, SLA, fee and termination clauses. (Not legal advice.)
30 min
Independent Consultant vs Agency vs In-House Team: Total Cost and Risk Comparison
A decision guide comparing an independent AI consultant, an AI consulting agency, and building an in-house team across total cost of ownership, speed, risk, and knowledge transfer.
30 min
Who Is an AI Trainer and How to Choose One? An Evaluation Framework for Organizations
How do you choose an AI trainer? A five-dimension evaluation framework for enterprises: selection criteria, academic vs practitioner, portfolio checks, and how to verify claims before you sign.
30 min
Enterprise AI Consulting: Service Scope, Process, and Delivery Models
What does enterprise AI consulting cover? Service scope components, the consulting process from discovery to scaling, and project/retainer/embedded-team delivery models explained end to end.
30 min
AI Consulting Fees 2026: Pricing Models, Scope, and Budget Guide for Türkiye
How are AI consulting fees set in 2026? Pricing models, budget ranges by scope, hidden costs, and ROI, all in this comprehensive guide for Türkiye.
30 min
Field Note
Field Note: What I Have Seen in Projects Without Executive Support
What happens to enterprise AI projects without sponsor support? A field note on budget erosion, slowing decisions, resistance, and how to keep a project alive.
30 minStrategy
Deep Dive
Does Microlearning Work in Enterprise AI Training?
Does microlearning work in enterprise AI training? The retention advantage of short modules, its limit on complex topics, and a practical decision guide for choosing the right format.
30 minSkills
Comparison
Model Serving: Serving-Layer Options and Selection Criteria
What is model serving? A guide to the serving layer: from managed APIs to self-hosted inference servers like vLLM, TGI and Ollama; batching, streaming, concurrency, throughput and latency trade-offs.
30 minLLMOps
Guide
Building an AI Roadmap: A 12-Month Phased Plan
How to build an AI roadmap? A 12-month phased plan: foundation, first use case, expansion and scale phases, gate criteria for each phase, and realistic milestones.
30 minStrategy
Analysis
The AI Ecosystem in Türkiye: Actors and Gaps
How is Türkiye's AI ecosystem? A guide to the actors — startups, enterprises, academia-industry, public sector, investors — their strengths, gaps, and the talent pool.
30 minTurkey
Deep Dive
Operationalizing AI Ethics Principles: From Values to Controls
AI ethics is not a poster of principles; this guide turns each principle into a control point, a testable criterion, an assigned owner, and an auditable trail across the delivery lifecycle.
30 minGovernance
Explainer
What Is Chain of Thought? A Complete Guide to Step-by-Step Reasoning
What is chain of thought? Chain of thought is a reasoning method where a language model answers a question by thinking step by step. When it helps, when it doesn't, and how reasoning models changed it.
30 minPrompt
Deep Dive
Metadata Design: The Foundation of Filtering in RAG
Metadata design is the foundation of retrieving the right chunk for the right user in RAG: the required field set, authorization scope, date and version fields, and filtered retrieval quality.
30 minRAG
Deep Dive
Multi-Agent Systems: When Are They Really Necessary?
When is a multi-agent system really necessary? The single-agent vs multi-agent decision, agent division of labor, coordination cost, error propagation, and orchestration patterns for enterprise AI.
30 minAgents
Guide
AI for Software Developers: How Is the Role Changing?
How is the software developer's role changing in the age of AI? Code-assistant impact, rising review load, the shifting role, and the new skills to learn — in this guide.
30 minSkills
Field Note
Field Note: Unexpected Delays During the Integration Phase
An integration-delay experience from the field. Why do legacy system APIs, data access permissions, missing test environments and data-mapping exceptions push project timelines?
30 minLLMOps
Explainer
What Is a Use Case? How to Define One
What is a use case? A definition of a business problem in which an actor, given a trigger and defined input, reaches a measurable output — with a success metric and clear scope.
30 minUse Cases
Deep Dive
The False-Alarm Economy in Computer Vision Models
The false-alarm economy in computer vision models: the differing cost of false positives and negatives, threshold tuning, the sensitivity-specificity trade-off, and managing operator load in production.
30 minUse Cases
Deep Dive
LLM Monitoring in Production: What to Log, What to Alert On
LLM monitoring is the discipline that makes a production language-model system's quality, cost, and performance visible through logging, tracing, and alerts. What to log and how to measure it.
30 minLLMOps
Analysis
Small Models or Large Models? Which Way the Trend Is Heading
Small language model or large model? An enterprise decision framework in light of task-based selection, the cost-performance balance, and the hybrid architecture trend.
31 minLLMs
Deep Dive
Measuring Training Impact: From Participation to Behavior Change
How is training impact measured? Four measurement levels from satisfaction to behavior change, tracking learning transfer, and an evidence-collection playbook.
30 minSkills
Explainer
What Is Quantization? The Cost of Shrinking a Model
What is quantization? Quantization is a model-compression technique that represents a model with fewer bits to save memory and gain speed, at the price of a measurable quality loss. INT8, INT4, PTQ, QAT and more.
30 minLLMs
Deep Dive
Automated Decision-Making and the Right to Object: A KVKK Perspective
What is automated decision-making, which decisions fall under KVKK, and how are the right to object, human intervention, and transparency ensured? A practical design guide.
30 minGovernance