Cover
Photo: StockSnap (CC0)
Spotlight
PAGE: https://alison.com/course/the-fundamentals-of-chat-gpt-ai-language-model
PROMISE: Build general AI literacy to judge if a specific model suits a development workflow.
WHO: Small business owners or devs evaluating AI IDEs who lack general AI context.
WHYNOW: AI feature bloat in developer tools makes verifying model fit essential before purchase.
DESC: Learn how to use ChatGPT and boost your productivity with the chatbot’s AI and ability to solve math problems, write text that seems human-like and more.
BEFORE: You browse IDEs and get lost in jargon about models and tiers.
BEFORE: You assume all AI coding assistants work the same way.
BEFORE: You hesitate to buy tools because you do not know if the AI fits your needs.
AFTER: You read IDE specs and understand which model powers the tool.
AFTER: You distinguish between basic chatbots and advanced reasoning models.
AFTER: You evaluate AI add-ons based on known limitations rather than hype.
GAIN: A clear comparison between free and paid ChatGPT capabilities.
GAIN: Knowledge of specific shortcomings that affect coding reliability.
GAIN: Context on how OpenAI drives current AI product development.
STEP: You face a menu of AI models and cannot distinguish their core capabilities. || Explain how different AI products work || Read model documentation with a baseline understanding of how LLMs generate text.
STEP: You wonder if ChatGPT Plus adds value for coding tasks over the free tier. || Compare ChatGPT and ChatGPT Plus || Decide if a paid tier is required by understanding feature deltas between levels.
STEP: You assume current AI handles all IDE tasks perfectly without limitations. || Analyze various shortcomings of ChatGPT that need improvement || Set realistic expectations by identifying where the model fails in logic or context.
STEP: You feel pressured to pick an IDE without understanding the underlying AI role. || Define the role of OpenAI in innovating technology || Separate brand marketing from technical reality when selecting developer tools.
NOTFOR: Developers who need deep technical details on model architecture.
NOTFOR: Users who only want a hands-on tutorial for a specific IDE interface.
FACT: Average duration: 1.5-3 Hours
FACT: CPD-accredited certificate available
FACT: Intermediate level
COVERS: Define the role of OpenAI in innovating technology
COVERS: Explain how different AI products work
COVERS: Compare the roles of ChatGPT and Google in terms of AI development
COVERS: Evaluate the working model designated for ChatGPT
COVERS: Outline different ways ChatGPT can be used positively
COVERS: Analyze various shortcomings of ChatGPT that need improvement
COVERS: Recognize ways you can develop and train another GPT model
COVERS: Compare ChatGPT and ChatGPT Plus
COVERS: Programming
COVERS: Productivity
COVERS: Chatbot
MODULE: Fundamentals of ChatGPT Functioning || Introduction to OpenAI and ChatGPT | Working with ChatGPT | ChatGPT and its Shortcomings | Training a GPT Model
What you are probably seeing
Your recent billing statement shows a higher cost per request when using Anthropic models compared to OpenAI models within the same Copilot tier.
You notice that the number of premium requests consumed by a single Opus response is significantly higher than for a GPT response, making your allowance drain faster.
Why it happens
Different AI providers have varying computational costs, so Microsoft applies a rate multiplier to balance the subsidized access to their partners’ models.
The platform treats model complexity as a factor in consumption, meaning more powerful models like Opus consume multiple units of your allowance per request compared to standard models.
What changed recently
2026-10-07 · microsoft copilot vscode
GitHub is now clarifying the rate multipliers for that gap:
• Copilot Pro: $10
• OpenAI models: 1x rate (Microsoft subsidized)
• Anthropic Opus: 3x rate
Source: autocomplete
Step by step
1. Review your current Copilot plan details to confirm which specific AI models are included in your subscription tier.
2. Check the billing dashboard to identify which models are triggering higher rate multipliers on your recent invoices.
3. Compare the consumption rates of different models to determine if your preferred tool fits within your monthly request limit.
4. Switch to a lower-cost model for routine tasks to conserve premium requests for complex coding challenges.
5. Monitor your usage trends over the week to ensure your tool stack remains within your financial and quota boundaries.
Ways to go further
Start here: The Fundamentals of ChatGPT: AI Language Model For when you need general AI literacy before picking a specific IDE. Open the free course on Alison ↗
Better fit: Microsoft: Use Microsoft AI Tools Like a Pro and Master MS Copilot For when you need to optimize Microsoft Copilot workflows. Open the free course on Alison ↗
Affiliate links: CHEAPUNO may earn a commission if you buy through them, at no extra cost to you.
Other problems readers raise
Can Fastmail or ProtonMail fully replace Google Workspace?
Why do AI workflows fail on final edge cases?
Is Campfire stable enough to self-host for your team?