ChatGPT Guide: Prompts, Tips & Advanced Techniques

Attach a saved recording to ChatGPT and turn the transcript into meeting minutes, interview notes, or lecture notes. The guide covers supported formats, the 512MB limit, differences from Voice and Record, troubleshooting, and separate API billing. It also explains how to check speakers and numbers, and how recordings are used for training and stored.

Before choosing Codex Security, compare the local plugin, the GitHub-connected Cloud service, and the standalone CLI. This guide uses official documentation to explain separate Cloud billing, conditional free scan credits, first-scan setup, Standard and Deep costs, scan coverage and reproduction evidence, and post-fix verification. It also covers when the standalone CLI uses an API key from the environment and how estimated cost limits work.

Conversations and code on personal ChatGPT and Codex plans, including Pro, are used for training by default. One ChatGPT setting also covers new Codex tasks, but environment training has a separate setting. The guide also covers what not to enter, what to do if you submit API keys or customer data, and the exceptions for deletion and review.

Prompt caching reuses the computed results for the start of a request that matches an earlier one, so that part of the input costs less and runs faster. OpenAI (GPT-5.6 and later) turns it on by default and keeps the cache at least 30 minutes after last use (12 hours is optional), with writes at 1.25x the input price (2.5x for 12 hours) and reads at 0.1x (0.05x for GPT-6.1 Sol); Claude caches only when a request includes cache_control, with a 5-minute cache (1 hour is optional), writes at 1.25x (2x for 1 hour), and reads at 0.1x (0.05x for Opus 5.5 and Sonnet 5.5, 0.025x for Fable 5.1). Based on both companies' official documentation as of October 3, 2026, this article compares minimum length, breakpoints, sharing scope, and rate limits, works out how many reads it takes to break even, and explains common misses and how to check hits with usage and diagnostics.

In the ChatGPT desktop app (Codex), right-click the floating pet and choose Hide Mini to remove it quickly. No official documentation describes a setting that disables pets in the app, so if a pet reappears, check the display shortcut first. This guide compares the steps, Mini, and the CLI, web, and IDE extension differences, using official documentation and a user-provided Windows screenshot.

ChatGPT dot is a continuous AI agent that keeps working on tasks between conversations, included at no extra charge with Pro. In our to-do app test, dot handled generating the app and adding undo, but screen checks were completed in Codex. The article covers pricing, usage limits, memory and permissions, delegation to Codex, and how to stop work, so you can decide how to split work between dot and Codex.

ChatGPT Pro comes in three tiers: 100, 200 and 500. Since October 29, 2026, the Work and Codex allowances are 10, 20 and 50 times Plus (calculated by this site), and the official monthly prices are $100, $200 and $500, so two 100 subscriptions and one 200 cost the same and give the same total allowance; local-currency prices vary by country or region. The article also explains how speed settings use up allowance, how and when to use banked reset passes, and how they differ from credits.

If you use GPT-6 Sol in Codex, switching to GPT-6.1 Sol is fine. Released on September 29, 2026, it is recommended for complex coding and long-running work, with the same context limit and standard API prices, half-price cached input, and a knowledge cutoff 10 days newer. The guide covers switching steps in Codex, the difference between new and existing chats, Plus and Pro usage limits, and how to compare both at Medium effort before you decide.

Even with the same Pro subscription, image generation draws from different usage pools in regular ChatGPT Chat versus Codex and Work. Claude models do not directly create photos or illustrations, but Claude Code can produce images through HTML, SVG, code, or external image APIs. The article diagrams each entry point and walks through a practical method: set the display size first, then specify the composition, separate reference material from new content, and select from a few outputs by checking them at full size and at the actual display size.

Ask an AI "What kind of person am I?" and all you get back is a plausible-sounding expansion of whatever you typed in. What works is the reverse: let the AI ask the questions to draw out real events, have it help sort out the common threads and put them into words, and make the final call yourself. This article gives you 8 prompts to use in order: an interview, strengths, values, weaknesses, the conditions of work that suits you, a personal pitch draft, mock interview questions, and a check from the opposing side. It also covers why you shouldn't take the answers at face value, including the tendency to feel that words which fit anyone are "spot on" (Forer's 1949 experiment) and AI's tendency to agree with you; what information is fine to enter and what to avoid; and how to use memory and projects in ChatGPT, Claude and Gemini, all checked against each company's official help pages.

OpenAI released GPT-6 Sol and GPT-6 Luna on September 22, 2026 (US time). Sol is priced at 1/5 of Astra ($2 input / $10 output) and Luna at 1/100 ($0.10 input / $0.50 output), and both are available in ChatGPT Work and Codex on Plus, Pro, Business, Enterprise and Edu, and in the API. Free and Go get Luna only, in the desktop app. Neither model was in regular Chat at launch, but since October 7 GPT-6 in Chat runs on Sol for Plus, Pro, Business and Enterprise, and since October 8 on Luna for Free and Go. GPT-5.6 remains available during the transition period. Written for people who currently use Astra at low (shown as Light in the app), this article separates its sources by publisher: the official use-case guidance (Sol at Medium, Luna at High, Astra from Light) and how it differs from the app's default preset (Sol Light); OpenAI's AutomationBench result where Sol xhigh beat Astra low; the values in Artificial Analysis's comparisons (42% for Astra low vs 19% for Sol medium on Terminal-Bench 4.0, but 59% vs 58% on business workflows); and AI Arte's small-scale test (every setting passed the short tasks, which is no basis for a ranking). It also explains why unit-price ratios don't carry over directly to the total cost of a job or to how much a subscription covers, and where the decision turns: Sol medium for everyday work, Sol low or Luna high for short, easy-to-verify jobs, and Astra for hard design work and important reviews.

A newer model is smarter but more expensive, or so the thinking usually goes. Yet comparing GPT-6 Astra with GPT-5.6 Sol on unit price alone settles nothing, because Astra finishes the same job on fewer tokens. In measurements by the independent benchmarking firm Artificial Analysis, running Astra at its weakest setting, low, costs almost exactly what Sol costs at high for one task ($0.82 against $0.81) while scoring higher (46 against 42), on one third the output tokens and a quarter of the wait before the reply starts. Working from the figures as of September 18, 2026, this article covers cost, tokens and speed at each level of reasoning effort, the breakdown that explains why a 2.5x unit price still lands on the same total, what the numbers look like once Sol's promotional price ends, the way the gap in price narrows on coding agent work, and the steps for measuring all of it on your own work.