ChatGPT Guide: Prompts, Tips & Advanced Techniques

ChatGPT Work is the "AI agent for work" that OpenAI announced on July 9, 2026 alongside GPT-5.6. Unlike a regular chat that just answers, it gathers context from your connected apps and files to build finished deliverables — documents, spreadsheets, slides, and even web apps. Its brain is the new flagship GPT-5.6 Sol (built on Codex), and it can break a complex project into steps and keep working for hours (Thurrott). Inside the unified desktop app, three modes coexist — Work (deliverables), Codex (technical, shows details), and regular chat (conversation) — with Work positioned as the "business version" that hides Codex's technical detail (9to5Mac). The model depends on your plan: Free/Go default to Terra, while Plus/Pro/Business/Enterprise choose from Sol/Terra/Luna (as reported). Its strength is pulling in "your context" via connectors like Google Drive, SharePoint, and Slack, plus MCP — and for enterprise, data isn't used for training by default. Drawing on Axios, TechCrunch, 9to5Mac, Thurrott, and OpenAI, this article lays out what ChatGPT Work is, how it differs from regular ChatGPT and Codex, which plans can use it, and which apps it connects to — with confidence labels on what is not yet official.

On July 8, 2026, OpenAI released "GPT-Live," a new model that overhauls ChatGPT's voice worldwide. Its headline feature is a full-duplex architecture that "listens and speaks at the same time": it returns backchannels (mhmm/yeah) while you're still talking, absorbs interruptions mid-sentence, and doesn't mistake your thinking silences for "you're done" and cut you off — a fundamental break from the turn-based (half-duplex) Advanced Voice Mode. Response latency is under 250ms. GPT-Live handles conversational responsiveness, and when web search or deep reasoning is needed it delegates to GPT-5.5 behind the scenes (choose Instant/Medium/High) so the conversation never stalls. Free defaults to GPT-Live-1 mini, and Go/Plus/Pro to GPT-Live-1, rolled out on iOS, Android, and web. In human evaluations it was clearly preferred over Advanced Voice Mode. This article explains, based on the official announcement, what GPT-Live is, how it differs from the old mode, how it works, the two models and plans, its main advances, and the limitations worth being honest about (no video or screen sharing, full multilingual parity not yet reached, and no API — with GPT-Realtime-2.1 provided as a separate line).

An in-depth comparison of OpenAI's flagship GPT-5.6 Sol and Google Gemini. Unlike the earlier battles against Claude, their strengths barely overlap: Sol dominates agentic and terminal coding (Terminal-Bench 2.1 88.8% vs 68.5%, SWE-bench Pro 64.6% estimated vs 54.2%), while Gemini counters with native multimodality (voice and video), roughly half the price ($2.50/$15 vs $5/$30), and a lead on MMLU 92.6%, ARC-AGI-2 77.1%, and WebDev Arena. There is also an important "timing trap": Google's true challenger, Gemini 3.5 Pro, is not yet released as of this writing (GA planned for mid-July 2026 after a full architecture overhaul), so the fair comparison target today is the current flagship Gemini 3.1 Pro (February 2026). This article lays out a spec cheat sheet, coding/reasoning/multimodal benchmarks, the multimodal gap that is Gemini's home turf, real cost (Gemini about 2x cheaper than Sol, but Terra now undercuts Gemini), a strengths-and-weaknesses map, and use-case-based selection, grounded in official announcements and independent benchmarks.

Arriving July 9, just two and a half months after April 2026's GPT-5.5, GPT-5.6 is not merely a performance bump — the biggest change is the reorganization from a single flagship into a three-model lineup: Luna/Terra/Sol. What matters most to many GPT-5.5 users is that the mid-tier Terra delivers GPT-5.5-class quality at a far lower price: it launched at half price, and the July 30, 2026 price cut took it to 40% of GPT-5.5's unit price ($2/$12). For those wanting more performance there is the top-tier Sol (same $5/$30, with SWE-Bench Pro rising an estimated 58.6→64.6%); for those wanting lower costs there is Terra. This article lays out, based on official announcements and independent analysis, what the three-model shift means, a spec-at-a-glance table, Terra's price-to-performance, generational benchmark gains (same-metric SWE-Bench Pro +6pt, but TerminalBench differs in version 2.0→2.1 and much general reasoning is undisclosed), 5.6's new features (Programmatic Tool Calling, max effort, ChatGPT Work, GPT-Live, GitHub Copilot support), real cost (roughly $1,100→$440 for 100M input/20M output a month), and which model you should migrate to (cut the bill by 60% with Terra, then move only performance-critical work to Sol).

An in-depth comparison of OpenAI's flagship GPT-5.6 Sol (July 9) and Claude Fable 5 (June 9), which Anthropic positions as "the most powerful model it has ever made generally available." Where the Opus 4.8 matchup was a head-to-head in the same price tier, this one turns on a cost-versus-capability trade-off: "the half-price all-rounder Sol ($5/$30)" against "the twice-as-expensive but top-tier Fable 5 ($10/$50)." On production-grade coding's SWE-Bench Pro, Fable 5's 80.3% pulls more than 15 points ahead of Sol's 64.6% (estimated) — a gap wider than in the Opus 4.8 matchup. Fable 5 also self-drives for up to 12 continuous hours while focusing on millions of tokens, with Stripe finishing a 50-million-line Ruby migration in a single day as its home-turf "follow-through." Sol, meanwhile, leads on terminal operation (TerminalBench 2.1 88.8% vs Fable 86.0%), Agents' Last Exam (53.6 vs 40.5), and Coding Agent Index (80 vs 77.2), plus best value with half the price and +54% token efficiency. This article covers the spec cheat sheet, benchmark details, the "undisclosed-benchmark problem" of OpenAI withholding Sol's SWE-bench Pro, long-running autonomy, real cost (viewed per completed task), a strengths-and-weaknesses map, and how to choose by use case — all grounded in official and independent benchmarks.

An in-depth comparison of 2026's two AI-coding giants, Claude Opus 4.8 (May 28) and GPT-5.6's top-tier Sol (July 9). Their strengths are almost opposite: Sol leads in terminal operation and overall agentic capability (TerminalBench 2.1 88.8% vs Opus 78.9%, Agents' Last Exam 53.6, Coding Agent Index 80), while Opus 4.8 leads in production-grade coding, math, and long context (SWE-bench Pro 69.2% vs Sol 64.6%, USAMO 2026 96.7%, GraphWalks 1M 68.1%) and foregrounds honesty (overconfidence cut to one-tenth, 0% uncritical reporting of flawed results). OpenAI also leaves many of Sol's benchmarks undisclosed (SWE-bench Pro, GPQA, AIME, MMLU), so in coding's heartland the disclosed Opus has the edge. We cover the spec table, benchmark details, the undisclosed-benchmark problem, real cost ($25 vs $30 unit price vs +54% token efficiency), a strengths/weaknesses map, use-case picks, and a dual-vendor strategy.

OpenAI made GPT-5.6 generally available on July 9, 2026, replacing the old "standard + Pro" structure with a three-model lineup: Luna (fast, low-cost, $0.20/$1.20), Terra (balanced, $2/$12, GPT-5.5-class at 40% of Sol's unit price), and Sol (flagship, $5/$30) — prices as revised on July 30, 2026. Sol takes first place on Agents' Last Exam (53.6) and the Coding Agent Index (80), and its 88.8% on TerminalBench 2.1 edges out Claude Fable 5 (86.0%) — yet on production-grade SWE-Bench Pro, Claude Fable 5 leads decisively at 80.0% against Sol's 64.6%. This article covers the differences between the three models, pricing, benchmarks, new features (Programmatic Tool Calling, ChatGPT Work, the full-duplex GPT-Live voice model), availability by ChatGPT plan, a comparison with Claude (Fable 5 / Opus 4.8), and how to choose by use case — all grounded in OpenAI's official announcement and independent benchmarks.

AI can be a know-it-all friend that keeps up with a child's "why?" and a storyteller before bed — but with kids, the safety setup matters before the fun. This article sets the safety promises first (① an adult operates and checks ② check age limits ③ enter no personal info ④ teach that AI can be wrong ⑤ set the tone and time), then shows 10 copy-paste activities: stories and words (a bedtime story where your child is the hero, a kids-decide story, a calm bedtime tale), learning and curiosity (a know-it-all professor, an animal & dinosaur quiz, a greetings teacher for other languages), and making and expression (draw an imagined creature, a coloring-page line drawing, craft ideas, a feelings & manners role-play). With tips by age (preschool / elementary / older kids), how to enjoy it more, what parents should know, and an FAQ. The basic rule: an adult operates the AI and checks the content before showing it. Works on free ChatGPT, Claude, or Gemini.

The most addictive way to play with AI is a text adventure with AI as your game master (GM): you declare an action, the AI describes the scene and the story branches, and it even handles wild actions outside the given choices. This article walks through how to build one from start to finish with copy-paste prompts: a starter prompt you just paste, the 5 parts that decide the fun (① setting ② tone ③ rules ④ state-tracking ⑤ pacing), genre presets (fantasy adventure, horror escape, mystery investigation, sci-fi survival, cozy slice-of-life), next-level tricks (dice for luck, stats and levels, save & resume), how to fix it when it goes wrong (too soft / runs on its own / on rails / forgets the state), and tips for long play. No programming, works on free ChatGPT, Claude, or Gemini. With cautions and an FAQ — the deep-dive companion to item ⑦ of "15 fun ways to use AI."

Stuck on "what am I even supposed to ask an AI?" This gives you 30 ready-to-paste prompts that get a fun reply back the moment you paste them. Six genres of five: get to know yourself (hidden strengths, shared values, which animal you are), spark ideas and what-ifs (unexpected uses for an everyday object, if gravity were halved, inventing a holiday), explanations that click (quantum mechanics for a 5-year-old, compound interest in three metaphors, the internet as pizza delivery), wordplay (rewrite in 10 styles, a two-sentence micro-story, epithets, palindromes), role-play and advice (a tough life coach, a sage who invents proverbs, a letter from your future self, a baffled alien), and useful-but-fun (turn an excuse into a maxim, five levels of saying no, fix a bland message, dramatic menu names, a fun detour in your to-do). Works on free ChatGPT, Claude, or Gemini. Includes tips (stack "more," add role and constraints, switch AIs), cautions, and a link to the sister article "15 fun ways to use AI."

Talk about AI and it is always the serious stuff, but AI might shine brightest at play. This article shows 15 fun ways to use AI, each with a copy-paste prompt you can try right now. Wordplay & comedy (① comedy battles ② parody-song/rap machine ③ naming factory), role-play & dialogue (④ talk to a historical figure ⑤ make two AIs debate ⑥ practice arguing with a devil's-advocate bot), games (⑦ text adventure with AI as game master ⑧ original quiz show ⑨ whodunit mystery game), creative (⑩ fictional creature field guide ⑪ a story where you are the hero ⑫ playing with image generation), and everyday & unexpected (⑬ leftovers chef ⑭ travel plans to ancient Rome or the Moon ⑮ entertainment fortune-teller). All work on free ChatGPT, Claude, or Gemini. The three keys to the fun — give it a role, bind it with constraints, stack "more" — double as the foundations of practical prompting. With cautions (fact vs. fiction, personal info, playing with kids) and an FAQ.

Knowledge workers lose 2–3 hours a day to email. Gmelius's 2026 study found that companies adopting AI email assistants cut inbox time by 65% and saw productivity gains of 82% — five minutes per reply collapsed to thirty seconds. This article frames the productive way to use AI for inbox and chat work through a 3-layer model (draft with human approval / tone tuning / full auto), compares the main tools (Gemini in Gmail, Microsoft Copilot, Shortwave, Gmelius, MailMaestro, ChatGPT/Claude, Intercom Fin), gives three copy-pasteable 10-second prompt templates (reply draft, 3-line summary, tone conversion), covers chat automation across Slack, Teams, and LINE, and lays out the three operational rules that keep AI assistance from destroying long-term relationships.