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AIAP Topic Courses·Using AI for Research·35:53

Evaluating AI Research Tools, Part 2: Buyer Personas, Marketing Trends, a Content-Gap Analysis, the Verdict, and Adapting a Proven Prompt

Outskill instructor (unnamed) Research trainer - runs identical prompts through six AI research tools and scores them live

The short version

  1. Use case 3 - four Notion buyer personas (demographics, psychographics, jobs to be done, pains, buying behaviour, channels, objections, voice of customer): runs of 30-35 minutes; ChatGPT 'so far the winner'; Gemini stopped on an error once but has the best paragraph-level sources; a '37.14% aged 25-34' stat checked out (0:00-0:14).
  2. Use case 4 - emerging trends in AI-led marketing, Perplexity added: Perplexity fastest and 4/4/4-4.5; ChatGPT and Gemini slowest; Claude deviated from the prompt; Genspark too brief. Use case 5 - content-gap analysis for Fireflies.ai vs Otter, Rev, Trint, Grain, AssemblyAI: Manus surprised with an exportable 90-day calendar; Gemini best on themes and search; Claude missed Granola (0:12-0:34).
  3. Verdict: Gemini Deep Research first, ChatGPT second, Claude and Perplexity decent, Genspark best presentation least depth; research in Gemini, augment in ChatGPT, format in Genspark. Workflow: paste a proven prompt and ask the LLM to adapt it to a new subject (Vapi) - 80% of a perfect prompt, then refine (0:31-0:35).

At a glance, three clicks deep

Skim here first: the closed row is the glance, open is the study card with the key points and timestamps, and the ↓ link drops to that concept's full write-up below.

02The verdict, the recommended stack, and adapting a proven promptGemini -> ChatGPT -> Genspark;›

Gemini -> ChatGPT -> Genspark; adapt prompts, don't rewrite.

Verdict (0:31-0:32)

Adaptation (0:33-0:35)

↓ Full write-up of this concept

The concepts in full

02

The verdict, the recommended stack, and adapting a proven prompt

Research in Gemini, augment in ChatGPT, format in Genspark. And never write the second prompt from scratch - hand the LLM the first one.

Verdict (mid-2025, subjective): Gemini Deep Research first choice, ChatGPT Deep Research second, Claude and Perplexity decent, Genspark best presentation with least depth. Stack: research in Gemini, augment with ChatGPT, format in Genspark. Prompt adaptation: paste a proven prompt and say 'I want to do this research for Vapi - modify the prompt to work for Vapi'; the LLM swapped industry (voice AI agents) and competitors (ElevenLabs, AssemblyAI, Deepgram, OpenAI Whisper, Speechify). Let the LLM draft the baseline prompt to reach '80% perfect', then refine with domain expertise. The course promises all five prompts in the resources.

Why it matters

Turns one good prompt into a reusable research instrument.

This idea elsewhereclosesThe method

Tools referenced

ToolCoverageMomentContext
GeminidemonstratedDeep Research - first choice
ChatGPTdemonstratedDeep Research
Perplexitydemonstrated
Manusdemonstrated
Gensparkdemonstrated
ClaudedemonstratedClaude Research
FirefliesmentionedContent-gap subject

Action items

    Resources mentioned

    Resources
    • docThe five research prompts (market landscape, Notion benchmark, Notion personas, AI-led marketing trends, Fireflies content gap)

    Extraction notes

    This page was built from an auto-generated transcript, which garbles product and people's names. Those were corrected silently in everything above and logged here for transparency. The warnings flag claims that were true on the recording day but change fast.

    Transcript corrections applied

    The transcript saysThe trainer actually means
    Print Grain / Simpli AITrint, Grain / AssemblyAI
    WAPI / PAPIVapi
    publicityPerplexity
    cloud / Cloud co work / cloud researchClaude / Claude Cowork / Claude Research
    chat g b t / ChargeGPT / Chargebee / chat GBTChatGPT
    ATN / n a 10 / Anytimen8n

    True on recording day — verify before relying