Lesson 16 of 25
The Seed of a New Idea (Brainstorming)
Brainstorming with an AI only works when you give it somewhere to push against. An open request - "suggest some names" - returns the most average answer in existence, because average is exactly what a prediction engine is built to produce. You get genuinely useful raw material by asking for volume, giving the model a specific brief to generate against, sorting the output into categories you chose, and banning the obvious answers by name.
Be clear-eyed: this is the weakest of the four for open brainstorming. An answer engine is built to find what has been written, so asking it to invent twenty names returns the names already indexed - it converges where a brainstorm needs to diverge. Its honest role in this chapter is the step before and the step after: find out what already exists so you do not spend an afternoon reinventing it, then come back to check your shortlist. For the traffic problem, that research step is genuinely the most valuable part of the whole chapter, because almost every idea on your list has been tried somewhere and written up.
- Research what exists; generate somewhere else.
- Best used after generating, to check your shortlist.
- Ask what has been tried and what happened.
- Academic focus for research; Web for market scans.
- Keep each brainstorm's research in its own Space.
Instead of
What should be the name for my new coffee shop in Kondapur?
Perplexity version
Do not generate the names here. Ask an answer engine to invent twenty brand names and it will hand you the names that are already indexed, with citations - which is precisely backwards. Generate in ChatGPT, Claude or Gemini. What this tool is genuinely good for is finding out what already exists, so that the brainstorm starts somewhere new instead of somewhere crowded. I am opening an upscale coffee shop in Kondapur, Hyderabad, aimed at IT professionals from the nearby tech parks. 1. What specialty and upscale coffee shops currently operate in Kondapur, Gachibowli, Madhapur and HITEC City? List them with their names, and note which are chains and which are independents. Cite sources. 2. Looking at those names together, what naming conventions dominate? Which words recur? I want the pattern stated explicitly, because that list becomes my ban list in the next tool. 3. What is reported about the Indian specialty coffee market and consumer preferences in the last two to three years - what segments are growing, how filter coffee is being positioned against third-wave coffee? Cite reports with dates. 4. How does one actually check whether a brand name is available in India? Set out the process: the trademark classes that cover a cafe, how to search the IP India register, FSSAI registration, and what a Shops and Establishments registration in Telangana requires. Cite the official sources. This is the step people skip and then discover eighteen months later. 5. What is documented about naming disputes or forced rebrands among Indian F&B businesses? Cite cases. I would like to know what the mistake actually costs. For each: source and date. Where you only find listing aggregators and food blogs rather than anything substantive, say so rather than dressing them up. Then generate the names elsewhere using answer 2 as the ban list - and come back here with your final three for the availability checks in answer 4. That round trip is the right use of this tool.
Instead of
Solve the traffic problem in Hyderabad.
Perplexity version
This is the one example in this chapter where the research step matters more than the brainstorm. Almost every unconventional idea for urban congestion has been tried somewhere and written up, and finding those write-ups beats inventing fifteen ideas blind. The problem: peak-hour congestion on the Outer Ring Road in Hyderabad, 8 to 11 AM and 5 to 8 PM, driven heavily by IT commuting to the western tech corridor. 1. What is currently documented about ORR and western-corridor traffic volumes, peak-hour patterns and travel times? Cite HMDA, the Telangana transport department, traffic police data or published studies, with dates. Give me the measured baseline before anyone proposes a solution to it. 2. What demand-management measures have cities elsewhere actually implemented - congestion pricing, cordon charges, staggered working hours, employer trip-reduction mandates, parking levies, road-space rationing? For each: where, when, and what the reported outcome was. Cite evaluations rather than press releases, and say when an evaluation is by the implementing authority itself. 3. Which of these have been tried, proposed or rejected in Indian cities, and what happened? Delhi's odd-even scheme, Bengaluru's attempts on the ORR, any Hyderabad proposals. Cite the sources and the current status. 4. What does the research literature say about employer-side interventions - staggered shifts, remote-work mandates, employer-run shuttles - and their measured effect on peak-hour volumes? Use Academic focus for this one. It is the least-covered lever and the most relevant, given how concentrated employment is in the corridor. 5. What is already announced or under construction for ORR traffic management - the Regional Ring Road, metro extensions, elevated corridors? Cite official announcements with dates, so no idea I propose turns out to be underway already. 6. What is documented about why congestion pricing has failed politically where it has failed? Cite the accounts. The constraint on this problem is political, not technical, and this is the question that will shape the brainstorm most. Cite everything with dates. Distinguish evaluated outcomes from claimed ones. Where an intervention was abandoned before evaluation, say so. Save it in a Space called "ORR congestion". Then take the findings to another tool for the actual divergent brainstorm - but brainstorm against this evidence, not against a blank page. Fifteen ideas generated after answer 2 are worth more than fifty generated before it.
Instead of
Write a blog post about the importance of saving for retirement.
Perplexity version
Do not ask for the analogies here. Metaphor generation is the clearest case of what this tool does not do: you will get the analogies that are already published, cited, and therefore already worn out. But there are two research questions that make the post materially better, and one of them is the difference between a good post and a problem. 1. Which analogies for compound interest are already in heavy circulation in Indian personal finance writing? Search the major Indian personal finance publications, bank and AMC blogs, and the big finance creators. Name the recurring images and cite where they appear. I want this as an exhaustion list - the snowball, the magic of compounding, the chessboard and grains of rice - so that whatever I generate elsewhere avoids all of it. 2. **The one that actually matters:** what do SEBI's advertising and disclosure rules permit a blog post to say about investment returns and past performance, and when does content about saving cross into investment advice requiring registration? Cite the regulations and any relevant SEBI circulars, with dates. An analogy that implies guaranteed returns is not just weak writing, and I would rather know the line before I write than after. 3. How do the instruments my readers would actually use work - EPF, NPS, PPF, equity mutual fund SIPs? Cite EPFO, PFRDA and AMFI sources with dates. I need the mechanics described accurately; I am not asking for returns or recommendations. 4. What is documented about actual retirement savings behaviour among young urban Indians - participation rates, when people start, what the reported barriers are? Cite surveys with dates. If the real barrier is irregular income rather than not understanding compounding, my post is aimed at the wrong thing and I should know that before writing it. 5. What does behavioural research say about which framings move people to start saving - future-self framing, loss framing, automatic enrolment? Use Academic focus. Cite the studies. This tells me which of my ten analogies to put first. Cite everything with dates. Do not cite content marketing from AMCs or insurance companies as neutral evidence on savings behaviour - name it as interested if you use it. Then write the analogies in another tool, with answer 1 as the ban list and answer 2 as the boundary. Answer 4 may change the post entirely, which is the best possible outcome from a research step.