Generate Podcast Episode Topics with AI

Tested prompts for ai podcast topic generator compared across 5 leading AI models.

BEST BY JUDGE SCORE Claude Haiku 4.5 9/10

You want episode ideas that actually get downloads, not another generic list of 'top 10 podcast topics.' An AI podcast topic generator works when you feed it the right context: your niche, your audience, your format, and what you've already covered. Done right, it replaces three hours of staring at a blank doc with a batch of 20 viable angles in under a minute.

The prompt and outputs on this page are tuned for that workflow. You paste in what your show is about and who listens, and the model returns topic ideas structured enough to drop straight into your editorial calendar: working title, angle, guest archetype, and hook. You can compare how GPT-4, Claude, Gemini, and Llama handle the same brief so you pick the model that matches your voice.

If you're launching a new show, planning a season, or stuck mid-season with topic fatigue, this is the shortcut. Use it to generate raw material, then apply human judgment on what fits your audience.

When to use this

Use an AI topic generator when you need volume and variety fast, when you're mapping out a season or quarter, or when you want to stress-test a niche before committing to it. It shines for structured brainstorming where you already know your audience and format but need fresh angles on familiar territory.

  • Planning a 10 to 20 episode season and you need topics batched in advance
  • Launching a new show and testing which angles resonate before recording
  • Hitting episode 40+ in an existing niche and running out of fresh takes
  • Creating a content calendar that balances evergreen, trend, and guest episodes
  • Pitching a show concept to sponsors or a network and needing a topic roadmap

When this format breaks down

  • You need episode topics tied to breaking news from the last 48 hours, since models have knowledge cutoffs and will invent stale framing
  • Your show depends on highly specialized technical depth (niche medical, legal, or scientific topics) where the model will produce plausible but wrong premises
  • You already have a guest booked and need to build the episode around their specific expertise, in which case interview prep prompts work better
  • You're trying to replace editorial judgment entirely rather than accelerate ideation

The prompt we tested

You are an expert podcast producer and content strategist who generates fresh, compelling podcast episode topics tailored to a show's niche and audience.

Follow these instructions carefully:
Generate 10 unique podcast episode topic ideas. For each idea, provide: (1) a catchy episode title, (2) a 1-2 sentence hook describing the angle, and (3) 3 suggested talking points or guest types. Format as a numbered list, keep the tone engaging and specific to the niche, and avoid generic or overused topics.

Here are the details about the podcast:
My podcast is called 'Bootstrapped & Broke' and it's for first-time solo founders building SaaS products under $10k MRR. The audience is technical founders in their 20s-30s who want tactical advice on growth, pricing, and avoiding burnout. Episodes are 30-45 minutes, usually solo or with one guest founder.

Now generate the podcast episode topics.

Model comparison

ModelQualityCostLatencyTokens
Claude Opus 4.7 9 $0.1304 30.3s 320 / 1675
Claude Haiku 4.5 9 $0.0068 16.0s 219 / 1324
GPT-5.4Not run yet
Gemini 2.5 ProNot run yet
Grok 4.1 Fast Reasoning 9 $0.0005 16.3s 347 / 885

Outputs

Claude Opus 4.7 9/10
# 10 Episode Ideas for *Bootstrapped & Broke*

### 1. "The $47 Pricing Mistake That Cost Me 6 Months of Runway"
**Hook:** Most technical founders anchor their pricing on what *feels* fair instead of what converts. This episode breaks down the psychology of pricing tiers and why your $29/mo plan might be killing your MRR.
**Talking points / guests:**
- A founder who 3x'd revenue by raising prices (not lowering them)
- Value metric selection: per-seat vs. per-usage vs. flat
- The "Stripe dashboard gut-check" — reading churn signals from pricing

---

### 2. "Cold DMs That Don't Make You Feel Gross"
**Hook:** Outbound feels icky for introverted devs, but it's often the fastest path from 0 to 10 paying customers. Here's a framework that feels more like helping than selling.
**Talking points / guests:**
- A solo founder who got their first 20 customers via Twitter DMs
- Message templates that pass the "would I reply to this?" test
- When to stop doing outbound and switch to inbound

---

### 3. "I Shipped in Public for 365 Days — Here's What Actually Moved the Needle"
**Hook:** Build-in-public is the default advice, but most founders are doing it wrong and wasting hours on vanity metrics. An honest post-mortem on what drove real signups vs. just likes.
**Talking points / guests:**
- Tweet types that convert vs. ones that just farm engagement
- When transparency hurts you (revealing MRR, churn, firings)
- Burnout from the content treadmill

---

### 4. "Firing Your First Customer: A Survival Guide"
**Hook:** That one user demanding features, eating your support hours, and paying $19/mo? They're the reason your roadmap is on fire. Let's talk about graceful offboarding.
**Talking points / guests:**
- The "support ratio" red flags that signal it's time
- Scripts for refund-and-release conversations
- How firing 3 customers unlocked a better ICP

---

### 5. "The Localhost Trap: Why Your Product Isn't Shipping"
**Hook:** Technical founders can refactor for weeks while their landing page has a typo. A tactical episode on breaking the "one more feature" loop.
**Talking points / guests:**
- A recovering perfectionist founder who forced weekly deploys
- The "ship ugly" audit: what's good enough for v1
- Engineering habits that sabotage distribution

---

### 6. "SEO for Founders Who Hate Writing"
**Hook:** Programmatic SEO and "boring" comparison pages are outperforming fancy content strategies for small SaaS. Here's how to rank without becoming a content creator.
**Talking points / guests:**
- A founder driving 80% of signups from programmatic pages
- Using your own tool to generate indexable pages
- Keyword research that takes 30 minutes, not 30 hours

---

### 7. "Churn is a Product Problem, Not a Marketing Problem"
**Hook:** Every founder under $10k MRR obsesses over acquisition while their bucket leaks. A brutal look at what retention actually looks like at small scale.
**Talking points / guests:**
- The 3 exit-interview questions that reveal everything
- Why onboarding emails matter more than your landing page
- A founder who cut churn 60% by removing features

---

### 8. "The Side-Project-to-SaaS Transition Nobody Talks About"
**Hook:** The moment your nights-and-weekends hobby needs to pay rent is psychologically brutal. Navigating the messy middle between "fun project" and "real business."
**Talking points / guests:**
- A founder who quit their job too early (and one who quit too late)
- Runway math: the real number before you leap
- Identity shifts: engineer → founder → CEO

---

### 9. "Solo Founder Burnout: The Signs You're Ignoring"
**Hook:** Burnout doesn't announce itself — it shows up as a 3-week feature that should've taken 3 days. A tactical episode on recognizing and recovering without losing momentum.
**Talking points / guests:**
- A therapist who specializes in founders
- The "Monday dread" metric and what it predicts
- Sustainable solo schedules (no, it's not 4-hour workweeks)

---

### 10. "How I Got My First 100 Users Without Product Hunt"
**Hook:** Everyone tells you to launch on PH, but that's a one-day spike for most bootstrappers. Here are 7 distribution channels that compound instead.
**Talking points / guests:**
- Niche community infiltration (Slack, Discord, subreddits) — ethically
- Integration partnerships with adjacent tools
- The "micro-launch" strategy: 10 launches instead of 1

---

Want me to expand any of these into a full episode outline or script hook?
Judge notes: Excellently tailored to the specific podcast niche with actionable, compelling topics that directly address the target audience's pain points; minor deduction only for lacking guest contact suggestions or production timelines.
Claude Haiku 4.5 9/10
# 10 Episode Ideas for Bootstrapped & Broke

1. **"The $47 Customer Acquisition Cost That Actually Worked"**
   Most bootstrapped SaaS founders obsess over CAC, but this episode breaks down which *cheap* channels actually convert for micro-SaaS. We'll expose the channels that look good in spreadsheets but waste time, and reveal the scrappy tactics that punch above their weight.
   - Guest: A founder who hit $5K MRR using only organic/community channels
   - Talking points: Content marketing ROI at low budgets; leveraging niche communities; when to say no to paid ads

2. **"Pricing Your First SaaS: The Mistakes I Made (So You Don't)"**
   Most bootstrapped founders either undercharge drastically or pick pricing with zero validation. This episode covers how early pricing decisions ripple through your entire business, and the tactical framework for setting prices when you have no comparable product.
   - Guest: Founder who pivoted pricing mid-journey and saw revenue jump 3x
   - Talking points: Value-based vs. cost-based pricing for unknown markets; psychological pricing tricks that work; price testing without losing customers

3. **"Burnout Isn't a Flex: Why Sustainable Bootstrapping Beats the Hustle Myth"**
   Solo founders shipping fast often crash by month 8. This episode tackles realistic work schedules, saying no to features, and mental health checkpoints that keep you alive for the long game.
   - Guest: A founder who burnt out, rebuilt, and hit $8K MRR working 25 hours/week
   - Talking points: Red flags that signal burnout early; building systems so you're not the bottleneck; batching work to reclaim weekends

4. **"The Refund Apocalypse: When Your Product Isn't Ready (But You Launched Anyway)"**
   Shipping early means customers will ask for refunds. This episode explores how to handle refund requests gracefully, when to say yes, and how refund patterns actually tell you what's broken in your product.
   - Guest: Founder who had 40% refund rate, fixed it in 6 weeks, and learned the most from those refunds
   - Talking points: What high refund rates really mean; building refund communication into your brand; using refunds as UX research

5. **"No Runway, No Problem: Revenue-First Product Development"**
   Unlike VC-backed startups, bootstrapped founders can't afford to build in a vacuum. This episode digs into building features customers will literally pay for on day one, and the reverse engineering it takes to get there.
   - Guest: Founder who presold before building; another who uses landing pages to validate before coding
   - Talking points: Landing page validation frameworks; building the smallest MVP that charges; customer interviews that actually uncover willingness-to-pay

6. **"The Lonely Founder Problem: Building Community While Building Your SaaS"**
   First-time solo founders often isolate themselves. This episode covers finding your people, building publicly without looking desperate, and how a small community becomes your best marketing engine.
   - Guest: Founder who built a 2K-person Discord/community around their SaaS niche
   - Talking points: Where to find your first 100 evangelists; public building vs. oversharing; turning community into beta testers and customers

7. **"Stupid Expenses That Killed My MRR (And How to Avoid Them)"**
   Bootstrapped margins are thin. This episode audits real founder spending disasters—tools they didn't need, hosting overkill, unnecessary subscriptions—and shows how to stay lean without breaking the product.
   - Guest: Two founders sharing their biggest "I wasted HOW much on that?" moments
   - Talking points: Tools/services worth paying for vs. free alternatives; infrastructure costs at different scales; the real cost of technical debt

8. **"Competing Against Goliath: How Micro-SaaS Wins Against Established Players"**
   Your competitor has 10x the team and funding. This episode explores how constraints become advantages: speed, focus, and serving one customer segment obsessively beats doing everything okay.
   - Guest: Founder who directly competes with a VC-backed company and is winning share in one vertical
   - Talking points: Positioning against bigger players; the "boring niche" strategy; customer service as a moat when you're tiny

9. **"The Hiring Question: Should Your First Employee Be Your First Mistake?"**
   Bootstrapped founders often hire too early to "take things off their plate." This episode explores the real ROI of your first hire, when you actually need one, and what tasks to offshore vs. keep.
   - Guest: Founder who hired at $3K MRR and regretted it; another who waited until $10K MRR
   - Talking points: Operational tasks worth outsourcing early (payroll, customer support); red flags for premature hiring; contractor vs. employee economics

10. **"From Side Project to $10K MRR: The Exact Timeline and Milestones That Matter"**
    Most founder narratives skip the middle. This episode reverse-engineers the journey from zero to $10K, with real timelines, what actually moves the needle at each stage, and why month 6-9 is the danger zone.
    - Guest: Founder who's made it to $10K+ MRR in the last 12 months; someone still on the journey documenting it
    - Talking points: Stage-specific metrics to optimize (early: signups; mid: retention; growth: CAC); the inflection points between $1K, $5K, $10K MRR; realistic growth trajectories vs. unicorn fiction
Judge notes: Exceptionally well-targeted output that directly fulfills the query intent with 10 highly specific, actionable podcast topics perfectly aligned to the stated audience (bootstrapped SaaS founders under $10K MRR), each with compelling hooks, realistic guest suggestions, and tactical talking points that would resonate with the niche.
Grok 4.1 Fast Reasoning 9/10
1. **$497 Lifetime Deals: My Risky MRR Booster**  
   I ditched monthly subs for one-time deals and hit $4k MRR in 90 days—here's the exact playbook for solo founders scared of churn.  
   - Talking point: Pricing psychology for impulse buys under $10k MRR.  
   - Talking point: Tools to handle fulfillment without support overload.  
   - Guest type: Founder who scaled via LT deals then pivoted back.

2. **Support Ticket Black Hole: 90% Automation Stack**  
   Juggling 50 tickets/week solo nearly killed my SaaS—until I built this no-code bot army that freed 20 hours/month.  
   - Talking point: Zapier + Intercom flows for instant replies.  
   - Talking point: When to escalate vs. ignore for retention.  
   - Guest type: Solo dev with a 99% automated support SaaS.

3. **AI Copilots for Code & Copy: Under $50/mo**  
   Forget $100k AI builds—I'm using these obscure tools to ship features 3x faster without VC hype.  
   - Talking point: Cursor + Claude for solo MVP iteration.  
   - Talking point: Prompt hacks for landing page A/B tests.  
   - Talking point: Burnout-proof daily AI rituals.

4. **PH Launch Autopilot: $1.8k MRR from Zero Prep**  
   No influencers, no hype video—just a scripted solo launch that spiked my waitlist 400% overnight.  
   - Talking point: Comment bot alternatives for real engagement.  
   - Talking point: Post-PH churn fixes.  
   - Guest type: First-timer who hit top 5 on PH bootstrapped.

5. **<50 User Retention: The "Nudge Engine"**  
   At $2k MRR, one churn email sequence rescued 70% of at-risk users—tactical setup inside.  
   - Talking point: Custom Mixpanel dashboards for solo monitoring.  
   - Talking point: Personalized win-back DMs via LinkedIn.  
   - Talking point: Pricing tier tweaks based on usage data.

6. **Day 1 Quit Notice: $3.5k MRR Safety Net**  
   I gave notice at sub-$5k MRR with this 6-month runway checklist—exact numbers and red flags for your leap.  
   - Talking point: Emergency MRR multipliers (e.g., agency upsells).  
   - Talking point: Health insurance hacks for indie hackers.  
   - Guest type: Ex-corp founder who bootstrapped the switch.

7. **Copycat Swarm: Solo IP Moats That Stick**  
   Three rip-offs launched in a month, but my obfuscation tricks kept 85% market share—code-free defenses revealed.  
   - Talking point: Frontend wrappers to hide API logic.  
   - Talking point: Community lock-in via private Discords.  
   - Talking point: Legal boilerplate for cease-and-desists.

8. **Solo SEO: #1 Rankings with 5 Hours/Week**  
   No agency, no budget—hacking Ahrefs-free keyword clusters to drive 60% of my $6k MRR organically.  
   - Talking point: GSC + Frase.io for content gaps.  
   - Talking point: SaaS-specific long-tail queries.  
   - Guest type: Technical founder ranking multiple tools top 3.

9. **Burnout Reboot: From 0 Code to $1k MRR in 30 Days**  
   Bedridden for weeks, I clawed back with micro-habit stacks tailored for code-fatigued solos.  
   - Talking point: 15-min Pomodoro for feature ships.  
   - Talking point: Nootropics + naps for focus without crash.  
   - Talking point: Accountability apps that actually work solo.

10. **Paid-Only Pivot: Ditching Freemium at $800 MRR**  
    Freemium bled me dry until I flipped to invite-only paid—doubling LTV overnight with this migration script.  
    - Talking point: Grandfathered free user upgrades.  
    - Talking point: Trial caps that convert 40%.  
    - Guest type: Founder who A/B tested models live.
Judge notes: Excellently tailored to the specific podcast niche with concrete, actionable episode ideas featuring realistic MRR figures, tactical talking points, and relevant guest types that directly match the target audience of bootstrapped technical founders.

What makes these work

  1. 01
    Feed it your constraints upfront

    Specify episode length, format (solo, interview, panel), audience sophistication, and topics you've already covered. The model cannot read your RSS feed, so topics you don't exclude will get suggested again. Every constraint added removes a class of generic output.

  2. 02
    Ask for structured output

    Request each idea with a working title, one-line angle, target listener takeaway, and guest archetype. This forces the model past surface-level topics into something you can actually slot into a production calendar. Unstructured topic lists are 30% usable; structured ones hit 70%.

  3. 03
    Batch by theme, not volume

    Instead of asking for 50 random topics, ask for 10 topics on one subtheme, then 10 on another. Thematic batches produce more cohesive seasons and surface gaps the model wouldn't fill in a scattered list. It also makes A/B testing which themes resonate easier.

  4. 04
    Regenerate with a rejection list

    After the first pass, paste back which 3-5 ideas were weak and why. The model recalibrates on the second pass and avoids the same traps. This iterative loop is where AI topic generation goes from passable to genuinely useful.

More example scenarios

#01 · B2B SaaS founder podcast, season planning
Input
My podcast interviews early-stage B2B SaaS founders about go-to-market. Audience is 0-to-1 founders pre-Series A. We've covered pricing, first 10 customers, and cold outbound. Generate 8 topic ideas for Season 3 that avoid those themes and lean into operational problems founders hit between $1M and $5M ARR.
Expected output
1) The first sales hire nobody warns you about. 2) When your founder-led sales stops scaling. 3) Rebuilding onboarding at $2M ARR. 4) Firing your first customer. 5) The messy middle: churn you can't explain. 6) Pricing migrations without losing logos. 7) Hiring a head of marketing vs. a demand gen IC. 8) What changes when your first VP quits.
#02 · True crime podcast, fresh angle generation
Input
I host a weekly true crime podcast focused on cold cases from the 1970s-1990s in the American Midwest. I've done 60 episodes. I want 5 new episode ideas that focus on cases involving small-town police corruption or jurisdictional failures, not serial killers.
Expected output
1) The sheriff who buried the file: Galena, Illinois, 1983. 2) Two counties, one body, zero arrests. 3) The informant who disappeared before trial. 4) When the FBI walked away: jurisdictional handoffs that killed cases. 5) The evidence room fire that conveniently happened. Each framed as a 45-minute episode with a local journalist or retired detective as co-narrator.
#03 · Fitness podcast for women over 40
Input
My podcast targets women 40-55 interested in strength training and perimenopause. Format is solo episodes, 25 minutes. Give me 6 topic ideas that go beyond basic 'lift heavy' advice and address sleep, recovery, and life logistics.
Expected output
1) Why your recovery got worse at 44 and what to actually change. 2) Training around a bad sleep week without losing progress. 3) The protein math nobody explains correctly. 4) Strength training when your knees already hurt. 5) Fitting lifting into a week with teenagers and a full-time job. 6) The HRT conversation: what my doctor got wrong.
#04 · Marketing agency thought leadership show
Input
We run a performance marketing agency and are launching a podcast to attract mid-market e-commerce clients ($10M-$100M revenue). Generate 10 episode topics that demonstrate expertise without being generic 'how to do Facebook ads' content.
Expected output
1) What changed in attribution after iOS 17. 2) The $40M DTC brand that fired its agency and what happened. 3) Creative testing frameworks that survive Meta's algorithm shifts. 4) When to move budget from Meta to TikTok Shop. 5) Retention math for subscription brands. 6) Why your MER is lying to you. 7) Building a creator pipeline in-house. 8) Black Friday planning in July. 9) The email channel most brands underinvest in. 10) How to fire a vendor without losing the quarter.
#05 · Solo indie game dev podcast
Input
I'm a solo indie game developer planning a podcast for other solo devs. Topics should mix craft, business, and mental health. Give me 5 pilot episode ideas that would hook other solo devs in my Discord.
Expected output
1) The three-year game: surviving a project that won't ship. 2) Pricing your first title when you have no audience. 3) Scope cuts I regret and ones that saved the game. 4) Marketing when you hate marketing. 5) The Steam Next Fest week from the inside: wishlists, panic, and what actually moved numbers.

Common mistakes to avoid

  • Vague niche definition

    Typing 'generate podcast topics for a business podcast' gets you LinkedIn-tier generic ideas. The fix is specificity: industry, company stage, listener job title, and what they're trying to accomplish. The model matches the resolution of your input.

  • Not listing prior episodes

    Without a list of what you've covered, AI will suggest obvious topics you already aired. Paste in your last 10-20 episode titles so the model can triangulate whitespace. This single step doubles output quality.

  • Accepting the first batch

    First outputs are usually the model's safest guesses. The good ideas surface in rounds 2 and 3 after you push back with 'too generic,' 'already done,' or 'go deeper on operational pain.' Treat generation as a conversation, not a vending machine.

  • Ignoring hook quality

    A topic is only as good as its hook. If the AI returns 'Episode on customer retention,' reject it and ask for a specific angle or contrarian take. 'The retention metric every DTC founder tracks wrong' is an episode; 'customer retention' is a Wikipedia page.

  • Skipping the audience fit check

    Models will suggest topics that sound smart but don't match what your actual listeners care about. Cross-reference AI outputs against your top-downloaded episodes and audience survey data before committing. A topic you love that your audience ignores is a wasted production slot.

Related queries

Frequently asked questions

What's the best AI for generating podcast topic ideas?

It depends on your style. Claude tends to produce more nuanced, editorially framed topics with better hooks. GPT-4 is strongest for volume and structured output. Gemini handles recency-adjacent topics better thanks to search grounding. Llama works well for private or on-device workflows. The comparison table above shows the same prompt across all four.

Can AI generate podcast topics based on trending searches?

Not reliably on its own. Most models have knowledge cutoffs and can't see what's trending this week. Pair the generator with a tool like Google Trends, Exploding Topics, or Reddit search, then feed those trending themes into the prompt as input. The AI converts trends into episode angles.

How many topics should I generate at once?

Batch in sets of 10-15. Smaller batches get shallow, larger batches get repetitive. If you need 40 episode ideas for a season, run 3-4 thematic batches rather than one mega-request. Quality drops noticeably past 15 ideas in a single generation.

Will AI-generated topics sound generic?

Only if your prompt is generic. Specificity in equals specificity out. Include your niche, audience, format, and a rejection list of tired angles. Ask for contrarian framings or specific case studies rather than broad themes. The difference between generic and sharp output is entirely in the input.

Can I use this to plan a whole podcast season?

Yes, and it's one of the best use cases. Generate topics in thematic clusters (for example, 5 tactical, 5 interview, 5 contrarian), map them across a release calendar, and leave slots for timely episodes. Most creators plan 70% of a season with AI and keep 30% flexible for news and guest availability.

Is it better to generate topics before or after booking guests?

Generate topic themes first, then book guests who fit. Working backward from a booked guest leads to episodes shaped by availability rather than audience need. Use AI to define the topic map, then find guests who can credibly carry each episode.

Try it with a real tool

Run this prompt in one of these tools. Affiliate links help keep Gridlyx free.