business

Verdict

Submitted 5/20/2026, 8:54:03 AM · Completed 5/20/2026, 9:08:48 AM

5.5
pivot
The idea

Built an async storytelling RPG with real human submissions to give my Mac Mini something to do. Half nostalgia, half curiosity whether 27B/35B models can actually roleplay.

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Backstory: had a Mac Mini M4 Pro running agentic work most of the day, but still mostly idle. Started wondering whether I could use the spare cycles for something I'd actually want to play with - half nostalgia for 80s tabletop dark fantasy, half real curiosity about how small local models (Qwen 27B / 35B-A3B) would handle actual human roleplay submissions. So I made **Morndur**. It's now live. Daily 24h cycles - players write 100-500 words of prose any time during the cycle, at 20:00 CET the AI engine weaves all submissions into the next published chapter, generates per-scene illustrations, and emails (optional) each contributor a coloured diff showing where their words landed (verbatim kept = yellow, amplified = green, narrator invention = grey). Everything runs on one box. Zero cloud, no signup, no data collection, no ads. Just for fun - niche by design, but maybe someone will stick around longer. Also curious how the pipeline would hold under hundreds of submissions per cycle - the engine should be ready for that (probably). The whole point was to keep it **low-effort from the player side**. For people who don't have time to GM their own table or sit over a campaign for hours every evening, but who'd still like the sense of agency from spending three minutes a day at any time, and the curiosity of "how did it turn out" the next morning. Spiritually closer to old browser games - Travian, NationStates, Fallen London, Battles of Tenadia for the Polish folks - where you click a few things daily and a world evolves around your input, than to a sit-down tabletop session. # What surprised me * **qwen3.6:27b actually writes readable dark fantasy.** Holds tone across 600-word chapters, doesn't break the 4th wall, doesn't add disclaimers. I * **Flux 2 Klein's native multi-image conditioning** lets the same character stay visually recognisable across scenes without LoRA training. * **MoE on Apple Silicon punches above its memory footprint.** Tried qwen3.6:35b-a3b - a 35B-total / 3B-active-per-token MoE - expecting it to drag vs the 27B dense. It lands only \~20% slower per token while producing noticeably better judgement on award-picking and continuity checks. Used to think MoE was a server-class trick; not on the M4 Pro. # What broke (and what I'd change) * qwen3:8b pre-filter choked on a 1600-char player submission once. Emitted truncated JSON mid-output, parser failed, the submission was silently dropped. The player had no email registered, no notification, **no way to know**. That broke my heart. Fix was a retry chain with a larger token budget, then a fallback to the larger model, and finally - if both fail - KEEP the submission instead of REFUSE. I will not punish a player for my infra glitch ever again. * Klein renders two characters at medium-shot distance as visual duplicates. Solution wasn't a model swap, it was a paradigm shift: one-character close-ups OR wide-distant tiny figures, never medium-shot 2+. Less elegant, more reliable. # No big expectations Genuinely proud of how all the small backend tricks ended up clicking together - Chekhov's gun system for cross-cycle continuity (post-synthesis LLM extracts unresolved sensory hooks, pre-synthesis LLM picks a weighted random subset as OPTIONAL), two-pass verbatim+cosine colorize for the feedback mail, vision-loop image judge with mistral-small3.2:24b (the only sub-70B VLM I found that doesn't chain-of-thought on `format:"json"`) - none of them looked like much alone, but the sum reads OK. # Two things I'd love feedback on **Engagement on dead cycles.** If no one writes during a 24h window, I have escalating in-world LLM-composed reminder posts on Mastodon + Bluesky (T+0, T+4d, T+7d, T+14d, T+21d, T+45d-final). Not sure if the tone is right or if I should do something else entirely. **Cadence of structural shifts.** There's no formal "end" of the story - the adventure just keeps going as long as players keep writing. Deaths, faction reveals, time skips happen organically between cycles. Should I plan harder seasonal arcs and a real ending, or trust that the unstructured pull of "what happens next" is enough by itself? Honest opinions welcome, including "the question itself is wrong." Not selling anything - happy to talk specifics on any piece if anyone is curious. Try it, break it - there are AI moderators and guardrails in place, so a successful break would actually be a useful bug report. Would genuinely love to see real submissions land. morndur.com
TRIZ inventive level: 3/5· Principles: parameter changes, self-service
Synthesis verdict
**Pivot**. Morndur is a technically impressive niche experiment with a unique blend of dark fantasy role-playing and AI-generated content. The project's technical foundation, use of pre-trained local models, and absence of cloud infrastructure are notable strengths. However, the lack of a monetization path and the potential risks associated with regulatory scrutiny, hardware failure, and scaling pressure are significant weaknesses. To move forward, it's essential to address these weaknesses and explore revenue streams, such as paid tiers or sponsorships, to ensure the project's sustainability.

Strengths

  • Unique blend of dark fantasy role-playing and AI-generated content
  • Technically impressive implementation using pre-trained local models
  • Absence of cloud infrastructure and data collection
  • Strong alignment with the 'low-effort, high-agency' design philosophy
  • Novel mechanics, such as colored-diff feedback and per-scene illustration pipeline

Weaknesses

  • Lack of a monetization path
  • Potential risks associated with regulatory scrutiny
  • Hardware failure and single-point dependency
  • Scaling pressure and limited resources
  • No clear plan for engagement sustainability

Best angle

Morndur should pivot to a community-driven, subscription-based model to ensure sustainability and explore additional revenue streams, such as sponsorships or donations, to support its unique blend of dark fantasy role-playing and AI-generated content.

Panel verdicts

Competition

nvidia/nemotron-3-nano-omni-30b-a3b-reasoning

8.0

Morndur's defensible edge lies in its on‑device, privacy‑first infrastructure that enables a unique, real‑time feedback and illustration system impossible for cloud‑based competitors.

The concept combines a highly specific niche (80s dark‑fantasy tabletop roleplay) with a technically demanding stack that runs entirely on a single consumer‑grade Mac Mini, using local LLMs (Qwen‑3.6 27B/35B‑A3B) and MoE inference on Apple Silicon. Existing alternatives - NationStates, Fallen London, and similar incremental world‑building platforms - rely on cloud services, require user accounts, and collect data for advertising or analytics, which directly conflicts with Morndur's zero‑signup, zero‑data‑collection philosophy. The colored‑diff feedback, per‑scene illustration pipeline, and Chekhov's‑gun continuity system are novel mechanics that are difficult to replicate without the same low‑latency, on‑device inference environment. While the player base will inevitably be small, the technical moat (running 27‑35 B‑parameter models locally with acceptable latency) and the strong alignment with the "low‑effort, high‑agency" design create a durable differentiation that is unlikely to be copied by mainstream competitors. The main risk is engagement sustainability, but the defensibility of the core technology and the unique feedback loop make the differentiation real and durable.

Viability

meta/llama-4-maverick-17b-128e-instruct

8.0

The use of pre-trained local models and a simple, self-contained architecture makes it feasible for a small team to build and maintain Morndur.

The idea of Morndur, a dark fantasy role-playing platform that leverages AI to weave player submissions into a narrative, is technically feasible for a solo or 2-person team to build within 4-12 weeks. The existing implementation already runs on a single Mac Mini M4 Pro, utilizing local models like Qwen 27B and Flux 2 Klein for text and image generation. The technical complexity is mitigated by the use of pre-trained models and the absence of cloud infrastructure, sign-up processes, and data collection. However, scaling the pipeline to handle hundreds of submissions per cycle may require additional optimization. The developer has already demonstrated adaptability in addressing issues, such as implementing a retry chain for handling large player submissions and adjusting the image generation paradigm to avoid character duplication. The key challenges lie in maintaining the robustness of the pipeline under increased load and ensuring player engagement during dead cycles. Overall, the project's technical foundation and the developer's problem-solving approach suggest that a solo or 2-person team could realistically build and iterate on this concept within the given timeframe.

Monetization

mistralai/mistral-medium-3.5-128b

3.0

A technically impressive niche experiment with zero revenue capture is a 3/10 business venture.

Morndur is a passion project with no monetization path - zero pricing, no signup, no ads, and no data collection. The unit economics are unsustainable: hardware costs (M4 Pro), electricity, and maintenance are absorbed without revenue. Even if scaled to hundreds of users, the model relies on a single machine with no clear cost-to-serve offset. The engagement mechanics (daily cycles, diff emails, AI-generated content) are clever but don't capture value. Niche appeal and low-effort UX are strengths, but without a revenue model (e.g., paid tiers, sponsorships, or donations), this remains a hobby. The surprise technical wins (Qwen3.6, Flux 2 Klein) are irrelevant to monetization. Fixes for edge cases (retry chains, fallback models) improve reliability but don't address the core issue: no path to profitability.

Market

qwen/qwen3-next-80b-a3b-instruct

8.0

Morndur succeeds not by attracting masses, but by turning passive readers into quiet co-authors who return daily not for reward, but for the emotional resonance of being part of something that remembers them.

Morndur taps into a highly specific but deeply underserved niche: busy adults who crave immersive, low-effort narrative agency without the overhead of traditional tabletop RPGs or persistent online worlds. The audience is not broad, but it's intensely loyal - think fans of NationStates, Fallen London, and browser-based slow-burn storytelling, estimated at 50K - 200K globally based on community sizes of similar niche interactive fiction platforms. What makes this compelling is the emotional hook: the quiet thrill of seeing your 3-minute prose woven into a living dark fantasy, with visual and textual feedback that validates participation without demanding more time. The technical execution is remarkable - running Qwen 35B-A3B on an M4 Pro with zero cloud dependency is a feat of optimization that appeals to privacy-conscious, anti-ad, anti-signup users. The silent submission drop bug was a critical flaw, but the fix demonstrates user-centric design. Engagement on dead cycles is smart but risks sounding desperate; the tone should shift from reminder to atmospheric lore drip - e.g., 'The Whispering Library has gone quiet...' - to preserve immersion. Structural openness is the product's soul; forcing arcs or endings would betray its organic charm. The real opportunity isn't monetization yet - it's community cultivation. If 1% of this niche engages consistently (500-2000 active players), Morndur becomes a cult classic. It's not a product for scale; it's a ritual for the devoted.

Risk

openai/gpt-oss-120b(fallback #1)

3.0

A free, single‑machine AI storytelling service cannot survive legal scrutiny, hardware failure, or scaling pressure beyond a few months.

1. **Regulatory hammer** - By stitching together user‑generated prose with a proprietary LLM and auto‑publishing it, Morndur creates a thin line of liability for defamation, hate speech, and copyrighted material. EU's AI Act and US state‑level AI disclosure laws are already demanding provenance logs and human‑in‑the‑loop safeguards. The current "no‑signup, no‑data‑collection" stance means you have no audit trail, so a single complaint can trigger a forced shutdown or massive legal fees within months. 2. **Platform fragility** - The entire pipeline lives on a single M4 Pro Mac Mini. A macOS update that changes memory handling, a failing SSD, or a firmware bug in the MoE runtime will crash the model serving stack. Because the service is live 24/7, any downtime instantly erodes trust; with no redundancy, a hardware failure is a single point of failure that can kill the project in weeks. 3. **Zero‑budget churn** - The model runs locally to avoid cloud costs, but each 24‑hour cycle with "hundreds of submissions" already pushes the box to its limits. As word‑of‑mouth brings more players, token‑budget overruns will cause slower generation, missed deadlines, and broken email diffs. Without any revenue stream, you cannot upgrade hardware or add redundancy, so the moment the user base outgrows the box, the service becomes unusable and disappears. These three concrete failure points - legal exposure, single‑point hardware dependency, and unsustainable free‑to‑play scaling - will likely terminate Morndur within a year.

Synthesized by meta/llama-3.3-70b-instruct · 30.6s