what are some things one can do to find divergent ideas. that lives in the fringes. but might solve emergent or near emergent problems.

divergent-ideas.md

Finding divergent “fringe” ideas that might solve emerging problems works best as a repeatable practice: systematically scan for weak signals, spend time with lead users at the edge of need, and then rigorously stress-test the ideas before investing heavily.[1][2]

Scan for weak signals

Horizon scanning is a structured way to look for early signs (weak signals) of potentially important developments that sit outside mainstream attention today.[3][1]

• Build a weekly “signal feed” from places where novelty appears early (new research, niche forums, small startups, policy pilots), and tag each item as “new capability,” “new constraint,” or “new behavior,” because weak signals are often subtle indicators of emerging issues.[2][4]
• Keep a “fringe log” and deliberately include signals from subcultures and non-obvious domains, since some public-sector scanning programs explicitly target fringe areas to broaden what gets noticed.[5]

Find lead users

The lead user approach focuses on people who experience needs earlier than the mainstream and often create their own workarounds or prototypes.[6][7]

• Identify groups living with the problem in a more extreme form (high frequency, high cost of failure, or unusual constraints), because lead user methods intentionally look at the “leading edges” and even “analogue markets.”[7]
• Ask for artifacts, not opinions (spreadsheets, scripts, custom hardware, checklists), because the most valuable “divergent” idea is often already embodied in a hack someone built to survive the edge case.[7]

Explore adjacent possibilities

The “adjacent possible” framing treats innovation as expanding from what’s currently feasible into nearby new combinations rather than betting on distant sci‑fi leaps.[8]

• Do “analogy jumps”: for each emerging problem, study a field that already solved a harsher version of it (e.g., aviation safety → hospital handoffs), aligning with the idea that solutions can come from just-one-step-away option sets.[8]
• Run short ethnographic observations (watch real work in context), because ethnography is widely used to uncover needs people don’t clearly articulate in interviews and can reveal hidden constraints that generate novel solution directions.[9][10]

Stress-test before you scale

Red teaming is explicitly about subjecting plans and assumptions to rigorous challenge to uncover blind spots and flaws in logic.[11]

• Do an “assumption audit” on each promising fringe idea (What must be true? What would falsify it?), because red teaming is meant to challenge assumptions and stress-test plans.[11]
• When feasible, use “skin-in-the-game” forecasting (like prediction markets) to aggregate dispersed beliefs about what will work, since research comparing markets vs. polls finds prediction markets can be strong long-run forecasting tools in some settings.[12][13]

What domain are the “near-emergent problems” in (e.g., AI safety, climate adaptation, healthcare operations, cybersecurity, education), so the most relevant fringe idea sources can be suggested?

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Finding divergent ideas that exist on the fringes to solve emergent problems requires a shift from standard "brainstorming" to active "horizon scanning" and engagement with non-traditional communities.

Here are actionable strategies to identify and utilize these ideas:

1. Identify and Monitor "Lead Users"

"Lead users" are individuals or groups who face needs months or years before the bulk of the marketplace encounters them and often create their own solutions. These users frequently inhabit fringe communities where regulatory or commercial constraints are absent.[1]

• Where to find them: Look for communities practicing "permissionless innovation."
  • DIY Biology & Biohacking: Platforms like DIYbio.org, Genspace, or BioHack Academy are hubs for citizen scientists conducting experiments outside formal institutions.[2][3]
  • Open Hardware & Maker Repositories: Scan GitHub or Instructables for "work-around" projects. For example, during the COVID-19 pandemic, maker communities shared designs for 3D-printed medical supplies (e.g., valves, face shields) long before supply chains could catch up.[3]
  • Niche Forums: Specialized subreddits or Discord servers often host discussions where users share "hacks" for existing products that reveal unmet needs.

2. Scan "Pre-Emergent" Knowledge Repositories

By the time an idea is published in a major journal or news outlet, it is often no longer "fringe." To catch ideas in their raw, emergent state, you must look at "grey literature" and pre-prints.

• Pre-print Servers: Regular scanning of repositories like arXiv (physics, CS), bioRxiv (biology), or SSRN (social sciences) allows you to see research before peer review. These papers often contain novel methodologies that might be filtered out by conservative peer-review processes.[4][5]
• Patent Outliers: Analyze "outlier patents"—filings that cite no "adjacent" technologies or combine varying technical fields (e.g., a biological patent citing a textile manufacturing process). These "long-distance" combinations often signal a radical shift in approach.[6][7]
• Grey Literature: Reports from think tanks, NGOs, and PhD theses often contain detailed data on niche problems that haven't hit the mainstream news cycle.[8]

3. Practice "Exaptation" (Repurposing)

Exaptation is the process of taking a trait or technology developed for one function and coopting it for a different use. This is a primary mechanic for solving emergent problems quickly, as it skips the long R&D cycle.[9]

• Search for Analogies: When facing an emergent problem (e.g., a new supply chain crisis), ask: "Who else solves a problem of 'flow' under extreme constraints?" You might look to ant colony researchers or fluid dynamics experts rather than logistics consultants.[10]
• Crisis as a Trigger: History shows exaptation spikes during crises. For instance, IKEA hacks—where users modify furniture for disability needs—are a form of "problem-first exaptation" that solves social exclusion issues the original designers ignored.[11][12]

4. Utilize "Directed Fiction" and Worldbuilding

To solve emergent problems (those that are just forming), you need to envision the context in which they will exist. Science fiction and foresight tools allow you to prototype solutions for worlds that don't quite exist yet.

• Worldbuilding: Instead of predicting the future, build a detailed scenario of a possible future (e.g., "A world where antibiotics no longer work"). Then, "test" divergent ideas within that narrative to see if they solve the problems of that specific world.[13]
• Directed Fiction: Use narrative storytelling to bridge the gap between hard data and human experience. This helps identify the social or ethical problems a new technology might create, which are often the "emergent problems" that catch organizations off guard.[14]

5. Detect "Weak Signals"

Weak signals are ambiguous snippets of information that indicate a potential change but aren't yet a trend.

• Fringe Interactions: Pay attention to "fringe interactions" on social platforms—topical discussions that attract vulnerable users or outliers. These can be early indicators of social unrest or shifting cultural values that mainstream moderation or algorithms might suppress.[15]
• Automated Scanning: While manual scanning is useful, AI tools (like those used for horizon scanning) can help aggregate these signals from thousands of multilingual sources to detect patterns invisible to the human eye.[16]

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follow up questions:
How to run a fringe focused horizon scanning session

Methods to surface weak signals in customer feedback

Techniques to recruit diverse fringe perspectives quickly

How to combine fringe ideas with core capabilities safely

Tools for mapping idea fringes to emerging problems

Scanning the Fringes

Finding divergent ideas that address emergent problems requires deliberately looking beyond mainstream sources and conventional thinking patterns. Weak signals scanning and horizon scanning are established foresight techniques that help identify early signs of change before they become widely recognized.[1][2][3][5]

Discovery Methods

Monitor fringe sources and subcultures

• Review academic journals, popular media, and fringe sources systematically to identify emerging patterns[3]
• Study subcultures and edge communities, as they often serve as key innovators who combine existing elements in novel ways[1]
• Engage with practitioners, entrepreneurs, and people coping with problems daily, not just traditional experts[4]

Apply divergent thinking techniques

• Use the Six Thinking Hats method to examine problems from multiple perspectives including intuitive, creative, and emotional angles[7]
• Practice SCAMPER (Substitute, Combine, Adapt, Modify, Put to other uses, Eliminate, Reverse) to transform existing ideas rather than creating entirely new ones[7]
• Generate random stimuli and embrace unconventional connections—even simple activities like walking can enhance creativity[8][2]

Establish systematic scanning processes

• Develop clear research hypotheses about where to look and what types of signals are relevant before beginning your scan[1]
• Challenge credible assumptions about the future to extend your radar into unconventional territory[1]
• Create recurring meetings or dedicated spaces where weak signals can be shared and clustered into thematic patterns[10]

Practice lateral thinking

• Deliberately set aside obvious solutions to study alternatives from all possible angles[8]
• Apply subtractive thinking by removing elements rather than adding them[8]
• Question established beliefs and seek multiple solutions instead of converging too quickly on a single answer[9]

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followup questions:

Techniques to find weak signals and fringe trends

How to run a scanning exercise for emerging problems

Methods to recruit diverse perspectives for ideation

Ways to structure divergent thinking sessions for novelty

Tools to map and prioritize fringe ideas quickly

You can reliably find fringe, divergent ideas by building a repeatable “edge-scanning” pipeline: go where incentives are weird, language is new, and prototypes exist—then pressure-test signals with small bets. The prompt in the linked gist is essentially about hunting solutions that sit outside the mainstream but match near-emergent problems.[1]

The edge isn’t random

“Fringe” ideas tend to cluster around constraints: communities that can’t afford the mainstream solution, people operating under novel regulations, or domains where tooling is immature. In practice, divergent thinking works best when you intentionally generate many candidate directions before filtering hard—quantity first, judgment second.[2][1]

Where to look (on purpose)

Use a handful of “collection surfaces” that naturally amplify weird-but-real work:

• Constraint-heavy operators: disaster response, accessibility, small municipalities, under-resourced clinics, small-scale manufacturing.
• Open experiments: niche OSS repos, maker communities, preprint culture, and “ugly” prototypes that still ship.
• Incentive-misaligned corners: forums where people complain about a problem they must solve anyway (compliance, latency, procurement, legacy hardware).

This matches the gist’s intent: finding ideas that live at the periphery but might unlock solutions to emerging needs.[1]

How to separate signal from noise

Treat every fringe idea as a hypothesis with a costed test, not an identity to believe in.

• Translate the idea into a “chain” of steps you can run repeatedly (inputs → operations → outputs), so it can be varied and compared across contexts.[3]
• Force “format pressure”: if you can’t express the idea as a small, modular artifact (a checklist, a spec, a template, a runnable demo), it’s probably not ready.[4]
• Score with three numbers: pain intensity, time-to-first-result, and dependency count (lower dependencies usually win early).

This operational, template-driven framing mirrors the practical, systems-minded tone typical of André’s Substack posts.[5]

A weekly edge-scanning ritual

Keep it lightweight so it actually persists:

• 30 minutes: collect 10 oddities (links, screenshots, notes) from your chosen surfaces.
• 30 minutes: rewrite each oddity as “problem → mechanism → cheap test.”
• 30 minutes: run 1 cheap test (email 3 practitioners, build a throwaway mock, replicate a claim, or simulate constraints).

Over time, this turns “fringe exploration” into a compounding dataset instead of a vibe.

What domain are the “emergent problems” in (AI tooling, climate adaptation, local governance, health, education, something else)?

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Based on the eoncodes.substack.com style I've analyzed, here's an essay in that format:

---

Finding Divergent Ideas at the Fringes

The breakthrough solutions to tomorrow's problems exist today—you just need to know where to look

🚨 The Problem

Most organizations gravitate toward mainstream solutions.[1]

Conventional thinking produces conventional results—no breakthroughs.

Emergent problems require novel approaches, not recycled best practices.[2]

💡 The Solution

Seek ideas at the fringes—where conventional wisdom breaks down.[1]

Cultivate divergent thinking practices that explore multiple solution pathways.[3]

Build systems for discovering, evaluating, and testing unconventional approaches.[4]

Why Fringe Ideas Matter

Divergent thinking involves generating creative ideas by combining diverse information in novel ways. While convergent thinking narrows options to find the "right" answer, divergent thinking expands the solution space—exploring possibilities without immediate judgment.[3][1]

The most valuable innovations often emerge from the margins because fringe ideas aren't constrained by established frameworks. They represent unexplored combinations, untested assumptions, and perspectives overlooked by mainstream thinking.[5][2]

Where to Look for Divergent Ideas

Adjacent industries and disciplines

• Study how other fields solve similar problems
• Cross-pollinate methods from unrelated domains
• Look for transferable patterns and principles

Emerging research and preprints

• Monitor arxiv.org and field-specific preprint servers
• Follow early-stage research before it reaches consensus
• Engage with work that challenges established theories

Edge communities and subcultures

• Explore niche forums, Discord servers, and Substacks
• Find communities solving problems differently
• Engage with practitioners outside traditional channels

Failed experiments and abandoned projects

• Review what didn't work—and why it failed
• Consider whether context has changed to make old ideas viable
• Extract lessons from well-documented failures

Contrarian thinkers and iconoclasts

• Follow individuals who consistently challenge orthodoxy
• Read critics of dominant paradigms in your field
• Engage with perspectives that make you uncomfortable

Practical Discovery Methods

Set up monitoring systems:

• Create RSS feeds for fringe publications and blogs
• Use Twitter lists for contrarian voices
• Configure alerts for emerging keywords and concepts

Practice structured divergence:

• Use brainstorming techniques without immediate filtering[4]
• Employ mind mapping to discover unexpected connections[1]
• Reframe problems as open-ended questions[1]

Cultivate cognitive flexibility:

• Switch perspectives deliberately—adopt opposing viewpoints[1]
• Challenge your own assumptions before evaluating ideas
• Separate idea generation from idea evaluation[5]

Build an idea capture system:

• Document fringe concepts without judgment
• Tag by problem domain, not by feasibility
• Review periodically as contexts change

Evaluating Fringe Ideas

Not every fringe idea is valuable—but dismissing ideas prematurely kills innovation. Instead:[5]

• Assess whether the idea addresses a real emerging problem
• Identify what assumptions would need to be true for it to work
• Consider low-cost experiments to test core hypotheses
• Look for partial applications even if the full idea isn't viable

Use convergent thinking only after exploring broadly—shortlist multiple promising approaches and prototype quickly to discover what works.[5]

Implementation Flow

1. Discovery phase: Cast a wide net across fringe sources
2. Documentation: Capture ideas without filtering
3. Pattern recognition: Identify themes and connections quarterly
4. Hypothesis formation: Develop testable assumptions
5. Rapid experimentation: Run small, low-cost tests

The goal isn't to implement every fringe idea—it's to ensure you're not trapped by conventional thinking when facing novel problems.[2]

Resources

Divergent thinking research: Understanding the cognitive science behind creative ideation[3]

Mind mapping tools: Visual tools for discovering unexpected connections[1]

Convergent vs divergent balance: When to expand possibilities and when to narrow[4]

Human creativity thrives at the intersection of broad exploration and focused execution—make sure your discovery process includes both 🚀

---

This essay follows the eoncodes.substack.com format with its problem/solution structure, practical focus, clear sectioning with bullets and bold headers, technical resources, and conversational-but-direct tone that prioritizes actionable information.[6][7]

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Based on the GitHub Gist content about finding divergent ideas that exist on the fringes but could solve emergent problems, and the eoncodes.substack.com writing style, here's the essay:[1][2]

---

Hunting for Fringe Ideas: A Practical Guide to Finding Divergent Solutions

The best answers to tomorrow's problems are hiding in today's weird corners

🚨 The Problem

Most innovation happens at the center—where everyone is looking, where consensus lives, where ideas feel safe.[3]

The fringe is uncomfortable. It's where unconventional thinkers dwell, where ideas sound ridiculous until they don't.

But emergent problems require emergent solutions. And those rarely come from the mainstream.

💡 The Solution

Deliberately seek out ideas that live on the edges.[4]

Build systems that capture signals from unconventional sources before they become obvious.

Create frameworks that help you identify which fringe ideas might actually solve real problems.

Why Fringe Ideas Matter

Divergent thinking explores multiple possible solutions rather than converging on a single answer. When you're facing emergent or near-emergent problems—challenges that don't yet have established playbooks—you need approaches that haven't been tried yet.[3]

The fringe is where tomorrow's mainstream solutions are born. Cloud computing was fringe. Remote work was fringe. Now they're standard operating procedure.

Where to Look

Academic preprint servers: ArXiv, bioRxiv, SSRN contain research before peer review—raw, unfiltered, sometimes brilliant.[5]

Niche online communities: Subreddits with under 10K members, Discord servers for obscure interests, specialized forums where deep expertise congregates.

Adjacent industries: Solutions in biology might solve software problems. Music production techniques might inform interface design.

Failed startups: Companies that died often had one brilliant idea buried in a flawed execution. Their postmortems are goldmines.

Contrarian thinkers: Find people who consistently disagree with consensus—not because they're contrary, but because they see different patterns.

Capture and Evaluation Framework

Use a divergent-convergent-distillation process to manage fringe ideas:[5]

Divergent Phase: Collect everything without judgment. Create separate documents for each idea source using descriptive naming like biotech-solutions-username.md. No filtering yet—just capture.[5]

Convergent Phase: Group similar concepts. Look for patterns across different domains. Identify which fringe ideas address your specific emergent problem.[5]

Distillation Phase: Extract the essence. Write a one-page synthesis. Create an action plan for testing the most promising concepts.[5]

Six Thinking Hats for Edge Cases

Apply de Bono's lateral thinking technique to evaluate fringe ideas from multiple angles:[4]

• White Hat: What data supports this unconventional approach?
• Red Hat: What's your intuitive reaction? Does it feel right?
• Black Hat: What could go catastrophically wrong?
• Yellow Hat: What's the best-case scenario if this works?
• Green Hat: How could this idea be modified to work better?
• Blue Hat: What's the meta-pattern here? What does this tell us about problem-solving?

Setting Up Your Fringe Idea Repository

Create a GitHub repository for collaborative divergent thinking:[5]

• Initialize with .gitignore containing *view* to exclude personal synthesis files
• Each contributor creates topic-name.md files for their ideas
• Use scripts or AI to generate summary views without conflicts
• Pull frequently to see others' contributions
• Let ideas accumulate before attempting to organize them

Practical Safeguards

Time-box your fringe exploration: Spend 20% of research time on unconventional sources. Too much and you lose grounding; too little and you miss breakthroughs.

Validate against first principles: Fringe ideas should violate conventions, not physics. Check whether they're genuinely novel or just repackaged conventional wisdom.

Look for weak signals becoming stronger: The best fringe ideas show up multiple times from independent sources before they break through.

📚 Resources

Divergent Work Using GitHub: Methodology for conducting creative thinking using GitHub and plain text[5]

Six Thinking Hats: Edward de Bono's lateral thinking framework for examining problems from multiple perspectives[4]

Convergent vs. Divergent Thinking: Understanding the balance between exploration and execution[3]

Subject Mapping Techniques: Visual organization methods for capturing and connecting ideas[4]

---

The future belongs to those who can see it coming from the edges.

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Based on the content structure of eoncodes.substack.com and the themes present in the provided Gist title ("finding divergent ideas," "lives in the fringes," "emergent problems"), here is the essay rewritten in the style of André J.

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The Architecture of the Fringe

Why the solutions to near-emergent problems are hiding in the noise, not the signal.

André J
Dec 15, 2025

The modern intellectual landscape is an optimization engine. We are exceptionally good at convergence—taking a known problem, applying a known framework, and iterating toward a local maximum. But as we face a new class of emergent problems—challenges that arise from complex system interactions rather than linear causal chains—optimization fails. You cannot optimize a solution for a problem you haven’t yet defined.

To solve problems that are "near emergent"—visible only as faint signals on the horizon—we need to abandon the center. The center is crowded with mimetic desire and consensus thinking. The answers we need live in the fringes.

Divergent thinking isn't just "brainstorming" or "thinking outside the box." It is a deliberate architectural choice to query the database of reality where the index is broken. Here is a systematic protocol for mining the fringes to solve the problems others haven't seen yet.

1. Audit the "Dead" Branches

In biological evolution, dead ends are just features that didn't fit the current environment. In technology and philosophy, "dead" ideas are often just premature.

• Excavate the pre-consensus: Look at solutions proposed before a dominant standard took over. If we are solving for a new environment (e.g., post-LLM coding), old "failed" ideas (like Smalltalk’s image-based persistence or Xanadu’s transclusion) might suddenly be viable.[1][2]
• Action: Read the "rejected" proposals of major standards committees. The fringe is often populated by the "technically superior but politically impossible" options of the past.

2. Invert the Constraint Function

Emergent problems often look unsolvable because we view them through legacy constraints. Divergent ideas appear when you treat a hard constraint as a variable.

• The "Impossible" Parameter: Identify the one variable everyone assumes is fixed (e.g., "compute is expensive," "latency is unavoidable," "trust requires centralization").
• The Null Hypothesis: Build a mental model where that constraint is zero. What architecture emerges? This is how we move from "faster horses" to "warp drives."
• Action: Take a near-emergent problem (like AI agent drift) and apply disruptive brainstorming—force a solution that violates a core assumption of the field.[3]

3. Cross-Index Incompatible Domains

The most potent divergent ideas come from "conceptual collisions" between domains that share no vocabulary.

• Biological Mimicry in Silicon: We often try to solve software problems with more software logic. Instead, look at how biological systems handle similar emergent issues—waste management (garbage collection), defense (immunology), or resource allocation (mycelial networks).[4][5]
• Action: When stuck on a system architecture problem, do not read engineering blogs. Read papers on urban planning, slime mold propagation, or ancient military logistics. The structure of the solution often exists; it’s just labeled differently.

4. Signal-Seek in the Noise (The Groan Zone)

There is a phase in group dynamics known as the "Groan Zone"—the uncomfortable space between divergent ideation and convergent decision-making. Most people rush to exit this zone because it feels messy.

• Dwell in the Discomfort: The fringe is uncomfortable because it lacks social validation. If an idea feels "cringy" or "weird" to the consensus, it is protected from competition.
• Action: Monitor the "edges" of communities. What are the grey-hat hackers, the bio-hackers, or the extreme hobbyists doing that looks "inefficient"? Efficiency is a metric for the center; novelty is the currency of the fringe.[6][7]

Conclusion: The Metacognition of Discovery

Finding divergent ideas is not a stroke of luck; it is a workflow. It requires a "metacognitive scaffolding" that allows you to suspend judgment and entertain the impossible long enough to see its utility.[8]

The problems of the next decade will not be solved by refining the solutions of the last. They will be solved by the things currently living in the fringes—the weird, the discarded, and the divergent. To solve the near emergent, you must be willing to look where no one else is looking.

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" The center is crowded with mimetic desire and consensus thinking ", " In technology and philosophy, "dead" ideas are often just premature. "