# Mike Heap (@mike_heap_) on x

- id: koinon:creator:x_mike_heap_
- url: https://koinonlink.com/kol/x/mike_heap_
- schema_version: 1.4

## Identity
- platform: x
- handle: mike_heap_
- platform_url: https://twitter.com/mike_heap_
- website: https://myaskai.com/?utm_source=twitter&utm_medium=organic_social&utm_content=profile_mike
- country: United Kingdom
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 2169
- following: 502
- posts_total: 7915
- posts_observed: 13
- posts_per_day: 4.997
- account_age_days: 1584
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.01291
- best_post_interactions: 28
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: saas
- category_confidence: 0.8
- category_source: derived_from_recent_content
- topics: AI-powered knowledge extraction, Bootstrapped SaaS growth, Product-market fit for B2B startups, Leveraging podcasts for team learning, Using AI to automate skill-building from content, Cost-benefit analysis of personal tools
- bio: Building a B2B SaaS bootstrapped @usemyaskai

Prev: 3 small sales + many 'failures'

## Audience (inferred)
- status: present
- description: B2B SaaS founders and bootstrapped startup operators, mainly early-stage founders focused on growth and product-market fit
- roles: general_ai
- seniority: practitioner
- pain_points: Struggling to turn podcast insights into actionable skills for their teams, Finding it hard to justify spending on health or wellness tools due to budget constraints, Lacking systematic ways to extract value from external advice and knowledge, Not sure how to apply AI tools effectively to improve team learning and decision-making
- posts_analysed: 2
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 70
- authenticity_basis: engagement_observed
- credibility_score: 70
- flagged_for_review: false
- koinon_bd_grade: A — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_mike_heap_#2e493c35] @thesamparr @ShaanVP after every pod you should turn each guests advice into a skill for listeners. Just put the transcript in Claude etc and ask it to take the key points and make a skill out of it. Then anyone who has a business can turn every one of your pods into something su (https://twitter.com/mike_heap_/status/1780491410116145258)
- [x_mike_heap_#1b61ae79] As long as you can afford it and aren’t a hypochondriac, I really struggle to see the downside of this. Feels like a perfect example of asymmetry - very low risk, highest possible reward. With the work the Midjourney guys are doing too, pretty sure within 5 years, the majority wi

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=81, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=81, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=108, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=81, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=108, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 81
- audience_updated_days_ago: 21

## AI retrieval
- indexing_requests: 6
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_mike_heap_
- Request removal: https://koinonlink.com/claim?k=x_mike_heap_
- Terms: https://koinonlink.com/for-ai