# Juan Pablo Moreno (@master_jpma) on x

- id: koinon:creator:x_master_jpma
- url: https://koinonlink.com/kol/x/master_jpma
- schema_version: 1.4

## Identity
- platform: x
- handle: master_jpma
- platform_url: https://twitter.com/master_jpma
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1669
- following: 947
- posts_total: 1555
- posts_observed: 7
- posts_per_day: 0.381
- account_age_days: 4083
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00419
- best_post_interactions: 7
- 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: ai_tools
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: AI agent development, e-commerce automation, workflow architecture, AI model adoption challenges, SaaS building with AI
- bio: Building AI agents and automation systems, sharing experiments, workflows, architecture, and lessons learned along the way.

## Audience (inferred)
- status: present
- description: Building AI agents and automation systems for e-commerce, primarily indie hackers, SaaS founders, and technical product builders
- roles: automation
- seniority: practitioner
- pain_points: Struggling to keep up with rapid AI model advancements and feeling pressure to constantly rebuild workflows, Frustrated by the ego-driven mindset around new AI releases that disrupt existing systems, Having difficulty designing end-to-end AI-powered e-commerce automation workflows from scratch
- posts_analysed: 4
- confidence: 0.4

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

## Quality signals
- authenticity_score: 58
- authenticity_basis: engagement_observed
- credibility_score: 58
- flagged_for_review: false
- koinon_bd_grade: B — 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_master_jpma#013aee95] I'm building a second SaaS. This one is focused on covering a full ecommerce ecosystem: - lead qualification - abandoned cart recovery - customer support - order status automation - all through AI agents The first product taught me how messy real conversations are. This one is ab (https://twitter.com/master_jpma/status/2069802388165132634)
- [x_master_jpma#589de78e] The fastest way to look outdated in 2026 is to keep saying "AI can't do X" based on what you tried 8 months ago. The capability curve is steep. Most opinions are expired.
- [x_master_jpma#165713d5] The ego problem with new models is real. Every release makes people feel like they need to restart their entire workflow. The ones who win treat new models as upgrades to an existing system, not as a reason to rebuild everything from zero.
- [x_master_jpma#e6445ee3] I have to be honest: Opus 5 has complete

## 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=20, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=20, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=20, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=80, 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=80, 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=80, 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: 80
- audience_updated_days_ago: 20

## AI retrieval
- indexing_requests: 8
- 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_master_jpma
- Request removal: https://koinonlink.com/claim?k=x_master_jpma
- Terms: https://koinonlink.com/for-ai