#!/usr/bin/env python3
"""Generate Roberto Aguirre CV for Anthropic Fellows Program — Economics & Policy track."""
from reportlab.lib.pagesizes import A4
from reportlab.lib.units import mm
from reportlab.lib.colors import HexColor
from reportlab.platypus import (
SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, HRFlowable
)
from reportlab.lib.styles import ParagraphStyle
from reportlab.lib.enums import TA_RIGHT, TA_JUSTIFY
OUTPUT = "/home/clawd/playgrounds/miles/cv-roberto-anthropic.pdf"
C_BLACK = HexColor("#0d0d0d")
C_MID = HexColor("#444444")
C_LIGHT = HexColor("#666666")
C_FAINT = HexColor("#cccccc")
C_BODY = HexColor("#333333")
C_GREY = HexColor("#555555")
def S(name, **kw):
return ParagraphStyle(name, **kw)
NAME = S("name", fontName="Times-Bold", fontSize=17, leading=21, textColor=C_BLACK, spaceAfter=1)
TITLEL = S("tl", fontName="Times-Roman", fontSize=8.5, leading=11, textColor=C_MID, spaceAfter=2)
CONTACT = S("ct", fontName="Helvetica", fontSize=7.2, leading=10, textColor=C_GREY)
SECTITLE = S("st", fontName="Helvetica-Bold", fontSize=6.8, leading=9, textColor=C_BLACK, spaceBefore=1, spaceAfter=2)
COMPANY = S("co", fontName="Helvetica-Bold", fontSize=8, leading=10, textColor=C_BLACK)
PERIOD = S("per", fontName="Helvetica", fontSize=7.4, leading=10, textColor=C_LIGHT, alignment=TA_RIGHT)
ROLE = S("ro", fontName="Helvetica-Oblique", fontSize=7.5, leading=9, textColor=C_MID, spaceAfter=1)
BODY = S("bo", fontName="Helvetica", fontSize=7.4, leading=10.5,textColor=C_BODY, spaceAfter=4, alignment=TA_JUSTIFY)
SUMMARY = S("su", fontName="Times-Roman", fontSize=7.8, leading=11.5,textColor=HexColor("#222222"), spaceAfter=0, alignment=TA_JUSTIFY)
BULLET = S("bu", fontName="Helvetica", fontSize=7.4, leading=10.5,textColor=C_BODY, spaceAfter=2, alignment=TA_JUSTIFY)
EDU_DEG = S("edg", fontName="Helvetica-Bold", fontSize=7.8, leading=10, textColor=C_BLACK)
EDU_SCH = S("esc", fontName="Helvetica", fontSize=7.2, leading=9, textColor=C_MID, spaceAfter=2)
SKILL_B = S("skb", fontName="Helvetica-Bold", fontSize=7.4, leading=10, textColor=C_BLACK)
SKILL_V = S("skv", fontName="Helvetica", fontSize=7.4, leading=10, textColor=C_BODY)
def hr():
return HRFlowable(width="100%", thickness=0.5, color=C_FAINT, spaceAfter=2)
def section(title):
return [Spacer(1, 1*mm), Paragraph(title.upper(), SECTITLE), hr()]
def job(company_name, period_str, role_str, desc):
tbl = Table(
[[Paragraph(company_name, COMPANY), Paragraph(period_str, PERIOD)]],
colWidths=[120*mm, 56*mm],
)
tbl.setStyle(TableStyle([
("VALIGN", (0,0), (-1,-1), "BOTTOM"),
("LEFTPADDING", (0,0), (-1,-1), 0),
("RIGHTPADDING", (0,0), (-1,-1), 0),
("TOPPADDING", (0,0), (-1,-1), 0),
("BOTTOMPADDING",(0,0), (-1,-1), 0),
]))
return [tbl, Paragraph(role_str, ROLE), Paragraph(desc, BODY)]
def build():
doc = SimpleDocTemplate(
OUTPUT, pagesize=A4,
leftMargin=13*mm, rightMargin=13*mm,
topMargin=7*mm, bottomMargin=7*mm,
title="Roberto Javier Aguirre Guardia — Anthropic Fellows Program",
)
story = []
# ── HEADER ───────────────────────────────────────────────────────────────
story.append(Paragraph("Roberto Javier Aguirre Guardia", NAME))
story.append(Paragraph(
"AI Economics Researcher & Practitioner — Labor Markets, Digital Transformation, and AI Adoption in Emerging Economies",
TITLEL))
story.append(Paragraph(
"aguirrerjg@gmail.com | +57 317 675 0419 "
" | Bogota, Colombia "
" | linkedin.com/in/roberto-javier-aguirre-guadia",
CONTACT))
story.append(Spacer(1, 2.5*mm))
# ── SUMMARY ──────────────────────────────────────────────────────────────
story += section("Summary")
story.append(Paragraph(
"Systems engineer with MBA and 20+ years at the intersection of technology, management, and economic transformation across Latin America. "
"Combines practitioner experience deploying AI-augmented workflows in fintech, healthcare, and public services with empirical research on how "
"managers adopt, resist, and adapt to AI-driven change. Founder of AI4Managers — a 500+ member LATAM community generating longitudinal "
"observational data on AI adoption curves in mid-market organizations. Applies Python, Claude API, and multi-agent orchestration to build "
"the quantitative tools needed to study AI's economic and labor-market implications at scale.",
SUMMARY))
story.append(Spacer(1, 1*mm))
# ── RESEARCH INTERESTS ───────────────────────────────────────────────────
story += section("Research Interests")
interests = [
"Labor market implications of AI in Latin America: occupational displacement, task re-composition, and wage dynamics "
"in management-intensive roles across fintech, banking, and public services.",
"AI adoption curves in financial services: firm-level heterogeneity in adoption rates, productivity returns, "
"and barriers in regulated industries (pensions, payments, insurance) in emerging markets.",
"Economic models for AI-driven productivity in management: measuring how LLM-augmented decision-making alters "
"span of control, organizational hierarchy, and output per manager — drawing on primary data from AI4Managers community.",
]
for item in interests:
story.append(Paragraph(f"• {item}", BULLET))
# ── EXPERIENCE ───────────────────────────────────────────────────────────
story += section("Professional Experience")
story += job(
"DigitalHubAssist LLC",
"Oct 2024 – Present",
"Manager, AI Engineering & Research",
"Lead engineering and research for a GenAI/SaaS platform serving medical professionals across LATAM. "
"Designed and deployed multi-agent systems (conversational assistants, voice transcription, teleconsultation) "
"in a high-sensitivity regulatory environment. Builds proprietary datasets on AI-augmented clinical workflows "
"to assess productivity and safety outcomes — a direct empirical contribution to AI impact research."
)
story += job(
"AI4Managers — Founder & Lead Researcher",
"2024 – Present",
"Education Practitioner / Applied Researcher",
"Founded and scaled a 500+ member LATAM community of managers navigating AI adoption. "
"Generates primary observational data on how mid-market managers learn, adopt, and resist AI tools "
"across industries including banking, logistics, and professional services. Conducts structured interviews "
"and cohort analyses that constitute a de facto longitudinal study on managerial AI adoption in emerging economies."
)
story += job(
"NTT DATA Colombia",
"Apr 2021 – Oct 2024",
"Consulting Manager — Financial Services & Utilities",
"Led Colombia's largest consulting engagement for Grupo AVAL (top-4 banking group), managing concurrent "
"technology transformation programs. Directed AI-readiness assessments and process automation initiatives "
"impacting 10,000+ employees. Maintained lowest staff turnover on account; delivered against financial KPIs "
"in a macro environment of accelerating digital disruption and competitive pressure from neobanks."
)
story += job(
"VASS Colombia",
"Nov 2015 – Apr 2021",
"Project Manager — Digital Transformation, Pension & Financial Sectors",
"Directed digitalization of Porvenir Private Pension Fund's member-facing channels — a program affecting "
"millions of beneficiaries. Managed transition of legacy processes to digital-first workflows, generating "
"first-hand evidence on workforce reskilling costs and productivity gains from technology adoption "
"in a regulated savings environment."
)
story += job(
"Tecnocom Colombia / GlobalHitss",
"Aug 2012 – Nov 2015",
"Digital Transformation Leader — Public Sector & Insurance",
"Directed judicial branch digitalization (PMP methodology) and led e-commerce and landing-page "
"implementations for healthcare (COLSANITAS) and insurance (CARDIF/BNP Paribas). "
"Early practitioner of platform economics applied to public services in Colombia."
)
# ── EDUCATION ────────────────────────────────────────────────────────────
story += section("Education")
edu_data = [
["Master of Business Administration (MBA)", "Tecnologico de Monterrey, Mexico | 2004"],
["B.Sc. Systems Engineering — Top Third of Class", "Universidad de Lima, Peru | 1999"],
]
for deg, sch in edu_data:
story.append(Paragraph(deg, EDU_DEG))
story.append(Paragraph(sch, EDU_SCH))
# ── KEY ACHIEVEMENTS ─────────────────────────────────────────────────────
story += section("Key Achievements")
achievements = [
"Recognized by Dinero magazine (Colombia's leading business publication) as high-impact startup in LATAM healthcare AI.",
"Selected keynote speaker at CLARO technology summit on digital transformation challenges in enterprise organizations.",
"Founding professor, Innovation chair — Specialization in Project Management, Universidad Sergio Arboleda (Bogota).",
"Certified Liferay Digital Experience expert; supervised 20+ platform migrations across financial and public-sector clients.",
]
for item in achievements:
story.append(Paragraph(f"• {item}", BULLET))
# ── TECHNICAL SKILLS ─────────────────────────────────────────────────────
story += section("Technical Skills")
skills = [
("Languages & Libraries:", "Python (pandas, NumPy, requests, SQLite), SQL, Bash"),
("AI & LLM Tooling:", "Claude API, OpenAI API, multi-agent orchestration, LLM prompt engineering, RAG pipelines"),
("Data & Research:", "Apify scraping, SQLite-vec embeddings, Supabase, REST APIs, observational dataset construction"),
("Platforms & Infra:", "Linux/Systemd, Docker, Vercel, GitHub Actions, SvelteKit"),
("Methodologies:", "Agile PM, PMP, mixed-methods research design, structured stakeholder interviews"),
]
skill_rows = []
for label, val in skills:
row = Table(
[[Paragraph(label, SKILL_B), Paragraph(val, SKILL_V)]],
colWidths=[48*mm, 128*mm],
)
row.setStyle(TableStyle([
("VALIGN", (0,0), (-1,-1), "TOP"),
("LEFTPADDING", (0,0), (-1,-1), 0),
("RIGHTPADDING", (0,0), (-1,-1), 2),
("TOPPADDING", (0,0), (-1,-1), 0),
("BOTTOMPADDING",(0,0), (-1,-1), 2),
]))
skill_rows.append(row)
for row in skill_rows:
story.append(row)
doc.build(story)
print(f"PDF saved → {OUTPUT}")
if __name__ == "__main__":
build()