u/Frequent_Trainer_128

I was frustrated with monday's native date automations — they fire in a daily batch window, not at the actual time in my DateTime column. So I built Precise Triggers.

\*\*The problem:\*\*

"When date arrives" triggers in the morning regardless of whether your due time is 14:30 or 23:00. If you need a status to flip at a specific moment (SLA deadlines, shift handoffs, client meetings), native workflows don't cut it.

\*\*What my app does:\*\*

\- Reads the full DateTime from any date column

\- Fires the action within seconds of that time

\- Actions: Change Status, Notify Person, Send Webhook

\- Optional condition check at fire time

\- Auto-reschedules when you change a date

\*\*Demo (30 sec):\*\* [https://precisetriggers.com/demo.mp4\](https://precisetriggers.com/demo.mp4)

\*\*Install (free, no credit card):\*\* [https://precisetriggers.com\](https://precisetriggers.com)

\*\*Step-by-step guide:\*\* [https://precisetriggers.com/blog/schedule-status-change-monday.html\](https://precisetriggers.com/blog/schedule-status-change-monday.html)

It's free for 14 days and includes 25 automations/month on the free tier. Not on the marketplace (rejected because "native workflows exist"), so it's distributed directly.

Early adopter deal: use code \*\*EARLY50\*\* at checkout for 50% off your first year.

Would love feedback from anyone who's run into this timing issue.

I was frustrated with monday's native date automations — they fire in a daily batch window, not at the actual time in my DateTime column. So I built Precise Triggers.

**The problem:**

"When date arrives" triggers in the morning regardless of whether your due time is 14:30 or 23:00. If you need a status to flip at a specific moment (SLA deadlines, shift handoffs, client meetings), native workflows don't cut it.

**What my app does:**

- Reads the full DateTime from any date column

- Fires the action within seconds of that time

- Actions: Change Status, Notify Person, Send Webhook

- Optional condition check at fire time

- Auto-reschedules when you change a date

**Demo (30 sec):** https://precisetriggers.com/demo.mp4

**Install (free, no credit card):** https://precisetriggers.com

**Step-by-step guide:** https://precisetriggers.com/blog/schedule-status-change-monday.html

It's free for 14 days and includes 25 automations/month on the free tier. Not on the marketplace (rejected because "native workflows exist"), so it's distributed directly.

Early adopter deal: use code **EARLY50** at checkout for 50% off your first year.

Would love feedback from anyone who's run into this timing issue.

I was frustrated with monday's native date automations — they fire in a daily batch window, not at the actual time in my DateTime column. So I built Precise Triggers.

The problem:

"When date arrives" triggers in the morning regardless of whether your due time is 14:30 or 23:00. If you need a status to flip at a specific moment (SLA deadlines, shift handoffs, client meetings), native workflows don't cut it.

What my app does:

- Reads the full DateTime from any date column

- Fires the action within seconds of that time

- Actions: Change Status, Notify Person, Send Webhook

- Optional condition check at fire time

- Auto-reschedules when you change a date

**Demo (30 sec):**https://precisetriggers.com/demo.mp4

Install (free, no credit card): https://precisetriggers.com

Step-by-step guide: https://precisetriggers.com/blog/schedule-status-change-monday.html

It's free for 14 days and includes 25 automations/month on the free tier. Not on the marketplace (rejected because "native workflows exist"), so it's distributed directly.

Early adopter deal: use code EARLY50 at checkout for 50% off your first year.

Would love feedback from anyone who's run into this timing issue.

Hi everyone,

I'm a Python backend developer based in Guimarães, Portugal (WET/UTC+0), available for remote work. I've spent the last 2+ years building internal web apps and REST APIs that real, non-technical teams use every day in production — not just side projects.

What I do:

Backend APIs with FastAPI and Flask (REST, Pydantic, SQLAlchemy)

SQL databases (PostgreSQL, MySQL, SQLite) — data modeling and query optimization

ETL pipelines and automation with Python (Pandas, NumPy)

BI dashboards (Power BI, Tableau) connected to Python/SQL backends

Deployment with Docker, Vercel, CI/CD via GitHub Actions

A bit of proof:

At a manufacturing company I built and maintained 3+ internal apps used daily across production and operations teams, plus KPI dashboards for leadership.

As a data analyst for a government agency in Brazil, I built ETL pipelines and dashboards that became the single source of truth for regional reporting.

Most recent project: Lanez — an open-source MCP server that connects Microsoft 365 to any AI client (Claude Desktop, Cursor, etc.). It does semantic search across Calendar/Mail/OneNote/OneDrive, persistent memory, and auto-generated pre-meeting briefings. Stack: FastAPI, PostgreSQL + pgvector, Redis, Claude API, Microsoft Graph.

Currently expanding into: full-stack with Next.js/React/TypeScript (this portfolio is built with it).

Looking for: backend or full-stack roles, contract or full-time, remote.

Rates: flexible / open to discussion depending on scope and engagement length.

Languages: Portuguese (native), English (B1), French (A2).

Portfolio: https://lanez.pt GitHub: https://github.com/LucasMilanez LinkedIn: https://linkedin.com/in/lucas--milanez

Happy to share code samples or do a technical chat. DM me or drop a comment. Thanks for reading!

Hi everyone,

I'm a Python backend developer based in Guimarães, Portugal (WET/UTC+0), available for remote work. I've spent the last 2+ years building internal web apps and REST APIs that real, non-technical teams use every day in production — not just side projects.

What I do:

Backend APIs with FastAPI and Flask (REST, Pydantic, SQLAlchemy)

SQL databases (PostgreSQL, MySQL, SQLite) — data modeling and query optimization

ETL pipelines and automation with Python (Pandas, NumPy)

BI dashboards (Power BI, Tableau) connected to Python/SQL backends

Deployment with Docker, Vercel, CI/CD via GitHub Actions

A bit of proof:

At a manufacturing company I built and maintained 3+ internal apps used daily across production and operations teams, plus KPI dashboards for leadership.

As a data analyst for a government agency in Brazil, I built ETL pipelines and dashboards that became the single source of truth for regional reporting.

Most recent project: Lanez — an open-source MCP server that connects Microsoft 365 to any AI client (Claude Desktop, Cursor, etc.). It does semantic search across Calendar/Mail/OneNote/OneDrive, persistent memory, and auto-generated pre-meeting briefings. Stack: FastAPI, PostgreSQL + pgvector, Redis, Claude API, Microsoft Graph.

Currently expanding into: full-stack with Next.js/React/TypeScript (this portfolio is built with it).

Looking for: backend or full-stack roles, contract or full-time, remote.

Rates: flexible / open to discussion depending on scope and engagement length.

Languages: Portuguese (native), English (B1), French (A2).

Portfolio: https://lanez.pt GitHub: https://github.com/LucasMilanez LinkedIn: https://linkedin.com/in/lucas--milanez

Happy to share code samples or do a technical chat. DM me or drop a comment. Thanks for reading!

Hi everyone,

I'm a Python backend developer based in Guimarães, Portugal (WET/UTC+0), available for remote work. I've spent the last 2+ years building internal web apps and REST APIs that real, non-technical teams use every day in production — not just side projects.

What I do:

Backend APIs with FastAPI and Flask (REST, Pydantic, SQLAlchemy)

SQL databases (PostgreSQL, MySQL, SQLite) — data modeling and query optimization

ETL pipelines and automation with Python (Pandas, NumPy)

BI dashboards (Power BI, Tableau) connected to Python/SQL backends

Deployment with Docker, Vercel, CI/CD via GitHub Actions

A bit of proof:

At a manufacturing company I built and maintained 3+ internal apps used daily across production and operations teams, plus KPI dashboards for leadership.

As a data analyst for a government agency in Brazil, I built ETL pipelines and dashboards that became the single source of truth for regional reporting.

Most recent project: Lanez — an open-source MCP server that connects Microsoft 365 to any AI client (Claude Desktop, Cursor, etc.). It does semantic search across Calendar/Mail/OneNote/OneDrive, persistent memory, and auto-generated pre-meeting briefings. Stack: FastAPI, PostgreSQL + pgvector, Redis, Claude API, Microsoft Graph.

Currently expanding into: full-stack with Next.js/React/TypeScript (this portfolio is built with it).

Looking for: backend or full-stack roles, contract or full-time, remote.

Rates: flexible / open to discussion depending on scope and engagement length.

Languages: Portuguese (native), English (B1), French (A2).

Portfolio: https://lanez.pt GitHub: https://github.com/LucasMilanez LinkedIn: https://linkedin.com/in/lucas--milanez

Happy to share code samples or do a technical chat. DM me or drop a comment. Thanks for reading!

Tenho andado a estudar como os Applicant Tracking Systems processam CVs e porque tantos candidatos não recebem respostas. Partilho notas caso seja útil.

As três fases de processamento ATS:

Parsing. O sistema lê o PDF e tenta extrair dados estruturados: nome, datas, funções, formação, competências. Se o parsing falha ou produz lixo, a candidatura está morta.

Keyword matching. O texto do CV é comparado com a descrição da vaga. O score de match determina o ranking.

Ranking. Recrutadores normalmente só revêem a parte superior da fila. O resto é invisível.

Falhas comuns de parsing:

Layouts em múltiplas colunas. A maioria dos parsers lê linha a linha da esquerda para a direita. Duas colunas produzem output desordenado onde os cargos ficam misturados com a formação.

Tabelas. Secções de skills construídas como tabelas frequentemente parseiam como uma string ilegível.

Cabeçalhos e rodapés. Contactos colocados aí são frequentemente ignorados.

Ícones, gráficos, texto como imagem. Não são extraídos. Se o teu nome está renderizado como parte de um cabeçalho gráfico, o sistema não tem nome no registo.

Cabeçalhos de secção não-standard. "Sobre mim" ou "A minha história" em vez de "Perfil" ou "Resumo" reduz a precisão do match.

Exports de ferramentas de design. Canva e Figma podem achatar texto em imagem dependendo das definições de export. Catastrófico para parsing.

O que funciona:

Coluna única. Nomes standard de secção. Fontes standard (Arial, Calibri, Helvetica). PDF exportado de Word ou Google Docs (baseado em texto, não em imagem). Ordem cronológica inversa.

Diferenças de formato por país na UE:

Um CV correctamente formatado varia significativamente entre países. Só as expectativas em relação à foto diferem:

Reino Unido e Irlanda - sem foto, geralmente sem dados pessoais (data nascimento, estado civil). Inclui-los cria preocupações de discriminação.

Alemanha - foto esperada, data de nascimento e nacionalidade habituais, assinatura no fim do Lebenslauf.

França - foto opcional, uma página para menos de 10 anos de experiência.

Países Baixos - tendência a remover foto, duas páginas standard.

Países Nórdicos - sem foto, foco em conquistas, brevidade valorizada.

Mesma pessoa, mesma experiência, formato correcto diferente por país. Tradução por si só não localiza um CV.

Princípios de keywords:

Usar a redacção exacta do anúncio onde for verdade. "Gestão de stakeholders" e "relação com clientes" descrevem skills sobrepostas mas o ATS trata como termos diferentes.

Carregar keywords no início. Skills devem aparecer no Perfil e nos bullets da primeira função, não enterradas no fim.

Estrutura de bullets para revisão humana:

Depois de passar o filtro, recrutadores gastam cerca de 7 segundos na primeira leitura. Bullets sem números são saltados. "Responsável pela gestão de equipa" lê-se como filler. "Geri equipa de 5 pessoas, reduzi backlog de tickets de 200 para 40 em 3 meses" chama atenção.

Números, verbos, resultados. Em cada linha.

Disponível para responder a questões.