In-between Tech stacks

This is my brain dump of how I’m finding myself navigating between the tech stacks… this time in between AI and data engineering landscape.

The Enterprise Tech Stack (aka steering the Titanic)

• Enterprise-grade tools. Think Salesforce, Snowflake, SAP etc. The heavy emphasis on corporate standards and compliance. Its hard to tell what kind of coverage you need and its all very boring because of…

Decisioning (Process / Governance)

The established processes of approvals, change management, and compliance reviews etc. Things are not always clear and the decision-making / approval hierarchies make it such a time drain especially when it comes to…

Deliverables: Long-term, large-scale implementations (e.g., dashboards integrated with ERP systems)

Because lets be real its all about the scalability, security, and regulatory compliance. And speaking of compliance…

The Learning Curve - where its just mostly compliance

• Sure there’s structured onboarding with detailed documentation, SOPs, and corporate training. But lets be honest- bronze, silver, gold medallion architectures are just as foggy as all the wars in the middle east.

Entrepreuner Tech Stack

• Extensive use of the quick and dirty: Excel / NoEmail (my pun on NoSQL)
• Lightweight tech stacks e.g. MongoDB, Ruby on Rails, or Node.js for agility. BYOD is like fire - can be a great tool or a weapon that works against you.

Decisioning

• Fast-paced, immediate decision cycles—often during impromptu whiteboard sessions. Minimal bureaucracy, focus on rapid iterations.

~Learning~ Trial-by-Fire

• Immediate immersion in fast-moving environments with real-world impact. Learn new tools and concepts quickly, often with minimal guidance.

Enterprise Role (ASX50, Large Corporates)

Meetings & Presentations Structured, formal meetings with cross-departmental teams.

Tech Stack Enterprise-grade tools. Think Salesforce, Snowflake, SAP etc. Heavy reliance on corporate standards and compliance.

Process & Governance / Decision making Established processes with approvals, change management, and compliance reviews. Not always clear and also lengthy decision-making / approval hierarchies.

Deliverables Long-term, large-scale implementations (e.g., dashboards integrated with ERP systems). Focus on scalability, security, and regulatory compliance.

Work Environment Collaborative but hierarchical. formal attire, open desk space, predictable work hours

Learning Curve Structured onboarding with detailed documentation, SOPs, and corporate training. Less immediate exposure to risk; mistakes are caught early through governance.

Work Style Clearly defined roles, allowing focus on specific tasks. Startup Role (Entrepreneur / Stealth Mode)

Hands-on Analysis & Quick Prototyping Extensive use of the quick and dirty: Excel, web-based tools etc

Tech Lightweight tech stacks e.g. MongoDB, Ruby on Rails, or Node.js for agility. BYOD is like fire - can be a great tool or a weapon that works against you.

Decision Making Fast-paced, immediate decision cycles—often during impromptu whiteboard sessions. Minimal bureaucracy, focus on rapid iterations.

Deliverables Quick MVPs, prototypes, or actionable insights to drive product decisions. Small-scale solutions that prioritize flexibility and speed over long-term scalability.

Work Environment Flat hierarchy, close-knit team, open desks. Casual attire, longer but flexible work hours

Trial-by-Fire Immediate immersion in fast-moving environments with real-world impact. Learn new tools and concepts quickly, often with minimal guidance.

Risk & Experimentation Directly test and deploy solutions with customers; breaking things is part of the process. High stakes: fast failure and faster recovery are integral to success.

Work Style Multitasking across roles and responsibilities.