Straight answers from our engineers
Expert, reviewed answers to the questions founders and engineering leaders actually ask - on building with AI, technical leadership, and hiring development teams.
Building with AI
Straight answers on building software with AI - production-readiness, code audits, AI agents, and choosing an AI-assisted partner.
10 questions →Tech Leadership
Architecture, code quality, technical due diligence, and engineering-leadership questions for CTOs and founders.
11 questions →Hiring & Engagement
Hiring, outsourcing, dedicated teams, and engagement models - how to build and scale development teams.
14 questions →CRM
Straight answers on CRM: what founders and teams actually want to know before getting started with planning and building a CRM solutions.
14 questions →Recently answered
What does a software development team structure look like?
A typical software development team has a technical lead, frontend and backend developers, a QA engineer, a UI/UX designer, and a product or project owner who sets direction. Small teams combine roles; larger ones split them. The right structure isn't a fixed template, it's the smallest set of roles that covers strategy, building, quality, and design for your product.
Read the answer →Custom AI CRM vs Salesforce Einstein: which should I choose?
Choose Salesforce Einstein if you're already on Salesforce and want AI features fast within that ecosystem. Choose a custom AI CRM if you want AI shaped to your exact workflows, full control over your data, and no escalating per-seat AI fees. The decision is really about fit and ownership versus speed inside an existing platform.
Read the answer →Should I outsource QA and testing?
Outsource QA when you need testing capacity, speed, or specialized skills you can't justify hiring full-time, which is most growing teams. It gives you experienced testers and tools without the fixed cost. Keep QA in-house when deep, ongoing product knowledge is critical and you have steady volume. For many companies, a hybrid works best.
Read the answer →How do you keep CRM data secure when you add AI or LLMs?
Control four things: what data the AI is allowed to see, where it's processed, whether it's used to train external models, and who can access AI features. The safest setups expose only the data the AI needs, use providers that don't train on your data, and keep sensitive processing in controlled environments. Done right, adding AI doesn't weaken CRM security.
Read the answer →What should I look for in an agency for regulated industries?
Look for an agency with proven experience in your specific regulation (HIPAA, PCI DSS, GDPR), recognized security certifications like ISO 27001, and evidence they build compliance in from the start rather than bolting it on. In regulated industries, "we can figure out compliance" isn't good enough. Demand proof, not promises, because the cost of getting it wrong is yours.
Read the answer →How do I compare agency quotes that look very different?
Compare scope, not just the number. Quotes vary wildly because they include different things: some cover only coding, others include design, testing, project management, and support. Normalize them by listing exactly what each includes, then compare like for like. A cheap quote that omits testing and support usually isn't cheaper; it's incomplete.
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