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.
8 questions →Tech Leadership
Architecture, code quality, technical due diligence, and engineering-leadership questions for CTOs and founders.
6 questions →Hiring & Engagement
Hiring, outsourcing, dedicated teams, and engagement models - how to build and scale development teams.
5 questions →CRM
Straight answers on CRM: what founders and teams actually want to know before getting started with planning and building a CRM solutions.
6 questions →Recently answered
After vibe-coding an MVP, should I hire a team to harden it?
Once your MVP has real users or paying customers, yes. Vibe coding is built for validation, not for production scale, and the moment real people depend on your app, it needs professional hardening. But hire based on traction, not fear: a dedicated team is the right step when the idea is proven and growth is real, not while you're still testing the concept.
Read the answer →What is vibe coding?
Vibe coding is building software by describing what you want to an AI tool (like Cursor, Lovable, or Bolt) in plain language and accepting the code it writes, often without reviewing it. Coined by Andrej Karpathy in February 2025, it's fast and ideal for prototypes, but risky for production without expert review.
Read the answer →Can a fractional CTO rescue a vibe-coded MVP?
Yes, and it's often the right first move. A fractional CTO gives you senior technical judgment part-time: they audit what you've built, decide what to keep, fix, or rebuild, and lead the work, without the cost of a full-time CTO. For a non-technical founder with a vibe-coded MVP and no in-house engineer, it's the fastest way to get an expert steering the ship.
Read the answer →How do you run technical due diligence on an AI-built product?
Treat an AI-built product like any acquisition, then add AI-specific checks. Assess code quality, security, scalability, and IP ownership as usual, but pay extra attention to whether anyone understands the codebase, whether it has tests, and who actually owns AI-generated code. You can run this yourself, but a fractional CTO does it faster and catches what an untrained eye misses. The biggest risk isn't bad code; it's a product no one can safely maintain or legally claim.
Read the answer →How do you avoid downtime during a CRM migration?
You avoid downtime by never flipping a switch. Run the old and new CRM in parallel, migrate data in validated batches, and cut over in phases during low-traffic windows, with a tested rollback ready. Sales keeps working the whole time. The businesses that suffer outages are the ones that attempt a single overnight "big bang" migration.
Read the answer →Will AI replace the work my sales team does in the CRM?
No. AI replaces the CRM admin work your reps hate, not the selling. It automates data entry, call logging, follow-up drafts, and forecasting, giving reps hours back each week. Relationship building, negotiation, and judgment stay human. The teams that win treat AI as a co-pilot that removes busywork, not a replacement for salespeople.
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